The Circadian Rhythm Gene Arntl2 Is a Metastasis Susceptibility Gene for Estrogen Receptor-Negative Breast Cancer

Resf1 is a compound G4 quadruplex-associated tumor suppressor for triple negative breast cancer

Patients with ER-negative breast cancer have the worst prognosis of all breast cancer subtypes, often experiencing rapid recurrence or progression to metastatic disease shortly after diagnosis. Given that metastasis is the primary cause of mortality in most solid tumors, understanding metastatic biology is crucial for effective intervention. Using a mouse systems genetics approach, we previously identified 12 genes associated with metastatic susceptibility. Here, we extend those studies to identify Resf1, a poorly characterized gene, as a novel metastasis susceptibility gene in ER- breast cancer. Resf1 is a large, unstructured protein with an evolutionarily conserved intron-exon structure, but with poor amino acid conservation. CRISPR or gene trap mouse models crossed to the Polyoma Middle-T antigen genetically engineered mouse model (MMTV-PyMT) demonstrated that reduction of Resf1 resulted in a significant increase in tumor growth, a shortened overall survival time, and increased incidence and number of lung metastases, consistent with patient data. Furthermore, an analysis of matched tail and primary tissues revealed loss of the wildtype copy in tumor tissue, consistent with Resf1 being a tumor suppressor. Mechanistic analysis revealed a potential role of Resf1 in transcriptional control through association with compound G4 quadruplexes in expressed sequences, particularly those associated with ribosomal biogenesis. These results suggest that loss of Resf1 enhances tumor progression in ER- breast cancer through multiple alterations in both transcriptional and translational control.

Activation of the PI3K/AKT signaling pathway by ARNTL2 enhances cellular glycolysis and sensitizes pancreatic adenocarcinoma to erlotinib

BACKGROUND

Pancreatic adenocarcinoma (PC) is an aggressive malignancy with limited treatment options. The poor prognosis primarily stems from late-stage diagnosis and when the disease has become therapeutically challenging. There is an urgent need to identify specific biomarkers for cancer subtyping and early detection to enhance both morbidity and mortality outcomes. The addition of the EGFR tyrosine kinase inhibitor (TKI), erlotinib, to gemcitabine chemotherapy for the first-line treatment of patients with advanced pancreatic cancer slightly improved outcomes. However, restricted clinical benefits may be linked to the absence of well-characterized criteria for stratification and dependable biomarkers for the prediction of treatment effectiveness.

METHODS AND RESULTS

We examined the levels of various cancer hallmarks and identified glycolysis as the primary risk factor for overall survival in PC. Subsequently, we developed a glycolysis-related score (GRS) model to accurately distinguish PC patients with high GRS. Through in silico screening of 4398 compounds, we discovered that erlotinib had the strongest therapeutic benefits for high-GRS PC patients. Furthermore, we identified ARNTL2 as a novel prognostic biomarker and a predictive factor for erlotinib treatment responsiveness in patients with PC. Inhibition of ARNTL2 expression reduced the therapeutic efficacy, whereas increased expression of ARNTL2 improved PC cell sensitivity to erlotinib. Validation in vivo using patient-derived xenografts (PDX-PC) with varying ARNTL2 expression levels demonstrated that erlotinib monotherapy effectively halted tumor progression in PDX-PC models with high ARNTL2 expression. In contrast, PDX-PC models lacking ARNTL2 did not respond favorably to erlotinib treatment. Mechanistically, we demonstrated that the ARNTL2/E2F1 axis-mediated cellular glycolysis sensitizes PC cells to erlotinib treatment by activating the PI3K/AKT signaling pathway.

CONCLUSIONS

Our investigations have identified ARNTL2 as a novel prognostic biomarker and predictive indicator of sensitivity. These results will help to identify erlotinib-responsive cases of PC and improve treatment outcomes. These findings contribute to the advancement of precision oncology, enabling more accurate and targeted therapeutic interventions.

Loss of NAT10 disrupts enhancer organization via p300 mislocalization and suppresses transcription of genes necessary for metastasis progression

Acetylation of protein and RNA represent a critical event for development and cancer progression. NAT10 is the only known RNA acetylase that catalyzes the N4-actylcytidine (ac4C) modification of RNAs. Here, we show that the loss of NAT10 significantly decreases lung metastasis in allograft and genetically engineered mouse models of breast cancer. NAT10 interacts with a mechanosensitive, metastasis susceptibility protein complex at the nuclear pore. In addition to its canonical role in RNA acetylation, we find that NAT10 interacts with p300 at gene enhancers. NAT10 loss is associated with p300 mislocalization into heterochromatin regions. NAT10 depletion disrupts enhancer organization, leading to alteration of gene transcription necessary for metastatic progression, including reduced myeloid cell-recruiting chemokines that results in a less metastasis-prone tumor microenvironment. Our study uncovers a distinct role of NAT10 in enhancer organization of metastatic tumor cells and suggests its involvement in the tumor-immune crosstalk dictating metastatic outcomes.

Interactions of circadian clock genes with the hallmarks of cancer

The molecular machinery of the circadian clock regulates the expression of many genes and processes in the organism, allowing the adaptation of cellular activities to the daily light-dark cycles. Disruption of the circadian rhythm can lead to various pathologies, including cancer. Thus, disturbance of the normal circadian clock at both genetic and environmental levels has been described as an independent risk factor for cancer. In addition, researchers have proposed that circadian genes may have a tissue-dependent and/or context-dependent role in tumorigenesis and may function both as tumor suppressors and oncogenes. Finally, circadian clock core genes may trigger or at least be involved in different hallmarks of cancer. Hence, expanding the knowledge of the molecular basis of the circadian clock would be helpful to identify new prognostic markers of tumorigenesis and potential therapeutic targets.

ARNTL2 upregulation of ACOT7 promotes NSCLC cell proliferation through inhibition of apoptosis and ferroptosis

BACKGROUND

Recent studies have reported that the circadian transcription factor aryl hydrocarbon receptor nuclear translocator like 2 (ARNTL2) promotes the metastatic progression of lung adenocarcinoma. However, the molecular mechanisms of ARNTL2 in non-small cell lung cancer (NSCLC) cell growth and proliferation remain to be explored.

