Genome-wide expression analysis suggests a crucial role of dysregulation of matrix metalloproteinases pathway in undifferentiated thyroid carcinoma

Methylation-related genes involved in renal carcinoma progression

Renal carcinomas are a group of malignant tumors often originating in the cells lining the small tubes in the kidney responsible for filtering waste from the blood and urine production. Kidney tumors arise from the uncontrolled growth of cells in the kidneys and are responsible for a large share of global cancer-related morbidity and mortality. Understanding the molecular mechanisms driving renal carcinoma progression results crucial for the development of targeted therapies leading to an improvement of patient outcomes. Epigenetic mechanisms such as DNA methylation are known factors underlying the development of several cancer types. There is solid experimental evidence of relevant biological functions modulated by methylation-related genes, associated with the progression of different carcinomas. Those mechanisms can often be associated to different epigenetic marks, such as DNA methylation sites or chromatin conformation patterns. Currently, there is no definitive method to establish clear relations between genetic and epigenetic factors that influence the progression of cancer. Here, we developed a data-driven method to find methylation-related genes, so we could find relevant bonds between gene co-expression and methylation-wide-genome regulation patterns able to drive biological processes during the progression of clear cell renal carcinoma (ccRC). With this approach, we found out genes such as ITK oncogene that appear hypomethylated during all four stages of ccRC progression and are strongly involved in immune response functions. Also, we found out relevant tumor suppressor genes such as RAB25 hypermethylated, thus potentially avoiding repressed functions in the AKT signaling pathway during the evolution of ccRC. Our results have relevant implications to further understand some epigenetic-genetic-affected roles underlying the progression of renal cancer.

Amelioration of non-alcoholic fatty liver disease by targeting adhesion G protein-coupled receptor F1 (Adgrf1)

Background

Recent research has shown that the adhesion G protein-coupled receptor F1 (Adgrf1; also known as GPR110; PGR19; KPG_012; hGPCR36) is an oncogene. The evidence is mainly based on high expression of Adgrf1 in numerous cancer types, and knockdown Adgrf1 can reduce the cell migration, invasion, and proliferation. Adgrf1 is, however, mostly expressed in the liver of healthy individuals. The function of Adgrf1 in liver has not been revealed. Interestingly, expression level of hepatic Adgrf1 is dramatically decreased in obese subjects. Here, the research examined whether Adgrf1 has a role in liver metabolism.

Methods

We used recombinant adeno-associated virus-mediated gene delivery system, and antisense oligonucleotide was used to manipulate the hepatic Adgrf1 expression level in diet-induced obese mice to investigate the role of Adgrf1 in hepatic steatosis. The clinical relevance was examined using transcriptome profiling and archived biopsy specimens of liver tissues from non-alcoholic fatty liver disease (NAFLD) patients with different degree of fatty liver.

Results

The expression of Adgrf1 in the liver was directly correlated to fat content in the livers of both obese mice and NAFLD patients. Stearoyl-coA desaturase 1 (Scd1), a crucial enzyme in hepatic de novo lipogenesis, was identified as a downstream target of Adgrf1 by RNA-sequencing analysis. Treatment with the liver-specific Scd1 inhibitor MK8245 and specific shRNAs against Scd1 in primary hepatocytes improved the hepatic steatosis of Adgrf1-overexpressing mice and lipid profile of hepatocytes, respectively.

Conclusions

These results indicate Adgrf1 regulates hepatic lipid metabolism through controlling the expression of Scd1. Downregulation of Adgrf1 expression can potentially serve as a protective mechanism to stop the overaccumulation of fat in the liver in obese subjects. Overall, the above findings not only reveal a new mechanism regulating the progression of NAFLD, but also proposed a novel therapeutic approach to combat NAFLD by targeting Adgrf1.

Funding

This work was supported by the National Natural Science Foundation of China (81870586), Area of Excellence (AoE/M-707/18), and General Research Fund (15101520) to CMW, and the National Natural Science Foundation of China (82270941, 81974117) to SJ.

