scholarly journals Immunity Depletion, Telomere Imbalance, and Cancer-associated Metabolism Pathway Aberrations in Intestinal Mucosa upon Caloric Restriction

2021 ◽  
Author(s):  
Evan Maestri ◽  
Kalina Duszka ◽  
Vladimir A Kuznetsov

AbstractSystematic analysis of calorie restriction (CR) mechanisms and pathways in cancer biology has not been carried out, leaving therapeutic benefits unclear. Using a systems biology approach and metadata analysis, we studied gene expression changes in the response of normal mouse duodenum mucosa (DM) to short-term (2-weeks) 25% CR as a biological model. We found a high similarity of gene expression profiles in human and mouse DM tissues. Surprisingly, 26% of the 467 CR responding differential expressed genes (DEGs) in mice consist of cancer-associated genes—most never studied in CR contexts. The DEGs were enriched with over-expressed cell cycle, oncogenes, and metabolic reprogramming pathways (MRP) that determine tissue-specific tumorigenesis, cancer, and stem cell activation; tumor suppressors and apoptosis genes were under-expressed. DEG enrichments suggest a misbalance in telomere maintenance and activation of metabolic pathways playing dual (anti-cancer and pro-oncogenic) roles. Immune system genes (ISGs) consist of 37% of the total DEGs; the majority of ISGs are suppressed, including cell-autonomous immunity and tumor immune evasion controls. Thus, CR induces MRP suppressing multiple immune mechanics and activating oncogenic pathways, potentially driving pre-malignant and cancer states. These findings change the paradigm regarding the anti-cancer role of CR and may initiate specific treatment target development.

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3180
Author(s):  
Evan Maestri ◽  
Kalina Duszka ◽  
Vladimir A Kuznetsov

Systems cancer biology analysis of calorie restriction (CR) mechanisms and pathways has not been carried out, leaving therapeutic benefits unclear. Using metadata analysis, we studied gene expression changes in normal mouse duodenum mucosa (DM) response to short-term (2-weeks) 25% CR as a biological model. Our results indicate cancer-associated genes consist of 26% of 467 CR responding differential expressed genes (DEGs). The DEGs were enriched with over-expressed cell cycle, oncogenes, and metabolic reprogramming pathways that determine tissue-specific tumorigenesis, cancer, and stem cell activation; tumor suppressors and apoptosis genes were under-expressed. DEG enrichments suggest telomeric maintenance misbalance and metabolic pathway activation playing dual (anti-cancer and pro-oncogenic) roles. The aberrant DEG profile of DM epithelial cells is found within CR-induced overexpression of Paneth cells and is coordinated significantly across GI tract tissues mucosa. Immune system genes (ISGs) consist of 37% of the total DEGs; the majority of ISGs are suppressed, including cell-autonomous immunity and tumor-immune surveillance. CR induces metabolic reprogramming, suppressing immune mechanics and activating oncogenic pathways. We introduce and argue for our network pro-oncogenic model of the mucosa multicellular tissue response to CR leading to aberrant transcription and pre-malignant states. These findings change the paradigm regarding CR’s anti-cancer role, initiating specific treatment target development. This will aid future work to define critical oncogenic pathways preceding intestinal lesion development and biomarkers for earlier adenoma and colorectal cancer detection.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 30-31
Author(s):  
Hanyin Wang ◽  
Shulan Tian ◽  
Qing Zhao ◽  
Wendy Blumenschein ◽  
Jennifer H. Yearley ◽  
...  