METHODS

The expression of ARNTL2 and acyl-CoA thioesterase 7 (ACOT7) in lung cancer patients was analyzed based on TCGA database. Gain-of-function of ARNTL2 and ACOT7 was conducted by transfecting the cells with plasmids or lentivirus. Knockdown assay was carried out by siRNAs. Western blot and qRT-PCR were performed to check the protein and mRNA expression. Dual luciferase and ChIP-qPCR assay was applied to check the interaction of ARNTL2 on ACOT7's promoter sequence. Triglyceride level, MDA production, the activity of casapase 3 to caspase 7, and lipid ROS were measured by indicated assay kit. Cellular function was detected by CCK8, colony formation and flow cytometry analysis of cell death and cell cycle.

RESULTS

We demonstrated that ARNTL2 upregulation of ACOT7 was critical for NSCLC cell growth and proliferation. Firstly, overexpression of ARNTL2 conferred the poor prognosis of LUAD patients and supported the proliferation of NSCLC cells. Based on molecular experiments, we showed that ARNTL2 potentiated the transcription activity of ACOT7 gene via direct binding to ACOT7's promoter sequence. ACOT7 high expression was correlated with the worse prognosis of LUAD patients. Gain-of-function and loss-of-function experiments revealed that AOCT7 contributed to NSCLC cell growth and proliferation. ACOT7 regulated the apoptosis and ferroptosis of NSCLC cells, while exhibited no effect on cell cycle progression. ACOT7 overexpression also potentiated fatty acid synthesis and suppressed lipid peroxidation. Lastly, we showed that ARNTL2 knockdown and overexpression inhibited and promoted the cellular triglyceride production and subsequent cell proliferation, which could be reversed by ACOT7 overexpression and knockdown.

CONCLUSION

Our study illustrated the oncogenic function of ARNTL2/ACOT7 axis in the development of NSCLC. Targeting ARNTL2 or ACOT7 might be promising therapeutic strategies for NSCLC patients with highly expressed ARNTL2.

Prognostic assessment capability of a five-gene signature in pancreatic cancer: a machine learning based-study

BACKGROUND

A prognostic assessment method with good sensitivity and specificity plays an important role in the treatment of pancreatic cancer patients. Finding a way to evaluate the prognosis of pancreatic cancer is of great significance for the treatment of pancreatic cancer.

METHODS

In this study, GTEx dataset and TCGA dataset were merged together for differential gene expression analysis. Univariate Cox regression and Lasso regression were used to screen variables in the TCGA dataset. Screening the optimal prognostic assessment model is then performed by gaussian finite mixture model. Receiver operating characteristic (ROC) curves were used as an indicator to assess the predictive ability of the prognostic model, the validation process was performed on the GEO datasets.

RESULTS

Gaussian finite mixture model was then used to build 5-gene signature (ANKRD22, ARNTL2, DSG3, KRT7, PRSS3). Receiver operating characteristic (ROC) curves suggested the 5-gene signature performed well on both the training and validation datasets.

CONCLUSIONS

This 5-gene signature performed well on both our chosen training dataset and validation dataset and provided a new way to predict the prognosis of pancreatic cancer patients.

Major roles of the circadian clock in cancer

Circadian rhythms are natural rhythms that widely exist in all creatures, and regulate the processes and physiological functions of various biochemical reactions. The circadian clock is critical for cancer occurrence and progression. Its function is regulated by metabolic activities, and the expression and transcription of various genes. This review summarizes the composition of the circadian clock; the biological basis for its function; its relationship with, and mechanisms in, cancer; its various functions in different cancers; the effects of anti-tumor treatment; and potential therapeutic targets. Research in this area is expected to advance understanding of circadian locomotor output cycles kaput (CLOCK) and brain and muscle ARNT-like protein 1 (BMAL1) in tumor diseases, and contribute to the development of new anti-tumor treatment strategies.

ARNTL2 is an indicator of poor prognosis, promotes epithelial-to-mesenchymal transition and inhibits ferroptosis in lung adenocarcinoma

OBJECTIVES

ARNTL2, as a circadian transcription factor, has been recently proposed to play an important role in a variety of tumors. however, the role of ARNTL2 in lung carcinogenesis and progression remains unclear. The purpose of this study was to investigate the effect of ARNTL2 on the clinical characteristics and prognosis of lung adenocarcinoma and to explore the relationship between ARNTL2 and EMT, ferroptosis in lung adenocarcinoma.

METHODS

The Cancer Genome Atlas (TCGA) database's multi-omics data were downloaded using the Xena browser. Based on the expression levels of ARNTL2, patients with lung adenocarcinoma from TCGA were divided into two groups: those with high ARNTL2 expression and those with low ARNTL2 expression. ARNTL2 was studied for its effects on lung adenocarcinoma's clinicopathological, genomic, and immunological characteristics. Furthermore, in vivo and in vitro assays were used to confirm the impact of ARNLT2 knockdown on lung adenocarcinoma cells.

RESULTS

We found ARNTL2 is highly expressed in lung adenocarcinoma and was an independent predictor of a poor prognosis in patients with lung adenocarcinoma. In addition, we demonstrated that knockdown of ARNTL2 promoted ferroptosis, inhibited EMT, cell proliferation, migration and invasion in lung adenocarcinoma. In contrast, overexpressing ARNTL2 yielded the opposite results.

CONCLUSIONS

ARNTL2 is an independent unfavorable prognostic factor for lung adenocarcinoma. It plays a facilitating role in the development of lung adenocarcinoma, especially in promoting EMT and inhibiting ferroptosis, revealing that ARNTL2 may be a potential biomarker for lung adenocarcinoma.