The crossroad between autoimmune disorder, tissue remodeling and cancer of the thyroid: The long pentraxin 3 (PTX3)

Thyroid is at the crossroads of immune dysregulation, tissue remodeling and oncogenesis. Autoimmune disorders, nodular disease and cancer of the thyroid affect a large amount of general population, mainly women. We wondered if there could be a common factor behind three processes (immune dysregulation, tissue remodeling and oncogenesis) that frequently affect, sometimes coexisting, the thyroid gland. The long pentraxin 3 (PTX3) is an essential component of the humoral arm of the innate immune system acting as soluble pattern recognition molecule. The protein is found expressed in a variety of cell types during tissue injury and stress. In addition, PTX3 is produced by neutrophils during maturation in the bone-marrow and is stored in lactoferrin-granules. PTX3 is a regulator of the complement cascade and orchestrates tissue remodeling and repair. Preclinical data and studies in human tumors indicate that PTX3 can act both as an extrinsic oncosuppressor by modulating complement-dependent tumor-promoting inflammation, or as a tumor-promoter molecule, regulating cell invasion and proliferation and epithelial to mesenchymal transition, thus suggesting that this molecule may have different functions on carcinogenesis. The involvement of PTX3 in the regulation of immune responses, tissue remodeling and oncosuppressive processes led us to explore its potential role in the development of thyroid disorders. In this review, we aimed to highlight what is known, at the state of the art, regarding the connection between the long pentraxin 3 and the main thyroid diseases i.e., nodular thyroid disease, thyroid cancer and autoimmune thyroid disorders.

Integrated analysis of novel macrophage related signature in anaplastic thyroid cancer

PURPOSE

Patients with anaplastic thyroid cancer (ATC) have a very poor prognosis. Immunotherapy is a potential treatment, while the current outcome is limited which may be due to the complicated tumor microenvironment (TME). Tumor associated macrophages (TAMs) is the most abundant cell in the TME of ATC. We aimed to clarify the novel indicators based on TAM in ATC.

METHODS

Transcriptome files were downloaded from the Gene Expression Omnibus (GEO) dataset. Weighted gene co-expression network analysis, cox regression, support vector machine, and random forest were utilized to identify TAM-related prognostic genes. Consensus clustering and principal component analysis were performed for integrated analysis. Moreover, external validation (Fudan University Shanghai Cancer Center cohort) was conducted in 23 ATC samples via immunohistochemistry.

RESULTS

ATC patients with an abundance of TAMs had a poorer prognosis. Four TAM related genes (FZD6, RBBP8, PREX1, HSD3B7) were identified and a TAM-related prognostic index (TAMRPI) was constructed with high area under the curve (AUC). Next, high TAMRPI was related to the higher level of TAM infiltration and upregulation of several pathways, such as E2F targets, IL6-JAK-STAT3, and G2M checkpoint. Immune checkpoint TIM-3 and CSF1R were positively associated with TAMRPI, and dysfunction of T cells was increased in high TAMRPI subset. Moreover, in the external validation of protein level, strong expression of TAM related genes was related to poorer prognosis, which was further supported by time-dependent AUC analysis.

CONCLUSION

TAM is negatively correlated to the prognosis of ATC. FZD6, RBBP8, PREX1, and HSD3B7 are potential biomarkers of ATC.

Whole genome analysis reveals the genomic complexity in metastatic cutaneous squamous cell carcinoma

Metastatic cutaneous squamous cell carcinoma (CSCC) is a highly morbid disease requiring radical surgery and adjuvant therapy, which is associated with a poor prognosis. Yet, compared to other advanced malignancies, relatively little is known of the genomic landscape of metastatic CSCC. We have previously reported the mutational signatures and mutational patterns of CCCTC-binding factor (CTCF) regions in metastatic CSCC. However, many other genomic components (indel signatures, non-coding drivers, and structural variants) of metastatic CSCC have not been reported. To this end, we performed whole genome sequencing on lymph node metastases and blood DNA from 25 CSCC patients with regional metastases of the head and neck. We designed a multifaceted computational analysis at the whole genome level to provide a more comprehensive perspective of the genomic landscape of metastatic CSCC. In the non-coding genome, 3′ untranslated region (3′UTR) regions of EVC (48% of specimens), PPP1R1A (48% of specimens), and ABCA4 (20% of specimens) along with the tumor-suppressing long non-coding RNA (lncRNA) LINC01003 (64% of specimens) were significantly functionally altered (Q-value < 0.05) and represent potential non-coding biomarkers of CSCC. Recurrent copy number loss in the tumor suppressor gene PTPRD was observed. Gene amplification was much less frequent, and few genes were recurrently amplified. Single nucleotide variants driver analyses from three tools confirmed TP53 and CDKN2A as recurrently mutated genes but also identified C9 as a potential novel driver in this disease. Furthermore, indel signature analysis highlighted the dominance of ID signature 13 (ID13) followed by ID8 and ID9. ID9 has previously been shown to have no association with skin melanoma, unlike ID13 and ID8, suggesting a novel pattern of indel variation in metastatic CSCC. The enrichment analysis of various genetically altered candidates shows enrichment of “TGF-beta regulation of extracellular matrix” and “cell cycle G1 to S check points.” These enriched terms are associated with genetic instability, cell proliferation, and migration as mechanisms of genomic drivers of metastatic CSCC.