Introduction: Richter's syndrome (RS) represents transformation of chronic lymphocytic leukemia (CLL) into a highly aggressive lymphoma with dismal prognosis. Transcriptomic alterations have been described in CLL but most studies focused on peripheral blood samples with minimal data on RS-involved tissue. Moreover, transcriptomic features of RS have not been well defined in the era of CLL novel therapies. In this study we investigated transcriptomic profiles of CLL/RS-involved nodal tissue using samples from a clinical trial cohort of refractory CLL and RS patients treated with Pembrolizumab (NCT02332980). Methods: Nodal samples from 9 RS and 4 CLL patients in MC1485 trial cohort were reviewed and classified as previously published (Ding et al, Blood 2017). All samples were collected prior to Pembrolizumab treatment. Targeted gene expression profiling of 789 immune-related genes were performed on FFPE nodal samples using Nanostring nCounter® Analysis System (NanoString Technologies, Seattle, WA). Differential expression analysis was performed using NanoStringDiff. Genes with 2 fold-change in expression with a false-discovery rate less than 5% were considered differentially expressed. Results: The details for the therapy history of this cohort were illustrated in Figure 1a. All patients exposed to prior ibrutinib before the tissue biopsy had developed clinical progression while receiving ibrutinib. Unsupervised hierarchical clustering using the 300 most variable genes in expression revealed two clusters: C1 and C2 (Figure 1b). C1 included 4 RS and 3 CLL treated with prior chemotherapy without prior ibrutinib, and 1 RS treated with prior ibrutinib. C2 included 1 CLL and 3 RS received prior ibrutinib, and 1 RS treated with chemotherapy. The segregation of gene expression profiles in samples was largely driven by recent exposure to ibrutinib. In C1 cluster (majority had no prior ibrutinb), RS and CLL samples were clearly separated into two subgroups (Figure 1b). In C2 cluster, CLL 8 treated with ibrutinib showed more similarity in gene expression to RS, than to other CLL samples treated with chemotherapy. In comparison of C2 to C1, we identified 71 differentially expressed genes, of which 34 genes were downregulated and 37 were upregulated in C2. Among the upregulated genes in C2 (majority had prior ibrutinib) are known immune modulating genes including LILRA6, FCGR3A, IL-10, CD163, CD14, IL-2RB (figure 1c). Downregulated genes in C2 are involved in B cell activation including CD40LG, CD22, CD79A, MS4A1 (CD20), and LTB, reflecting the expected biological effect of ibrutinib in reducing B cell activation. Among the 9 RS samples, we compared gene profiles between the two groups of RS with or without prior ibrutinib therapy. 38 downregulated genes and 10 upregulated genes were found in the 4 RS treated with ibrutinib in comparison with 5 RS treated with chemotherapy. The top upregulated genes in the ibrutinib-exposed group included PTHLH, S100A8, IGSF3, TERT, and PRKCB, while the downregulated genes in these samples included MS4A1, LTB and CD38 (figure 1d). In order to delineate the differences of RS vs CLL, we compared gene expression profiles between 5 RS samples and 3 CLL samples that were treated with only chemotherapy. RS samples showed significant upregulation of 129 genes and downregulation of 7 genes. Among the most significantly upregulated genes are multiple genes involved in monocyte and myeloid lineage regulation including TNFSF13, S100A9, FCN1, LGALS2, CD14, FCGR2A, SERPINA1, and LILRB3. Conclusion: Our study indicates that ibrutinib-resistant, RS-involved tissues are characterized by downregulation of genes in B cell activation, but with PRKCB and TERT upregulation. Furthermore, RS-involved nodal tissues display the increased expression of genes involved in myeloid/monocytic regulation in comparison with CLL-involved nodal tissues. These findings implicate that differential therapies for RS and CLL patients need to be adopted based on their prior therapy and gene expression signatures. Studies using large sample size will be needed to verify this hypothesis. Figure Disclosures Zhao: Merck: Current Employment. Blumenschein:Merck: Current Employment. Yearley:Merck: Current Employment. Wang:Novartis: Research Funding; Incyte: Research Funding; Innocare: Research Funding. Parikh:Verastem Oncology: Honoraria; GlaxoSmithKline: Honoraria; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; AbbVie: Honoraria, Research Funding; Merck: Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Kenderian:Sunesis: Research Funding; MorphoSys: Research Funding; Humanigen: Consultancy, Patents & Royalties, Research Funding; Gilead: Research Funding; BMS: Research Funding; Tolero: Research Funding; Lentigen: Research Funding; Juno: Research Funding; Mettaforge: Patents & Royalties; Torque: Consultancy; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding. Kay:Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Research Funding; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; MEI Pharma: Research Funding; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Ding:DTRM: Research Funding; Astra Zeneca: Research Funding; Abbvie: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees.


Genes ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 206 ◽  
Author(s):  
Celia Salazar ◽  
Osvaldo Yañez ◽  
Alvaro A. Elorza ◽  
Natalie Cortes ◽  
Olimpo García-Beltrán ◽  
...  