Development and Validation of a Novel Circadian Rhythm-Related Signature to Predict the Prognosis of the Patients with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most important causes of cancer-related deaths and remains a major public health challenge worldwide. Considering the extensive heterogeneity of HCC, more accurate prognostic models are imperative. The circadian genes regulate the daily oscillations of key biological processes, such as nutrient metabolism in the liver. Circadian rhythm disruption has recently been recognized as an independent risk factor for cancer. In this study, The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were compared and 248 differentially expressed genes (DEGs) of the circadian rhythm were identified. HCC was classified into two subtypes based on these DEGs. The prognostic value of each circadian rhythm-associated gene (CRG) for survival was assessed by constructing a multigene signature from TCGA cohort. A 6-gene signature was created by applying the least absolute shrinkage and selection operator (LASSO) Cox regression method, and all patients in TCGA cohort were divided into high- and low-risk groups according to their risk scores. The survival rate of patients with HCC in the low-risk group was significantly higher than that in the high-risk group (p < 0.001). The patients with HCC in the Gene Expression Omnibus (GEO) cohort were also divided into two risk subgroups using the risk score of TCGA cohort, and the overall survival time (OS) was prolonged in the low-risk group (p = 0.012). Based on the clinical characteristics, the risk score was an independent predictor of OS in the patients with HCC. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that multiple metabolic pathways, cell cycle, etc., were enhanced in the high-risk group. Using the metabolic pathway single-sample gene set enrichment analysis (ssGSEA), it was found that the metabolic pathways in the high- and low-risk groups between TCGA and GEO cohorts were altered essentially in the same way. In conclusion, the circadian genes play an important role in HCC metabolic rearrangements and can be further used to predict the prognosis the patients with HCC.

Host CLIC4 expression in the tumor microenvironment is essential for breast cancer metastatic competence

The TGF-β-regulated Chloride Intracellular Channel 4 (CLIC4) is an essential participant in the formation of breast cancer stroma. Here, we used data available from the TCGA and METABRIC datasets to show that CLIC4 expression was higher in breast cancers from younger women and those with early-stage metastatic disease. Elevated CLIC4 predicted poor outcome in breast cancer patients and was linked to the TGF-β pathway. However, these associations did not reveal the underlying biological contribution of CLIC4 to breast cancer progression. Constitutive ablation of host Clic4 in two murine metastatic breast cancer models nearly eliminated lung metastases without reducing primary tumor weight, while tumor cells ablated of Clic4 retained metastatic capability in wildtype hosts. Thus, CLIC4 was required for host metastatic competence. Pre- and post-metastatic proteomic analysis identified circulating pro-metastatic soluble factors that differed in tumor-bearing CLIC4-deficient and wildtype hosts. Vascular abnormalities and necrosis increased in primary tumors from CLIC4-deficient hosts. Transcriptional profiles of both primary tumors and pre-metastatic lungs of tumor-bearing CLIC4-deficient hosts were consistent with a microenvironment where inflammatory pathways were elevated. Altogether, CLIC4 expression in human breast cancers may serve as a prognostic biomarker; therapeutic targeting of CLIC4 could reduce primary tumor viability and host metastatic competence.

The Circadian Clock and Cancer: Links between Circadian Disruption and Disease Pathology

There is growing evidence that disruption of our 24-hour clock increases our risk for acquiring several diseases and disorders. One of these diseases is cancer. While the mechanistic links between circadian clock disruption and cancer initiation or progression are an active area of study, significantly more work needs to be done to understand the molecular substrates involved. Of particular complexity remains the functions of the clock in individual cells during the process of transformation (cancer initiation) vs. the functions of the clock in tumor-surrounding stroma in the process of tumor progression or metastasis. Indeed, the nexus of cellular circadian dynamics, metabolism, and carcinogenesis is drawing more attention, and many new studies are now highlighting the critical role of circadian rhythms and clock proteins in cancer prevention. In this brief review, we cover some of the basic mechanisms reported to link circadian disruption and cancer at the level of gene expression and metabolism. We also review some of the human studies addressing circadian disruption and cancer incidence as well as some controlled laboratory studies connecting the two in pre-clinical models. Finally, we discuss the tremendous opportunity to use circadian approaches for future prevention and treatment in the context of cancer in specific organs.

ARNTL2 is a Prognostic Biomarker and Correlates with Immune Cell Infiltration in Triple-Negative Breast Cancer

Background

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and is associated with poor prognosis. The aberrant expression of circadian genes contributes to the origin and progression of breast cancer. The present study was designed to explore the potential function and prognosis value of circadian genes in TNBC.

Methods

The transcriptome data of circadian genes were downloaded from The Cancer Genomic Atlas (TCGA), GSE25066 and GSE31448 datasets. The differential expressed circadian genes between non-TNBC and TNBC patients were analysed by Wilcoxon test. Univariate and multivariate Cox regression analyses were employed to identify the prognostic circadian genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were performed to study the biological functions of ARNTL2. The composition of 22 immune cells in the tumour samples was estimated with CIBERSORT algorithm. The correlations between ARNTL2 expression and tumour-infiltrating immune cells were evaluated by Spearman correlation coefficient.

Results

A total of 8 circadian genes were found to be differentially expressed between non-TNBC and TNBC, but only ARNTL2 has prognostic value. Multivariate Cox analysis identified that ARNTL2 was an independent prognosis factor for overall survival and relapse-free survival in TNBC patients. Functionally, ARNTL2 was mainly involved in immune response processes such as positive regulation of cytokine production, regulation of innate immune response, and cellular responses to molecules of bacterial origin. High expression of ARNTL2 was positively correlated with activated CD4 memory T cells, activated mast cells, and neutrophil infiltration and the expression of markers of neutrophils (ITGAM), dendritic cells (HLA-DRA, HLA-DPA1, ITGAM), Th1 (IL1B, STAT1), Th2 (IL13), Th17 (STAT3) and mast cells (TPSB2, TPSAB1).

Conclusion

ARNTL2 may be linked with the functional modulation of the tumour immune microenvironment and serve as a potential biomarker for predicting the prognosis of TNBC patients.

Circadian regulation of cancer cell and tumor microenvironment crosstalk

Circadian rhythms regulate a remarkable variety of physiologic functions in living organisms. Circadian disruption is associated with tumorigenesis and tumor progression through effects on cancer cell biological properties, including proliferation, DNA repair, apoptosis, metabolism, and stemness. Emerging evidence indicates that circadian clocks also play an influential role in the tumor microenvironment (TME). This review outlines recent discoveries on how cancer cell clock components (including circadian clock and clock genes/proteins) regulate TME biology and, reciprocally, how TME clock components affect tumor growth, metastasis, and therapeutic response. An improved understanding of how clock components regulate the symbiosis between cancer cells and the TME will inform the development of novel clock-oriented therapeutic strategies, including immunotherapy.