Characterization of stem cell landscape and identification of stemness-relevant prognostic gene signature to aid immunotherapy in colorectal cancer

Background

It is generally accepted that colorectal cancer (CRC) originates from cancer stem cells (CSCs), which are responsible for CRC progression, metastasis and therapy resistance. The high heterogeneity of CSCs has precluded clinical application of CSC-targeting therapy. Here, we aimed to characterize the stemness landscapes and screen for certain patients more responsive to immunotherapy.

Methods

Twenty-six stem cell gene sets were acquired from StemChecker database. Consensus clustering algorithm was applied for stemness subtypes identification on 1,467 CRC samples from TCGA and GEO databases. The differences in prognosis, tumor microenvironment (TME) components, therapy responses were evaluated among subtypes. Then, the stemness-risk model was constructed by weighted gene correlation network analysis (WGCNA), Cox regression and random survival forest analyses, and the most important marker was experimentally verified.

Results

Based on single-sample gene set enrichment analysis (ssGSEA) enrichments scores, CRC patients were classified into three subtypes (C1, C2 and C3). C3 subtype exhibited the worst prognosis, highest macrophages M0 and M2 infiltrations, immune and stromal scores, and minimum sensitivity to immunotherapies, but was more sensitive to drugs like Bosutinib, Docetaxel, Elesclomol, Gefitinib, Lenalidomide, Methotrexate and Sunitinib. The turquoise module was identified by WGCNA that it was most positively correlated with C3 but most negatively with C2, and five hub genes in turquoise module were identified for stemness model construction. CRC patients with higher stemness scores exhibited worse prognosis, more immunosuppressive components in TME and lower immunotherapeutic responses. Additionally, the model’s immunotherapeutic prediction efficacy was further confirmed from two immunotherapy cohorts (anti-PD-L1 in IMvigor210 cohort and anti-PD-1 in GSE78220 cohort). Mechanistically, Gene Set Enrichment Analysis (GSEA) results revealed high stemness score group was enriched in interferon gamma response, interferon alpha response, P53 pathway, coagulation, apoptosis, KRAS signaling upregulation, complement, epithelial–mesenchymal transition (EMT) and IL6-mediated JAK-STAT signaling gene sets.

Conclusions

Our study characterized three stemness-related subtypes with distinct prognosis and TME patterns in CRC patients, and a 5-gene stemness-risk model was constructed by comprehensive bioinformatic analyses. We suggest our stemness model has prospective clinical implications for prognosis evaluation and might facilitate physicians selecting prospective responders for preferential use of current immune checkpoint inhibitors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13287-022-02913-0.

Construction of a Signature Model to Predict the Radioactive Iodine Response of Papillary Thyroid Cancer

Papillary thyroid cancer (PTC) accounts for about 90% of thyroid cancer. There are approximately 20%-30% of PTC patients showing disease persistence/recurrence and resistance to radioactive iodine (RAI) treatment. For these PTC patients with RAI refractoriness, the prognosis is poor. In this study, we aimed to establish a comprehensive prognostic model covering multiple signatures to increase the predictive accuracy for progression-free survival (PFS) of PTC patients with RAI treatment. The expression profiles of mRNAs and miRNAs as well as the clinical information of PTC patients were extracted from TCGA and GEO databases. A series of bioinformatics methods were successfully applied to filtrate a two-RNA model (IPCEF1 and hsa-mir-486-5p) associated with the prognosis of RAI-therapy. Finally, the RNA-based risk score was calculated based on the Cox coefficient of the individual RNA, which achieved good performances by the time-dependent receiver operating characteristic (tROC) curve and PFS analyses. Furthermore, the predictive power of the nomogram, integrated with the risk score and clinical parameters (age at diagnosis and tumor stage), was assessed by tROC curves. Collectively, our study demonstrated high precision in predicting the RAI response of PTC patients.