The expression of HIGD2A is dependent on oxygen levels, glucose concentration, and cell cycle progression. This gene encodes for protein HIG2A, found in mitochondria and the nucleus, promoting cell survival in hypoxic conditions. The genomic location of HIGD2A is in chromosome 5q35.2, where several chromosomal abnormalities are related to numerous cancers. The analysis of high definition expression profiles of HIGD2A suggests a role for HIG2A in cancer biology. Accordingly, the research objective was to perform a molecular biosystem analysis of HIGD2A aiming to discover HIG2A implications in cancer biology. For this purpose, public databases such as SWISS-MODEL protein structure homology-modelling server, Catalogue of Somatic Mutations in Cancer (COSMIC), Gene Expression Omnibus (GEO), MethHC: a database of DNA methylation and gene expression in human cancer, and microRNA-target interactions database (miRTarBase) were accessed. We also evaluated, by using Real-Time Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR), the expression of Higd2a gene in healthy bone marrow-liver-spleen tissues of mice after quercetin (50 mg/kg) treatment. Thus, among the structural features of HIG2A protein that may participate in HIG2A translocation to the nucleus are an importin α-dependent nuclear localization signal (NLS), a motif of DNA binding residues and a probable SUMOylating residue. HIGD2A gene is not implicated in cancer via mutation. In addition, DNA methylation and mRNA expression of HIGD2A gene present significant alterations in several cancers; HIGD2A gene showed significant higher expression in Diffuse Large B-cell Lymphoma (DLBCL). Hypoxic tissues characterize the “bone marrow-liver-spleen” DLBCL type. The relative quantification, by using qRT-PCR, showed that Higd2a expression is higher in bone marrow than in the liver or spleen. In addition, it was observed that quercetin modulated the expression of Higd2a gene in mice. As an assembly factor of mitochondrial respirasomes, HIG2A might be unexpectedly involved in the change of cellular energetics happening in cancer. As a result, it is worth continuing to explore the role of HIGD2A in cancer biology.


2007 ◽  
Vol 132 (5) ◽  
pp. 1937-1946 ◽  
Author(s):  
Samuele De Minicis ◽  
Ekihiro Seki ◽  
Hiroshi Uchinami ◽  
Johannes Kluwe ◽  
Yonghui Zhang ◽  
...  

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
M. Dolcino ◽  
E. Cozzani ◽  
S. Riva ◽  
A. Parodi ◽  
E. Tinazzi ◽  
...  

Dermatitis herpetiformis (DH) is an autoimmune blistering skin disease associated with gluten-sensitive enteropathy (CD). In order to investigate the pathogenesis of skin lesions at molecular level, we analysed the gene expression profiles in skin biopsies from 6 CD patients with DH and 6 healthy controls using Affymetrix HG-U133A 2.0 arrays. 486 genes were differentially expressed in DH skin compared to normal skin: 225 were upregulated and 261 were downregulated. Consistently with the autoimmune origin of DH, functional classification of the differentially expressed genes (DEGs) indicates a B- and T-cell immune response (LAG3, TRAF5, DPP4, and NT5E). In addition, gene modulation provides evidence for a local inflammatory response (IL8, PTGFR, FSTL1, IFI16, BDKRD2, and NAMPT) with concomitant leukocyte recruitment (CCL5, ENPP2), endothelial cell activation, and neutrophil extravasation (SELL, SELE). DEGs also indicate overproduction of matrix proteases (MMP9, ADAM9, and ADAM19) and proteolytic enzymes (CTSG, ELA2, CPA3, TPSB2, and CMA1) that may contribute to epidermal splitting and blister formation. Finally, we observed modulation of genes involved in cell growth inhibition (CGREF1, PA2G4, and PPP2R1B), increased apoptosis (FAS, TNFSF10, and BASP1), and reduced adhesion at the dermal epidermal junction (PLEC1, ITGB4, and LAMA5). In conclusion, our results identify genes that are involved in the pathogenesis of DH skin lesions.