Upregulation of ARNTL2 is associated with poor survival and immune infiltration in clear cell renal cell carcinoma

Background

Aryl hydrocarbon receptor nuclear translocator like 2 (ARNTL2) is a member of the PAS superfamily. Previous studies explored the carcinogenic roles of transcription factor ARNTL2 in human malignancies. However, its roles in ccRCC have not been elucidated. This study sought to explore the roles of ARNTL2 in ccRCC and determine its correlations with tumor immunity.

Methods

The expression of ARNTL2 was analyzed using the GEO, TCGA and GTEx database, and verified in ccRCC tissue samples and cell lines by qRT-PCR and western blot analysis. Kaplan–Meier survival curve analysis, Cox regression analysis (including univariate and multivariate analysis) was utilized to evaluate the prognostic values of ARNTL2. Potential biological mechanisms of ARNTL2 were explored using GSEA method. Colony formation and wound healing assays were conducted to explore the oncogenic role of ARNTL2 in ccRCC. ssGSEA and xCell algorithm were used to explore the correlation between ARNTL2 expression and tumor immune microenvironment (TIME).

Results

ARNTL2 was significantly upregulated in ccRCC tissues and cell lines compared to normal kidney tissues and cell line. Enhanced expression of ARNTL2 was strongly linked to advanced clinical stage and unfavorable overall survival in ccRCC. ARNTL2 was determined as an independent prognostic marker through cox regression analysis. A prognostic nomogram was constructed to predict 1-, 3- and 5-year overall survival of ccRCC patients by integrating ARNTL2 expression with other clinicopathologic variables. GSEA analysis showed that focal adhesion, T cell receptor, cell cycle, and JAK-STAT signaling pathway were significantly enriched in high ARNTL2 samples. Silencing of ARNTL2 suppressed the colony formation ability and wound healing efficacy of ccRCC cell lines. xCell analysis showed that high expression level of ARNTL2 exhibited an immune infiltration status similar to CD8 + inflamed ccRCC subtype, which was characterized by high infiltration level of CD8 + T cell and high expression level of the immune escape biomarkers such as PD-L1, PD-L2, PD1 and CTLA4.

Conclusion

ARNTL2 is an independent adverse predictor of ccRCC patient survival. High expression level of ARNTL2 is associated with immune infiltration, and may be a novel therapeutic target in ccRCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02046-z.

Mechanisms of breast cancer metastasis

Invasive breast cancer tends to metastasize to lymph nodes and systemic sites. The management of metastasis has evolved by focusing on controlling the growth of the disease in the breast/chest wall, and at metastatic sites, initially by surgery alone, then by a combination of surgery with radiation, and later by adding systemic treatments in the form of chemotherapy, hormone manipulation, targeted therapy, immunotherapy and other treatments aimed at inhibiting the proliferation of cancer cells. It would be valuable for us to know how breast cancer metastasizes; such knowledge would likely encourage the development of therapies that focus on mechanisms of metastasis and might even allow us to avoid toxic therapies that are currently used for this disease. For example, if we had a drug that targeted a gene that is critical for metastasis, we might even be able to cure a vast majority of patients with breast cancer. By bringing together scientists with expertise in molecular aspects of breast cancer metastasis, and those with expertise in the mechanical aspects of metastasis, this paper probes interesting aspects of the metastasis cascade, further enlightening us in our efforts to improve the outcome from breast cancer treatments.

A wild-derived inbred mouse strain, MSM/Ms, provides insights into novel skin tumor susceptibility genes

Cancer is one of the most catastrophic human genetic diseases. Experimental animal cancer models are essential for gaining insights into the complex interactions of different cells and genes in tumor initiation, promotion, and progression. Mouse models have been extensively used to analyze the genetic basis of cancer susceptibility. They have led to the identification of multiple loci that confer, either alone or in specific combinations, an increased susceptibility to cancer, some of which have direct translatability to human cancer. Additionally, wild-derived inbred mouse strains are an advantageous reservoir of novel genetic polymorphisms of cancer susceptibility genes, because of the evolutionary divergence between wild and classical inbred strains. Here, we review mapped Stmm (skintumor modifier of MSM) loci using a Japanese wild-derived inbred mouse strain, MSM/Ms, and describe recent advances in our knowledge of the genes responsible for Stmm loci in the 7,12-dimethylbenz(a)anthracene (DMBA)/12-O-tetradecanoylphorbol-13-acetate (TPA) two-stage skin carcinogenesis model.

ARID1A-dependent permissive chromatin accessibility licenses estrogen-receptor signaling to regulate circadian rhythms genes in endometrial cancer

Estrogen receptor α (ER) acts as an oncogenic signal in endometrial endometrioid carcinoma. ER binding activity largely depends on chromatin remodeling and recruitment of transcription factors to estrogen response elements. A deeper understanding of these regulatory mechanisms may uncover therapeutic targets for ER-dependent endometrial cancers. We show that estrogen induces accessible chromatin and ER binding at a subset of enhancers, which form higher-order super enhancers that are vital for ER signaling. ER positively correlates with active enhancers in primary tumors, and tumors were effectively classified into molecular subtypes with chromatin accessibility dynamics and ER-dependent gene signature. ARID1A binds within ER-bound enhancers and regulates ER-dependent transcription. Knockdown of ARID1A or fulvestrant treatment profoundly affects the gene-expression program, and inhibits cell growth phenotype by affecting the chromatin environment. Importantly, we found dysregulated expression of circadian rhythms genes by estrogen in cancer cells and in primary tumors. Knockdown of ARID1A reduces the chromatin accessibility and ER binding at enhancers of the circadian gene ARNTL and BHLHE41, leading to a decreased expression of these genes. Altogether, we uncover a critical role for ARID1A in ER signaling and therapeutic target in ER-positive endometrial cancer.