In Vitro and In Vivo Effects of the Urokinase Plasminogen Activator Inhibitor WX-340 on Anaplastic Thyroid Cancer Cell Lines

Increased expression of the urokinase-type plasminogen activator (uPA) system is associated with tumor invasion, neo-angiogenesis, and metastatic spread, and has been shown to positively correlate with a poor prognosis in several cancer types, including thyroid carcinomas. In recent years, several uPA inhibitors were found to have anticancer effects in preclinical studies and in some phase II clinical trials, which prompted us to evaluate uPA as a potential therapeutic target for the treatment of patients affected by the most aggressive form of thyroid cancer, the anaplastic thyroid carcinoma (ATC). In this study, we evaluated the in vitro and in vivo effects of WX-340, a highly specific and selective uPA inhibitor, on two ATC-derived cell lines, CAL-62 and BHT-101. The results obtained indicated that WX-340 was able to reduce cell adhesion and invasiveness in a dose-dependent manner in both cell lines. In addition, WX-340 increased uPA receptor (uPAR) protein levels without affecting its plasma membrane concentration. However, this compound was unable to significantly reduce ATC growth in a xenograft model, indicating that uPA inhibition alone may not have the expected therapeutic effects.

Identification of key genes associated with papillary thyroid microcarcinoma characteristics by integrating transcriptome sequencing and weighted gene co-expression network analysis

OBJECTIVE

Papillary thyroid microcarcinoma (PTMC) is the most prevalent histological type of thyroid carcinoma. Despite the overall favorable prognosis of PTMC, some cases exhibit aggressive phenotypes. The identification of robust biomarkers may improve early PTMC diagnosis. In this study, we integrated high-throughput transcriptome sequencing, bioinformatic analyses and experimental validation to identify key genes associated with the malignant characteristics of PTMC.

METHODS

Total RNA was extracted from 24 PTMC samples and 7 non-malignant thyroid tissue samples, followed by RNA sequencing. The differentially expressed genes (DEGs) were identified and used to construct co-expression networks by weighted gene co-expression network analysis (WGCNA). Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed, and protein-protein interaction networks were constructed. Key modules and hub genes showing a strong correlation with the malignant characteristics of PTMC were identified and validated.

RESULTS

The green-yellow and turquoise modules generated by WGCNA were strongly associated with the malignant characteristics of PTMC. Functional enrichment analysis revealed that genes in the green-yellow module participated in cell motility and metabolism, whereas those in the turquoise module participated in several oncogenic biological processes. Nine real hub genes (FHL1, NDRG2, NEXN, SYNM, COL1A1, FN1, LAMC2, POSTN, and TGFBI) were identified and validated at the transcriptional and translational levels. Our preliminary results indicated their diagnostic potentials in PTMC.

CONCLUSIONS

In this study, we identified key co-expression modules and nine malignancy-related genes with potential diagnostic value in PTMC.

The DPP-IV inhibitor saxagliptin promotes the migration and invasion of papillary thyroid carcinoma cells via the NRF2/HO1 pathway

Dipeptidyl peptidase-IV (DPP-IV) inhibitors are used to control blood glucose levels in patients with type 2 diabetes. However, the influence of DPP-IV inhibitors on malignant tumors remains unknown. The present study aimed to investigate the effect of the DPP-IV inhibitor saxagliptin on thyroid carcinoma cells. Transwell assays and a nude mouse lung metastasis model were used to evaluate the invasion and metastasis of thyroid carcinoma cells. Western blotting was used to determine the protein levels of migration and invasion-related molecules. We tested the expression and distribution of nuclear factor, erythroid 2 like 2 (NRF2) in thyroid carcinoma cells with and without saxagliptin. Furthermore, we silenced NRF2 and observed saxagliptin's effect on migration and invasion. Quantitative real-time reverse transcription PCR (qRT-PCR) and western blotting were then used to measure the expression of NFR2's downstream molecules (heme oxygenase 1 (HO1), matrix metalloproteinase 2 (MMP2), and vascular endothelial growth factor (VEGF)). A luciferase reporter assay was used to validate whether NRF2 could regulate the transcriptional activity of the HO1 promoter. Saxagliptin enhanced the migratory and invasive ability of thyroid carcinoma cells. MMP2 and VEGF levels were also elevated by saxagliptin treatment. We found that saxagliptin treatment increases the nuclear and cytoplasmic accumulation NRF2. Silencing NRF2 abolished the effect of saxagliptin on migration and invasion. Accordingly, NRF2 silencing downregulated HO1, MMP2, and VEGF levels. The luciferase assay showed that NRF2 activated transcription from the HO1 promoter. Saxagliptin could promote this transcriptional activity by upregulating NRF2. Saxagliptin enhanced the migratory and invasive ability of human thyroid carcinoma cells, as well as the expression of MMP2 and VEGF, by activating the NRF2/HO1 pathway.