2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Zheng-yuan Wu ◽  
Gang Du ◽  
Yi-cai Lin

Abstract Background Osteoarthritis (OA) is the most common chronic degenerative joint disorder globally that is characterized by synovitis, cartilage degeneration, joint space stenosis, and sub-cartilage bone hyperplasia. However, the pathophysiologic mechanisms of OA have not been thoroughly investigated. Methods In this study, we conducted various bioinformatics analyses to identify hub biomarkers and immune infiltration in OA. The gene expression profiles of synovial tissues from 29 healthy controls and 36 OA samples were obtained from the gene expression omnibus database to identify differentially expressed genes (DEGs). The CIBERSORT algorithm was used to explore the association between immune infiltration and arthritis. Results Eighteen hub DEGs were identified as critical biomarkers for OA. Through gene ontology and pathway enrichment analyses, it was found that these DEGs were primarily involved in PI3K-Akt signaling pathway and Rap1 signaling pathway. Furthermore, immune infiltration analysis revealed differences in immune infiltration between patients with OA and healthy controls. The hub gene ZNF160 was closely related to immune cells, especially mast cell activation in OA. Conclusion Overall, this study presented a novel method to identify hub DEGs and their correlation with immune infiltration, which may provide novel insights into the diagnosis and treatment of patients with OA.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 2-2
Author(s):  
Arpan A. Sinha ◽  
Pilar I. Andrade ◽  
Courtney Sansam ◽  
Megan Malone-Perez ◽  
Christopher Sansam ◽  
...  

MYCis a key oncogene overexpressed by many cancers, however, its oncogenic mechanisms are poorly understood. MYC is also central to acute lymphoblastic leukemia (ALL), the most common and second most lethal pediatric malignancy. Much of MYC's oncogenicity has been attributed to its transcription factor function, but data suggest MYC also deregulates replication in transcription-independent fashion. As a known master regulator of cancer transcriptomes and epigenomes, we hypothesize that MYC dramatically alters both gene expression and replication timing (non-random spatiotemporal process where some part of the genome replicates early, and other late) in both types of ALL - B-ALL and T-ALL. Conceivably, MYC exerts oncogenic effects upon the ALL transcription and replication programs, with some changes shared by B- and T-ALL, and others unique to only one. We aim to address two novel questions not been investigated before. First, in ALL, do the same genetic loci show aberrant RNA transcriptionandDNA replication? Second, how similar are the affected loci in two closely-related, yet distinct, ALL types driven by the same oncogene? The basis of our project is a unique double-transgenicrag2:hMYC,lck:GFPzebrafish pre-clinical model we established, which is the only animal model proven to develop both B-ALL and T-ALL. We previously showed that gene expression profiles (GEP) differentiating zebrafish B- and T-ALL also distinguish human B- and T-ALL, making this an ideal model system to study human ALL. In this model, B-ALL and T-ALL are induced by human MYC(hMYC) regulated by aD.rerio(zebrafish)rag2promoter.Since B and T lymphoblasts both expressrag2, both lineages over-express MYC, causing highly-penetrant B- and T-ALL. Differential activity of aD. rerio lckpromoter causes B cells to fluoresce dimly and T cells to fluoresce brightly, allowing us to identify and purify B-ALL and T-ALL by fluorescent microscopy and fluorescence-based flow cytometry, respectively. This unique model enables comparing B- and T-ALL in one genetic background. We have purified >20 zebrafish ALL (both T-ALL and B-ALL) and isolated their RNA and DNA. We are now analyzing RNA-seq gene expression profiles (GEP) and replication timing (RT) profiles via next generation sequencing (NGS). We will compare both ALL types to identify mRNA signatures that are unique to, or shared by, both types. We seek loci that shift DNA replication from early-to-late, or late-to-early, to define the regions that replicate at the same time in both ALL types, versus loci that vary by ALL type. We will also interrogate these data to determine whether GEP and RT profiles correlate with each other, and with known MYC target genes. In conclusion, GEP and RT have never been analyzed in the same cancer sample, or in related cancers driven by the same oncogene. Exploiting our expertise with thehMYCzebrafish model, we are delineating how MYC alters transcription and replication, to ascertain if these affect the same loci and define which loci are unique to one ALL type or shared by both. MYC hyper-activity is seen ~70% of human cancers - making MYC a crucial oncogene in human cancer biology, so our findings are likely to inform not only mechanisms operative in ALL, but also other MYC-driven cancers. Disclosures No relevant conflicts of interest to declare.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shojiro Kitajima ◽  
Wendi Sun ◽  
Kian Leong Lee ◽  
Jolene Caifeng Ho ◽  
Seiichi Oyadomari ◽  
...  