ARNTL2 promotes pancreatic ductal adenocarcinoma progression through TGF/BETA pathway and is regulated by miR-26a-5p

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive malignancies and the therapeutic outcomes remain undesirable. Increasing evidence shows that aryl hydrocarbon receptor nuclear translocator like 2 (ARNTL2) plays crucial roles in tumorigenesis of multiple tumors. However, the expression status and functions of ARNTL2 in PDAC remain elusive. Here we showed that ARNTL2 expression was markedly upregulated in PDAC tissues and cell lines. elevated expression of ARNTL2 was positively related to unfavorable prognosis. Knockdown of ARNTL2 could suppress motility and invasive ability of PDAC cells in vitro, as well as tumor development in vivo. In addition, microRNA-26a-5p (miR-26a-5p) was identified as the crucial specific arbitrator for ARNTL2 expression and the expression of miR-26a-5p was inversely correlated with ARNTL2 expression in PDAC tissues. Functionally, elevated expression of miR-26a-5p was found to inhibit the proliferation, migration, and invasion of PDAC cells in vitro, while ARNTL2 increased expression could partially abolish the suppressive effect of miR-26a-5p. Mechanism study indicated that elevated expression of miR-26a-5p suppressed TGF/BETA signaling pathway by targeting ARNTL2 in PDAC cells. In conclusion, our data suggested that ARNTL2 acted as an oncogene to regulate PDAC growth. MiR-26a-5p/ARNTL2 axis may be a novel therapeutic candidate target in PDAC treatment.

Development and validation of an immune-related prognostic signature in lung adenocarcinoma

BACKGROUND

Lung adenocarcinomas (LUAD) is the most common histological subtype of lung cancers. Tumor immune microenvironment (TIME) is involved in tumorigeneses, progressions, and metastases. This study is aimed to develop a robust immune-related signature of LUAD.

METHODS

A total of 1774 LUAD cases sourced from public databases were included in this study. Immune scores were calculated through ESTIMATE algorithm and weighted gene co-expression network analysis (WGCNA) was applied to identify immune-related genes. Stability selections and Lasso COX regressions were implemented to construct prognostic signatures. Validations and comparisons with other immune-related signatures were conducted in independent Gene Expression Omnibus (GEO) cohorts. Abundant infiltrated immune cells and pathway enrichment analyses were carried out, respectively, through ImmuCellAI and gene set enrichment analysis (GSEA).

RESULTS

In Cancer Genome Atlas (TCGA) LUAD cohorts, immune scores of higher levels were significantly associated with better prognoses (P < .05). Yellow (n = 270) and Blue (n = 764) colored genes were selected as immune-related genes, and after univariate Cox regression analysis (P < .005), a total of 133 genes were screened out for subsequent model constructions. A four-gene signature (ARNTL2, ECT2, PPIA, and TUBA4A) named IPSLUAD was developed through stability selection and Lasso COX regression. It was suggested by multivariate and subgroup analyses that IPSLUAD was an independent prognostic factor. It was suggested by Kaplan-Meier survival analysis that eight out of nine patients in high-risk groups had significantly worse prognoses in validation data sets (P < .05). IPSLUAD outperformed other signatures in two independent cohorts.

CONCLUSIONS

A robust immune-related prognostic signature with great performances in multiple LUAD cohorts was developed in this study.

The genomic landscape of metastasis in treatment-naïve breast cancer models

Metastasis remains the principle cause of mortality for breast cancer and presents a critical challenge because secondary lesions are often refractory to conventional treatments. While specific genetic alterations are tightly linked to primary tumor development and progression, the role of genetic alteration in the metastatic process is not well-understood. The theory of tumor evolution postulated by Peter Nowell in 1976 has yet to be proven in the context of metastasis. Therefore, in order to investigate how somatic evolution contributes to breast cancer metastasis, we performed exome, whole genome, and RNA sequencing of matched metastatic and primary tumors from pre-clinical mouse models of breast cancer. Here we show that in a treatment-naïve setting, recurrent single nucleotide variants and copy number variation, but not gene fusion events, play key metastasis-driving roles in breast cancer. For instance, we identified recurrent mutations in Kras, a known driver of colorectal and lung tumorigenesis that has not been previously implicated in breast cancer metastasis. However, in a set of in vivo proof-of-concept experiments we show that the Kras G12D mutation is sufficient to significantly promote metastasis using three syngeneic allograft models. The work herein confirms the existence of metastasis-driving mutations and presents a novel framework to identify actionable metastasis-targeted therapies.

The majority of breast cancer-associated deaths are due to metastatic disease, the process where cancerous cells leave the primary tumor and spread to a new location in the body, because metastatic tumors often become insensitive to the same therapies that were successful in treating the primary tumor. To date, this complex process has been attributed to dynamic changes in tumor cell gene expression regulated by epigenetic factors. Interestingly, while genomic alterations are accepted drivers of neoplastic transformation, it is unknown if such events contribute to metastatic spread. One reason for this is the limited availability of matched and treatment-naïve primary tumor and metastatic tumor samples from patients for comparative genomic testing. Here we use two pre-clinical mouse models of metastatic breast cancer to test if genomic alterations can drive metastatic capacity. We identified metastasis-specific events of single nucleotide variation and gene amplification in well-known oncogenic genes, as well as lesser known factors. We also show that expression of these mutant factors can drive metastasis of weakly and non-metastatic mouse mammary cancer cell lines when implanted in mice. Crucially, by observing and reporting this untested etiology of metastatic disease, specific genomic events can now be included in efforts to develop targets for metastasis-specific therapies.

Development of a four-gene prognostic model for pancreatic cancer based on transcriptome dysregulation

We systematically developed a prognostic model for pancreatic cancer that was compatible across different transcriptomic platforms and patient cohorts. After performing quality control measures, we used seven microarray datasets and two RNA sequencing datasets to identify consistently dysregulated genes in pancreatic cancer patients. Weighted gene co-expression network analysis was performed to explore the associations between gene expression patterns and clinical features. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to construct a prognostic model. We tested the predictive power of the model by determining the area under the curve of the risk score for time-dependent survival. Most of the differentially expressed genes in pancreatic cancer were enriched in functions pertaining to the tumor immune microenvironment. The transcriptome profiles were found to be associated with overall survival, and four genes were identified as independent prognostic factors. A prognostic risk score was then proposed, which displayed moderate accuracy in the training and self-validation cohorts. Furthermore, patients in two independent microarray cohorts were successfully stratified into high- and low-risk prognostic groups. Thus, we constructed a reliable prognostic model for pancreatic cancer, which should be beneficial for clinical therapeutic decision-making.