PTX3 modulates the immunoflogosis in tumor microenvironment and is a prognostic factor for patients with clear cell renal cell carcinoma

Pentraxin-3 (PTX3) belongs to the pentraxine family, innate immune regulators involved in angiogenesis, proliferation and immune escape in cancer. Here, we evaluated PTX3 tissue expression and serum levels as biomarkers of clear cell renal cell carcinoma (ccRCC) and analyzed the possible role of complement system activation on tumor site. A 10-year retrospective cohort study including patients undergoing nephrectomy for ccRCC was also performed. PTX3 expression was elevated in both neoplastic renal cell lines and tissues, while it was absent in both normal renal proximal tubular cells (HK2) and normal renal tissues. Analysis of complement system activation on tumor tissues showed the co-expression of PTX3 with C1q, C3aR, C5R1 and CD59, but not with C5b-9 terminal complex. RCC patients showed higher serum PTX3 levels as compared to non-neoplastic patients (p<0.0001). Higher PTX3 serum levels were observed in patients with higher Fuhrman grade (p<0.01), lymph node (p<0.0001), and visceral metastases (p<0.001). Patients with higher PTX3 levels also showed significantly lower survival rates (p=0.002). Our results suggest that expression of PTX3 can affect the immunoflogosis in the ccRCC microenvironment, by activating the classical pathway of CS (C1q) and releasing pro-angiogenic factors (C3a, C5a). The up-regulation of CD59 also inhibits the complement-mediated cellular lysis.

The Emerging Role of Adhesion GPCRs in Cancer

Aberrant expression, function, and mutation of G protein-coupled receptors (GPCRs) and their signaling partners, G proteins, have been well documented in many forms of cancer. These cell surface receptors and their endogenous ligands are implicated in all aspects of cancer including proliferation, angiogenesis, invasion, and metastasis. Adhesion GPCRs (aGPCRs) form the second largest family of GPCRs, most of which are orphan receptors with unknown physiological functions. This is mainly due to our limited insight into their structure, natural ligands, signaling pathways, and tissue expression profiles. Nevertheless, recent studies show that aGPCRs play important roles in cell adhesion to the extracellular matrix and cell-cell communication, processes that are dysregulated in cancer. Emerging evidence suggests that aGPCRs are implicated in migration, proliferation, and survival of tumor cells. We here review the role of aGPCRs in the five most common types of cancer (lung, breast, colorectal, prostate, and gastric) and emphasize the importance of further translational studies in this field.

The Long Pentraxin PTX3 as a Link Between Innate Immunity, Tissue Remodeling, and Cancer

The innate immune system comprises a cellular and a humoral arm. Humoral pattern recognition molecules include complement components, collectins, ficolins, and pentraxins. These molecules are involved in innate immune responses by recognizing microbial moieties and damaged tissues, activating complement, exerting opsonic activity and facilitating phagocytosis, and regulating inflammation. The long pentraxin PTX3 is a prototypic humoral pattern recognition molecule that, in addition to providing defense against infectious agents, plays several functions in tissue repair and regulation of cancer-related inflammation. Characterization of the PTX3 molecular structure and biochemical properties, and insights into its interactome and multiple roles in tissue damage and remodeling support the view that microbial and matrix recognition are evolutionarily conserved functions of humoral innate immunity molecules.

Genetic expression profile-based screening of genes and pathways associated with papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common subtype of thyroid cancer; however, the specific genes and signaling pathways involved in this cancer remain largely unclear. The present study analyzed three profile datasets, GSE6004, GSE29265 and GSE60542, which were comprised of 47 PTC and 41 normal thyroid tissue samples, to identify key genes and pathways associated with PTC. Initially, differentially-expressed genes (DEGs) between PTC and normal thyroid tissue were screened using R 3.4.0 (2017-04-21, R Foundation, Vienna, Austria, http://www.R-project.org/). These DEGs were then clustered by gene ontology functional terms and representative signaling pathways. Additionally, specific key gene nodes were filtered out from a constructed protein-protein interaction (PPI) network. The results identified a total of 423 shared DEGs associated with PTC, including 211 upregulated and 212 downregulated genes. These 423 genes were primarily enriched in glycosaminoglycan binding, sulfur compound binding, heparin binding, enzyme activator activity, peptidase activator activity and hsa04512: Extracellular matrix (ECM)-receptor interaction. A total of 21 central node genes were identified as key genes in the PTC disease process including complement factor D (CFD), Collagen Type I α 1 Chain (COL1A1), Extracellular Matrix Protein 1 (ECM1) and Fibronectin 1 (FN1). These genes are involved in protease binding, G-protein coupled receptor binding, extracellular matrix structural constituent and peptidase regulator activity. To conclude, using bioinformatics analysis, the present study identified candidate DEGs and critical pathways in PTC that may improve the current understanding regarding the underlying mechanisms of PTC. These genes and pathways may be used as potential therapeutic targets of PTC in the future.