AbstractUTX/KDM6A encodes a major histone H3 lysine 27 (H3K27) demethylase, and is frequently mutated in various types of human cancers. Although UTX appears to play a crucial role in oncogenesis, the mechanisms involved are still largely unknown. Here we show that a specific pharmacological inhibitor of H3K27 demethylases, GSK-J4, induces the expression of transcription activating factor 4 (ATF4) protein as well as the ATF4 target genes (e.g. PCK2, CHOP, REDD1, CHAC1 and TRIB3). ATF4 induction by GSK-J4 was due to neither transcriptional nor post-translational regulation. In support of this view, the ATF4 induction was almost exclusively dependent on the heme-regulated eIF2α kinase (HRI) in mouse embryonic fibroblasts (MEFs). Gene expression profiles with UTX disruption by CRISPR-Cas9 editing and the following stable re-expression of UTX showed that UTX specifically suppresses the expression of the ATF4 target genes, suggesting that UTX inhibition is at least partially responsible for the ATF4 induction. Apoptosis induction by GSK-J4 was partially and cell-type specifically correlated with the activation of ATF4-CHOP. These findings highlight that the anti-cancer drug candidate GSK-J4 strongly induces ATF4 and its target genes via HRI activation and raise a possibility that UTX might modulate cancer formation by regulating the HRI-ATF4 axis.


2019 ◽  
Author(s):  
Joske Ubels ◽  
Pieter Sonneveld ◽  
Martin H. van Vliet ◽  
Jeroen de Ridder

AbstractMany cancer drugs only benefit a subset of the patients that receive them, but are often associated with serious side effects. Predictive classification methods that can identify which patients will benefit from a specific treatment are therefore of great clinical utility. We here introduce a novel machine learning method to identify predictive gene expression signatures, based on the idea that patients who received different treatments but exhibit similar expression profiles can be used to model response to the alternative treatment. We use this method to predict proteasome inhibitor benefit in Multiple Myeloma (MM). In a dataset of 910 MM patients we identify a 14-gene expression signature that can successfully predict benefit to the proteasome inhibitor bortezomib, with a hazard ratio of 0.47 (p = 0.04) in class ‘benefit’, while in class ‘no benefit’ the hazard ratio is 0.91 (p = 0.68). Importantly, we observe a similar classification performance (HR class benefit = 0.46, p = 0.04) in an independent patient cohort which was moreover measured on a different platform, demonstrating the robustness of the signature. Moreover, we find that the genes in the discovered signature are essential, as no equivalent signature can be found when they are excluded from the analysis. Multiple genes in the signature are linked to working mechanisms of proteasome inhibitors or MM disease progression. In conclusion, our method allows for identification of gene expression signatures that can aid in treatment decisions for MM patients and provide insight into the biological mechanism behind treatment benefit.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Andrea R. Daamen ◽  
Prathyusha Bachali ◽  
Katherine A. Owen ◽  
Kathryn M. Kingsmore ◽  
Erika L. Hubbard ◽  
...  

AbstractSARS-CoV2 is a previously uncharacterized coronavirus and causative agent of the COVID-19 pandemic. The host response to SARS-CoV2 has not yet been fully delineated, hampering a precise approach to therapy. To address this, we carried out a comprehensive analysis of gene expression data from the blood, lung, and airway of COVID-19 patients. Our results indicate that COVID-19 pathogenesis is driven by populations of myeloid-lineage cells with highly inflammatory but distinct transcriptional signatures in each compartment. The relative absence of cytotoxic cells in the lung suggests a model in which delayed clearance of the virus may permit exaggerated myeloid cell activation that contributes to disease pathogenesis by the production of inflammatory mediators. The gene expression profiles also identify potential therapeutic targets that could be modified with available drugs. The data suggest that transcriptomic profiling can provide an understanding of the pathogenesis of COVID-19 in individual patients.


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