A network analysis to identify mediators of germline-driven differences in breast cancer prognosis

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.

Breast Cancer in Young Women: Status Quo and Advanced Disease Management by a Predictive, Preventive, and Personalized Approach

Why does healthcare of breast cancer (BC) patients, especially in a young population, matter and why are innovative strategies by predictive, preventive, and personalized medicine (PPPM) strongly recommended to replace current reactive medical approach in BC management? Permanent increase in annual numbers of new BC cases with particularly quick growth of premenopausal BC patients, an absence of clearly described risk factors for those patients, as well as established screening tools and programs represent important reasons to focus on BC in young women. Moreover, "young" BC cases are frequently "asymptomatic", difficult to diagnose, and to treat effectively on time. The objective of this article is to update the knowledge on BC in young females, its unique molecular signature, newest concepts in diagnostics and therapy, and to highlight the concepts of predictive, preventive, and personalized medicine with a well-acknowledged potential to advance the overall disease management.

Identification of a Nine-Gene Signature and Establishment of a Prognostic Nomogram Predicting Overall Survival of Pancreatic Cancer

Background: Pancreatic cancer is highly lethal and aggressive with increasing trend of mortality in both genders. An effective prediction model is needed to assess prognosis of patients for optimization of treatment. Materials and Methods: Seven datasets of mRNA expression and clinical data were obtained from gene expression omnibus (GEO) database. Level 3 mRNA expression and clinicopathological data were obtained from The Cancer Genome Atlas pancreatic ductal adenocarcinoma (TCGA-PAAD) dataset. Differentially expressed genes (DEGs) between pancreatic tumor and normal tissue were identified by integrated analysis of multiple GEO datasets. Univariate and Lasso Cox regression analyses were applied to identify overall survival-related DEGs and establish a prognostic gene signature whose performance was evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC), Harrell's concordance index (C-index) and calibration curve. GSE62452 and GSE57495 were used for external validation. Gene set enrichment analysis (GSEA) and tumor immunity analysis were applied to elucidate the molecular mechanisms and immune relevance. Multivariate Cox regression analysis was used to identify independent prognostic factors in pancreatic cancer. Finally, a prognostic nomogram was established based on the TCGA PAAD dataset. Results: A nine-gene signature comprising MET, KLK10, COL17A1, CEP55, ANKRD22, ITGB6, ARNTL2, MCOLN3, and SLC25A45 was established to predict overall survival of pancreatic cancer. The ROC curve and C-index indicated good performance of the nine-gene signature at predicting overall survival in the TCGA dataset and external validation datasets relative to classic AJCC staging. The nine-gene signature could classify patients into high- and low-risk groups with distinct overall survival and differentiate tumor from normal tissue. Univariate Cox regression revealed that the nine-gene signature was an independent prognostic factor in pancreatic cancer. The nomogram incorporating the gene signature and clinical prognostic factors was superior to AJCC staging in predicting overall survival. The high-risk group was enriched with multiple oncological signatures and aggressiveness-related pathways and associated with significantly lower levels of CD4⁺ T cell infiltration. Conclusion: Our study identified a nine-gene signature and established a prognostic nomogram that reliably predict overall survival in pancreatic cancer. The findings may be beneficial to therapeutic customization and medical decision-making.

Identification and meta-analysis of copy number variation-driven circadian clock genes for colorectal cancer

Both copy number variation (CNV) and circadian clock genes play a critical role in the etiology and pathogenesis of colorectal cancer (CRC); however, a comprehensive analysis of CNV-driven circadian clock genes is urgently required. The present study aimed to investigate the systematic associations between somatic cell CNVs and circadian clock gene expression in patients with CRC. Using somatic CNV, legacy clinical information and gene expression data from The Cancer Genome Atlas, 295 genes that were significantly differentially expressed and with significantly different CNV were obtained, and the expression of the genes, among which 15 were circadian clock genes, was significantly associated with CNV. Further analysis revealed that aryl hydrocarbon receptor nuclear translocator-like 2 (ARNTL2) expression and CNV in these circadian clock genes were significantly associated with survival time in patients with CRC, and the expression of ARNTL2 was also significantly associated with the pathological stage of CRC. Gene set enrichment analysis found that ARNTL2 is enriched for gene sets associated with CRC pathogenesis such as the p53 signaling pathway. These results suggest that ARNTL2 may be a promising prognostic biomarker for patients with CRC, and that circadian clock genes play an important role in CRC through CNV.

Deletion of clock gene Bmal1 impaired the chondrocyte function due to disruption of the HIF1α-VEGF signaling pathway

Several studies have demonstrated the core circadian rhythm gene Bmal1 could regulate the clock control genes (CCGs) expression and maintain the integrity in cartilage tissue. In addition, its abnormal expression is connected with the occurrence and development of several diseases including osteoarthritis (OA). However, the relationship between Bmal1 and cartilage development still needs to be fully elucidated. Here, we bred tamoxifen-induced cartilage-specific knockout mice to learn the effects of Bmal1 on the cartilage development and its underlying mechanisms at specific time points. We observed that Bmal1 ablated mice showed growth retardation during puberty, and the length of whole growth plate and the proliferation zone were both shorter than those in the control group. Deletion of Bmal1 significantly inhibited the chondrocytes proliferation and activated cells apoptosis in the growth plate. Meanwhile, knockout of Bmal1 attenuated the expression of VEGF and HIF1α and enhanced the level of MMP13 and Runx2 in the growth plate chondrocytes. Consistent with these findings in vivo, ablation of Bmal1 could also lead to decrease chondrocytes proliferation, the expression of HIF1α and VEGF and elevate apoptosis in cultured chondrocytes. These findings suggest that Bmal1 plays a pivotal role in cartilage development by regulating the HIF1α-VEGF signaling pathway.

OMICfpp: a fuzzy approach for paired RNA-Seq counts

Background

RNA sequencing is a widely used technology for differential expression analysis. However, the RNA-Seq do not provide accurate absolute measurements and the results can be different for each pipeline used. The major problem in statistical analysis of RNA-Seq and in the omics data in general, is the small sample size with respect to the large number of variables. In addition, experimental design must be taken into account and few tools consider it.