Network Modularity in Breast Cancer Molecular Subtypes

Breast cancer is a heterogeneous and complex disease, a clear manifestation of this is its classification into different molecular subtypes. On the other hand, gene transcriptional networks may exhibit different modular structures that can be related to known biological processes. Thus, modular structures in transcriptional networks may be seen as manifestations of regulatory structures that tightly controls biological processes. In this work, we identify modular structures on gene transcriptional networks previously inferred from microarray data of molecular subtypes of breast cancer: luminal A, luminal B, basal, and HER2-enriched. We analyzed the modules (communities) found in each network to identify particular biological functions (described in the Gene Ontology database) associated to them. We further explored these modules and their associated functions to identify common and unique features that could allow a better level of description of breast cancer, particularly in the basal-like subtype, the most aggressive and poor prognosis manifestation. Our findings related to the immune system and a decrease in cell death-related processes in basal subtype could help to understand it and design strategies for its treatment.

A transcriptome-based protein network that identifies new therapeutic targets in colorectal cancer

Background

Colon cancer occurrence is increasing worldwide, making it the third most frequent cancer. Although many therapeutic options are available and quite efficient at the early stages, survival is strongly decreased when the disease has spread to other organs. The identification of molecular markers of colon cancer is likely to help understanding its course and, eventually, to uncover novel genes to be targeted by drugs. In this study, we compared gene expression in a set of 95 human colon cancer samples to that in 19 normal colon mucosae, focusing on 401 genes from 5 selected pathways (Apoptosis, Cancer, Cholesterol metabolism and lipoprotein signaling, Drug metabolism, Wnt/beta-catenin). Deregulation of mRNA levels largely matched that of proteins, leading us to build in silico protein networks, starting from mRNA levels, to identify key proteins central to network activity.

Results

Among the analyzed genes, 10.5% (42) had no reported link with colon cancer, including the SFRP1, IGF1 and ADH1B (down), and MYC and IL8 (up), whose encoded proteins were most interacting with other proteins from the same or even distinct networks. Analyzing all pathways globally led us to uncover novel functional links between a priori unrelated or rather remotely connected pathways, such as the Drug metabolism and the Cancer pathways or, even more strikingly, between the Cholesterol metabolism and lipoprotein signaling and the Cancer pathways. In addition, we analyzed the responsiveness of some of the deregulated genes essential to network activities, to chemotherapeutic agents used alone or in presence of Lovastatin, a lipid-lowering drug. Some of these treatments could oppose the deregulations occurring in cancer samples, including those of the CHECK2, CYP51A1, HMGCS1, ITGA2, NME1 or VEGFA genes.

Conclusions

Our network-based approach allowed discovering genes not previously known to play regulatory roles in colon cancer. Our results also showed that selected drug treatments might revert the cancer-specific deregulation of genes playing prominent roles within the networks operating to maintain colon homeostasis. Among those genes, some could constitute novel testable targets to eliminate colon cancer cells, either directly or, potentially, through the use of lipid-lowering drugs such as statins, in association with selected anticancer drugs.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4139-y) contains supplementary material, which is available to authorized users.

Using Ion Torrent sequencing to study genetic mutation profiles of fatal thyroid cancers

BACKGROUND/PURPOSE

Surgery followed by radioiodine is a mainstay of treatment for thyroid cancers of follicular origins. However, about 5% of the thyroid cancers are non-operable and/or radioiodine-refractory diseases, which are either locally advanced or metastatic and result in a survival of less than 5 years. How to treat this population of thyroid cancer patients becomes a critical issue requiring further understanding of the tumor's genetic information.

METHODS

We used formalin-fixed paraffin-embedded specimens of 22 fatal thyroid cancers and their corresponding non-tumor parts, if available, to yield genomic DNA, and applied the Ion Torrent™ Personal Genome Machine (IT-PGM) System (Life Technologies), a next generation sequencing technology, to interrogate 740 mutational hotspots in 46 oncogenes. We further validated the results by conventional direct sequencing.