Results

We propose OMICfpp, a method for the statistical analysis of RNA-Seq paired design data. First, we obtain a p-value for each case-control pair using a binomial test. These p-values are aggregated using an ordered weighted average (OWA) with a given orness previously chosen. The aggregated p-value from the original data is compared with the aggregated p-value obtained using the same method applied to random pairs. These new pairs are generated using between-pairs and complete randomization distributions. This randomization p-value is used as a raw p-value to test the differential expression of each gene. The OMICfpp method is evaluated using public data sets of 68 sample pairs from patients with colorectal cancer. We validate our results through bibliographic search of the reported genes and using simulated data set. Furthermore, we compared our results with those obtained by the methods edgeR and DESeq2 for paired samples. Finally, we propose new target genes to validate these as gene expression signatures in colorectal cancer. OMICfpp is available at http://www.uv.es/ayala/software/OMICfpp_0.2.tar.gz.

Conclusions

Our study shows that OMICfpp is an accurate method for differential expression analysis in RNA-Seq data with paired design. In addition, we propose the use of randomized p-values pattern graphic as a powerful and robust method to select the target genes for experimental validation.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5496-5) contains supplementary material, which is available to authorized users.

The second genome: Effects of the mitochondrial genome on cancer progression

The role of genetics in cancer has been recognized for centuries, but most studies elucidating genetic contributions to cancer have understandably focused on the nuclear genome. Mitochondrial contributions to cancer pathogenesis have been documented for decades, but how mitochondrial DNA (mtDNA) influences cancer progression and metastasis remains poorly understood. This lack of understanding stems from difficulty isolating the nuclear and mitochondrial genomes as experimental variables, which is critical for investigating direct mtDNA contributions to disease given extensive crosstalk exists between both genomes. Several in vitro and in vivo models have isolated mtDNA as an independent variable from the nuclear genome. This review compares and contrasts different models, their advantages and disadvantages for studying mtDNA contributions to cancer, focusing on the mitochondrial-nuclear exchange (MNX) mouse model and findings regarding tumor progression, metastasis, and other complex cancer-related phenotypes.

A Polymorphic Variant in p19Arf Confers Resistance to Chemically Induced Skin Tumors by Activating the p53 Pathway

Identification of the specific genetic variants responsible for the increased susceptibility to familial or sporadic cancers is important. Using a forward genetics approach to map such loci in a mouse skin cancer model, we previously identified a strong genetic locus, Stmm3, conferring resistance to chemically induced skin papillomas on chromosome 4. Here, we report the cyclin-dependent kinase inhibitor gene Cdkn2a/p19^Arf as a major responsible gene for the Stmm3 locus. We provide evidence that the function of Stmm3 is dependent on p53 and that p19^ArfMSM confers stronger resistance to papillomas than p16^Ink4aMSMin vivo. In addition, we found that genetic polymorphism in p19^Arf between a resistant strain, MSM/Ms (Val), and a susceptible strain, FVB/N (Leu), alters the susceptibility to papilloma development, malignant conversion, and the epithelial-mesenchymal transition. Moreover, we demonstrated that the p19^ArfMSM allele more efficiently activates the p53 pathway than the p19^ArfFVB allele in vitro and in vivo. Furthermore, we found polymorphisms in CDKN2A in the vicinity of a polymorphism in mouse Cdkn2a associated with the risk of human cancers in the Japanese population. Genetic polymorphisms in Cdkn2a and CDKN2A may affect the cancer risk in both mice and humans.

YAP1 enhances NF-κB-dependent and independent effects on clock-mediated unfolded protein responses and autophagy in sarcoma

Terminal differentiation opposes proliferation in the vast majority of tissue types. As a result, loss of lineage differentiation is a hallmark of aggressive cancers, including soft tissue sarcomas (STS). Consistent with these observations, undifferentiated pleomorphic sarcoma (UPS), an STS subtype devoid of lineage markers, is among the most lethal sarcomas in adults. Though tissue-specific features are lost in these mesenchymal tumors they are most commonly diagnosed in skeletal muscle, and are thought to develop from transformed muscle progenitor cells. We have found that a combination of HDAC (Vorinostat) and BET bromodomain (JQ1) inhibition partially restores differentiation to skeletal muscle UPS cells and tissues, enforcing a myoblast-like identity. Importantly, differentiation is partially contingent upon downregulation of the Hippo pathway transcriptional effector Yes-associated protein 1 (YAP1) and nuclear factor (NF)-κB. Previously, we observed that Vorinostat/JQ1 inactivates YAP1 and restores oscillation of NF-κB in differentiating myoblasts. These effects correlate with reduced tumorigenesis, and enhanced differentiation. However, the mechanisms by which the Hippo/NF-κB axis impact differentiation remained unknown. Here, we report that YAP1 and NF-κB activity suppress circadian clock function, inhibiting differentiation and promoting proliferation. In most tissues, clock activation is antagonized by the unfolded protein response (UPR). However, skeletal muscle differentiation requires both Clock and UPR activity, suggesting the molecular link between them is unique in muscle. In skeletal muscle-derived UPS, we observed that YAP1 suppresses PERK and ATF6-mediated UPR target expression as well as clock genes. These pathways govern metabolic processes, including autophagy, and their disruption shifts metabolism toward cancer cell-associated glycolysis and hyper-proliferation. Treatment with Vorinostat/JQ1 inhibited glycolysis/MTOR signaling, activated the clock, and upregulated the UPR and autophagy via inhibition of YAP1/NF-κB. These findings support the use of epigenetic modulators to treat human UPS. In addition, we identify specific autophagy, UPR, and muscle differentiation-associated genes as potential biomarkers of treatment efficacy and differentiation.

Genetic insights into the morass of metastatic heterogeneity

Tumour heterogeneity poses a substantial problem for the clinical management of cancer. Somatic evolution of the cancer genome results in genetically distinct subclones in the primary tumour with different biological properties and therapeutic sensitivities. The problem of heterogeneity is compounded in metastatic disease owing to the complexity of the metastatic process and the multiple biological hurdles that the tumour cell must overcome to establish a clinically overt metastatic lesion. New advances in sequencing technology and clinical sample acquisition are providing insights into the phylogenetic relationship of metastases and primary tumours at the level of somatic tumour genetics while also illuminating fundamental mechanisms of the metastatic process. In addition to somatically acquired genetic heterogeneity in the tumour cells, inherited population-based genetic heterogeneity can profoundly modify metastatic biology and further complicate the development of effective, broadly applicable antimetastatic therapies. Here, we examine how genetic heterogeneity impacts metastatic disease and the implications of current knowledge for future research endeavours and therapeutic interventions.