RESULTS

We confirmed 21 mutations of 11 oncogenes in the 22 fatal thyroid cancer samples. Among them, the MET p.N375S and MLH1 p.V384D mutations, each was detected in two cases, and has rarely been found to be involved in thyroid cancer pathogenesis before. We also identified homozygous PDGFRA p.V824V mutation in eight out of the 22 cases, while the non-tumor counterparts carried heterozygous PDGFRA p.V824V mutation. We noted that the Ion Torrent technique unfortunately showed high false positive rates for detecting EGFR mutations in thyroid cancers.

CONCLUSION

The extensive genetic studies provide new insights to future targeted therapy in these patients. IT-PGM proved to be valuable for comprehensively searching genetic mutations in potentially fatal thyroid cancers.

RNA-Seq based genome-wide analysis reveals loss of inter-chromosomal regulation in breast cancer

Breast cancer is a complex heterogeneous disease. Common hallmark features of cancer can be found. Their origin may be traced back to their intricate relationships governing regulatory programs during the development of this disease. To unveil distinctive features of the transcriptional regulation program in breast cancer, a pipeline for RNA-seq analysis in 780 breast cancer and 101 healthy breast samples, at gene expression and network level, was implemented. Inter-chromosomal relationships between genes resulted strikingly scarce in a cancer network, in comparison to its healthy counterpart. We suggest that inter-chromosomal regulation loss may be a novel feature in breast cancer. Additional evidence was obtained by independent validation in microarray and Hi-C data as well as supplementary computational analyses. Functional analysis showed upregulation in processes related to cell cycle and division; while migration, adhesion and cell-to-cell communication, were downregulated. Both the BRCA1 DNA repairing signalling and the Estrogen-mediated G1/S phase entry pathways were found upregulated. In addition, a synergistic underexpression of the γ-protocadherin complex, located at Chr5q31 is also shown. This region has previously been reported to be hypermethylated in breast cancer. These findings altogether provide further evidence for the central role of transcriptional regulatory programs in shaping malignant phenotypes.

Cell Cycle M-Phase Genes Are Highly Upregulated in Anaplastic Thyroid Carcinoma

BACKGROUND

Anaplastic thyroid carcinoma (ATC) accounts for only 3% of thyroid cancers, yet strikingly, it accounts for almost 40% of thyroid cancer deaths. Currently, no effective therapies exist. In an effort to identify ATC-specific therapeutic targets, we analyzed global gene expression data from multiple studies to identify ATC-specific dysregulated genes.

METHODS

The National Center for Biotechnology Information Gene Expression Omnibus database was searched for high-throughput gene expression microarray studies from human ATC tissue along with normal thyroid and/or papillary thyroid cancer (PTC) tissue. Gene expression levels in ATC were compared with normal thyroid or PTC using seven separate comparisons, and an ATC-specific gene set common in all seven comparisons was identified. We investigated these genes for their biological functions and pathways.

RESULTS

There were three studies meeting inclusion criteria, (including 32 ATC patients, 69 PTC, and 75 normal). There were 259 upregulated genes and 286 downregulated genes in ATC with at least two-fold change in all seven comparisons. Using a five-fold filter, 36 genes were upregulated in ATC, while 40 genes were downregulated. Of the 10 top globally upregulated genes in ATC, 4/10 (MMP1, ANLN, CEP55, and TFPI2) are known to play a role in ATC progression; however, 6/10 genes (TMEM158, CXCL5, E2F7, DLGAP5, MME, and ASPM) had not been specifically implicated in ATC. Similarly, 3/10 (SFTA3, LMO3, and C2orf40) of the most globally downregulated genes were novel in this context, while 7/10 genes (SLC26A7, TG, TSHR, DUOX2, CDH1, PDE8B, and FOXE1) have been previously identified in ATC. We experimentally validated a significant correlation for seven transcription factors (KLF16, SP3, ETV6, FOXC1, SP1, EGFR1, and MAFK) with the ATC-specific genes using microarray analysis of ATC cell lines. Ontology clustering of globally altered genes revealed that "mitotic cell cycle" is highly enriched in the globally upregulated gene set (44% of top upregulated genes, p-value <10^-30).

CONCLUSIONS

By focusing on globally altered genes, we have identified a set of consistently altered biological processes and pathways in ATC. Our data are consistent with an important role for M-phase cell cycle genes in ATC, and may provide direction for future studies to identify novel therapeutic targets for this disease.

Molecular profiles of thyroid cancer subtypes: Classification based on features of tissue revealed by mass spectrometry imaging

Determination of the specific type of thyroid cancer is crucial for the prognosis and selection of treatment of this malignancy. However, in some cases appropriate classification is not possible based on histopathological features only, and it might be supported by molecular biomarkers. Here we aimed to characterize molecular profiles of different thyroid malignancies using mass spectrometry imaging (MSI) which enables the direct annotation of molecular features with morphological pictures of an analyzed tissue. Fifteen formalin-fixed paraffin-embedded tissue specimens corresponding to five major types of thyroid cancer were analyzed by MALDI-MSI after in-situ trypsin digestion, and the possibility of classification based on the results of unsupervised segmentation of MALDI images was tested. Novel method of semi-supervised detection of the cancer region of interest (ROI) was implemented. We found strong separation of medullary cancer from malignancies derived from thyroid epithelium, and separation of anaplastic cancer from differentiated cancers. Reliable classification of medullary and anaplastic cancers using an approach based on automated detection of cancer ROI was validated with independent samples. Moreover, extraction of spectra from tumor areas allowed the detection of molecular components that differentiated follicular cancer and two variants of papillary cancer (classical and follicular). We concluded that MALDI-MSI approach is a promising strategy in the search for biomarkers supporting classification of thyroid malignant tumors. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

The Genomic Landscape of Pancreatic and Periampullary Adenocarcinoma

Despite advances in diagnostics, less than 5% of patients with periampullary tumors experience an overall survival of five years or more. Periampullary tumors are neoplasms that arise in the vicinity of the ampulla of Vater, an enlargement of liver and pancreas ducts where they join and enter the small intestine. In this study, we analyzed copy number aberrations using Affymetrix SNP 6.0 arrays in 60 periampullary adenocarcinomas from Oslo University Hospital to identify genome-wide copy number aberrations, putative driver genes, deregulated pathways, and potential prognostic markers. Results were validated in a separate cohort derived from The Cancer Genome Atlas Consortium (n = 127). In contrast to many other solid tumors, periampullary adenocarcinomas exhibited more frequent genomic deletions than gains. Genes in the frequently codeleted region 17p13 and 18q21/22 were associated with cell cycle, apoptosis, and p53 and Wnt signaling. By integrating genomics and transcriptomics data from the same patients, we identified CCNE1 and ERBB2 as candidate driver genes. Morphologic subtypes of periampullary adenocarcinomas (i.e., pancreatobiliary or intestinal) harbor many common genomic aberrations. However, gain of 13q and 3q, and deletions of 5q were found specific to the intestinal subtype. Our study also implicated the use of the PAM50 classifier in identifying a subgroup of patients with a high proliferation rate, which had impaired survival. Furthermore, gain of 18p11 (18p11.21-23, 18p11.31-32) and 19q13 (19q13.2, 19q13.31-32) and subsequent overexpression of the genes in these loci were associated with impaired survival. Our work identifies potential prognostic markers for periampullary tumors, the genetic characterization of which has lagged. Cancer Res; 76(17); 5092-102. ©2016 AACR.

Transcriptional master regulator analysis in breast cancer genetic networks

Gene regulatory networks account for the delicate mechanisms that control gene expression. Under certain circumstances, gene regulatory programs may give rise to amplification cascades. Such transcriptional cascades are events in which activation of key-responsive transcription factors called master regulators trigger a series of gene expression events. The action of transcriptional master regulators is then important for the establishment of certain programs like cell development and differentiation. However, such cascades have also been related with the onset and maintenance of cancer phenotypes. Here we present a systematic implementation of a series of algorithms aimed at the inference of a gene regulatory network and analysis of transcriptional master regulators in the context of primary breast cancer cells. Such studies were performed in a highly curated database of 880 microarray gene expression experiments on biopsy-captured tissue corresponding to primary breast cancer and healthy controls. Biological function and biochemical pathway enrichment analyses were also performed to study the role that the processes controlled - at the transcriptional level - by such master regulators may have in relation to primary breast cancer. We found that transcription factors such as AGTR2, ZNF132, TFDP3 and others are master regulators in this gene regulatory network. Sets of genes controlled by these regulators are involved in processes that are well-known hallmarks of cancer. This kind of analyses may help to understand the most upstream events in the development of phenotypes, in particular, those regarding cancer biology.