The Genomic Landscape and Pharmacogenomic Interactions of Clock Genes in Cancer Chronotherapy

Cancer chronotherapy, treatment at specific times during circadian rhythms, endeavors to optimize anti-tumor effects and to lower toxicity. However, comprehensive characterization of clock genes and their clinical relevance in cancer is lacking. We systematically characterized the alterations of clock genes across 32 cancer types by analyzing data from The Cancer Genome Atlas, Cancer Therapeutics Response Portal, and The Genomics of Drug Sensitivity in Cancer databases. Expression alterations of clock genes are associated with key oncogenic pathways, patient survival, tumor stage, and subtype in multiple cancer types. Correlations between expression of clock genes and of other genes in the genome were altered in cancerous versus normal tissues. We identified interactions between clock genes and clinically actionable genes by analyzing co-expression, protein-protein interaction, and chromatin immunoprecipitation sequencing data and also found that clock gene expression is correlated to anti-cancer drug sensitivity in cancer cell lines. Our study provides a comprehensive analysis of the circadian clock across different cancer types and highlights potential clinical utility of cancer chronotherapy.

Direct inhibition of ACTN4 by ellagic acid limits breast cancer metastasis via regulation of β-catenin stabilization in cancer stem cells

Background

Pharmacology-based target identification has become a novel strategy leading to the discovery of novel pathological biomarkers. Ellagic acid (EA), a dietary polyphenol compound, exhibits potent anticancer activities; however, the underlying mechanisms remain unclear. The current study sought to determine the role and regulation of ACTN4 expression in human breast cancer metastasis and EA-based therapy.

Methods

The anti-metastasis ability of EA was validated by MMTV-PyMT mice and in vitro cell models. Drug affinity responsive target stability (DARTS) was utilized to identify ACTN4 as the direct target of EA. The metastatic regulated function of ACTN4 were assessed by cancer stem cells (CSCs)-related assays, including mammosphere formation, tumorigenic ability, reattachment differentiation, and signaling pathway analysis. The mechanisms of ACTN4 on β-catenin stabilization were investigated by western blotting, co-immunoprecipitation and ubiquitination assays. The clinical significance of ACTN4 was based on human tissue microarray (TMA) analysis and The Cancer Genome Atlas (TCGA) database exploration.

Results

EA inhibited breast cancer growth and metastasis via directly targeting ACTN4 in vitro and in vivo, and was accompanied by a limited CSC population. ACTN4 knockdown resulted in the blockage of malignant cell proliferation, colony formation, and ameliorated metastasis potency. ACTN4-positive CSCs exhibited a higher ESA⁺ proportion, increased mammosphere-formation ability, and enhanced in vivo tumorigenesis ability. Mechanism exploration revealed that interruption of ACTN4/β-catenin interaction will result in the activation of β-catenin proteasome degradation. Increased ACTN4 expression was directly associated with the advanced cancer stage, an increased incidence of metastasis, and poor overall survival period.

Conclusions

Taken together, our results suggest that ACTN4 plays an important role in breast CSCs-related metastasis and is a novel therapeutic target of EA treatment.

Electronic supplementary material

The online version of this article (10.1186/s13046-017-0635-9) contains supplementary material, which is available to authorized users.

CYCLOPS reveals human transcriptional rhythms in health and disease

Circadian rhythms modulate many aspects of physiology. Knowledge of the molecular basis of these rhythms has exploded in the last 20 years. However, most of these data are from model organisms, and translation to clinical practice has been limited. Here, we present an approach to identify molecular rhythms in humans from thousands of unordered expression measurements. Our algorithm, cyclic ordering by periodic structure (CYCLOPS), uses evolutionary conservation and machine learning to identify elliptical structure in high-dimensional data. From this structure, CYCLOPS estimates the phase of each sample. We validated CYCLOPS using temporally ordered mouse and human data and demonstrated its consistency on human data from two independent research sites. We used this approach to identify rhythmic transcripts in human liver and lung, including hundreds of drug targets and disease genes. Importantly, for many genes, the circadian variation in expression exceeded variation from genetic and other environmental factors. We also analyzed hepatocellular carcinoma samples and show these solid tumors maintain circadian function but with aberrant output. Finally, to show how this method can catalyze medical translation, we show that dosage time can temporally segregate efficacy from dose-limiting toxicity of streptozocin, a chemotherapeutic drug. In sum, these data show the power of CYCLOPS and temporal reconstruction in bridging basic circadian research and clinical medicine.

Emerging functional roles of nuclear receptors in breast cancer

Nuclear receptors (NRs) have been targets of intensive drug development for decades due to their roles as key regulators of multiple developmental, physiological and disease processes. In breast cancer, expression of the estrogen and progesterone receptor remains clinically important in predicting prognosis and determining therapeutic strategies. More recently, there is growing evidence supporting the involvement of multiple nuclear receptors other than the estrogen and progesterone receptors, in the regulation of various processes important to the initiation and progression of breast cancer. We review new insights into the mechanisms of action of NRs made possible by recent advances in genomic technologies and focus on the emerging functional roles of NRs in breast cancer biology, including their involvement in circadian regulation, metabolic reprogramming and breast cancer migration and metastasis.

Feeling cold and other underestimated symptoms in breast cancer: anecdotes or individual profiles for advanced patient stratification?

Breast cancer (BC) epidemic is recognised as being characteristic for the early twenty-first century. BC is a multifactorial disease, and a spectrum of modifiable (preventable) factors significantly increasing risks has been described. This article highlights a series of underestimated symptoms for consequent BC risk assessment and patient stratification. Phenomena of the deficient thermoregulation, altered sensitivity to different stimuli (pain, thirst, smell, light, stress provocation), dehydration, altered circadian and sleep patterns, tendency towards headache, migraine attacks and dizziness, as well as local and systemic hypoxic effects are discussed for BC patients providing functional links and proposing new approaches in the overall BC management.