MiR-361-5p as a promising qRT-PCR internal control for tumor and normal breast tissues

Background: One of the most widely used evaluation methods in miRNA experiments is qRT-PCR. However, selecting suitable internal controls (IC) is crucial for qRT-PCR experiments. Currently, there is no consensus on the ICs for miRNA qRT-PCR experiments in breast cancer. To this end, we tried to identify the most stable (the least expression alteration) and promising miRNAs in normal and tumor breast tissues by employing TCGA miRNA-Seq data and then experimentally validated them on fresh clinical samples. Methods: A multi-component scoring system was used which takes into account multiple expression stability criteria as well as correlation with clinical characteristics. Furthermore, we extended the scoring system for more than two biological sub-groups. TCGA BRCA samples were analyzed based on two grouping criteria: Tumor & Normal samples and Tumor subtypes. The top 10 most stable miRNAs were further investigated by differential expression and survival analysis. Then, we examined the expression level of the top scored miRNA (hsa-miR- 361-5p) along with two commonly used ICs hsa-miR-16-5p and U48 on 34 pairs of Primary breast tumor and their adjacent normal tissues using qRT-PCR. Results: According to our multi-component scoring system, hsa-miR-361-5p had the highest stability score in both grouping criteria and hsa-miR-16-5p showed significantly lower scores. Based on our qRT-PCR assay, while U48 was the most abundant IC, hsa-miR-361-5p had lower standard deviation and also was the only IC capable of detecting a significant up-regulation of hsa-miR-21-5p in breast tumor tissue. Conclusions: miRNA-Seq data is a great source to discover stable ICs. Our results demonstrated that hsa-miR-361-5p is a highly stable miRNA in tumor and non-tumor breast tissue and we. recommend it as a suitable reference gene for miRNA expression studies in breast cancer. Additionally, although hsa-miR-16-5p is a commonly used IC, it's not a suitable one for breast cancer studies. Copyright © 2021 Ghanbari et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Expression and function of c1orf132 long-noncoding rna in breast cancer cell lines and tissues

miR-29b2 and miR-29c play a suppressive role in breast cancer progression. C1orf132 (also named MIR29B2CHG) is the host gene for generating both microRNAs. However, the region also expresses longer transcripts with unknown functions. We employed bioinformatics and experimental approaches to decipher C1orf132 expression and function in breast cancer tissues. We also used the CRISPR/Cas9 technique to excise a predicted C1orf132 distal promoter and followed the behavior of the edited cells by real-time PCR, flow cytometry, migration assay, and RNA-seq techniques. We observed that C1orf132 long transcript is significantly downregulated in triple-negative breast cancer. We also identified a promoter for the longer transcripts of C1orf132 whose functionality was demonstrated by transfecting MCF7 cells with a C1orf132 promoter-GFP construct. Knocking-out the promoter by means of CRISPR/Cas9 revealed no alterations in the expression of the neighboring genes CD46 and CD34, while the expression of miR-29c was reduced by half. Furthermore, the promoter knockout elevated the migration ability of the edited cells. RNA sequencing revealed many up-and downregulated genes involved in various cellular pathways, including epithelial to mesenchymal transition and mammary gland development pathways. Altogether, we are reporting here the existence of an additional/distal promoter with an enhancer effect on miR-29 generation and an inhibitory effect on cell migration. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

A novel metabolic disorder in the degradation pathway of endogenous methanol due to a mutation in the gene of alcohol dehydrogenase

Background: A small amount of methanol is produced endogenously in the human body but it is efficiently metabolized by alcohol dehydrogenase (ADH) and other enzymes, and the products eliminated without harm. In this study, we present a new entity of inborn error of methanol metabolism due to a mutation in the ADH1C gene coding for the γ subunit that is part of several ADH isoenzymes. Results: This disorder was discovered in an 11.58-year-old boy. During one 9-month hospital admission, he had periods of 1�4 days during which he was comatose, and between these periods he was sometimes verbose and euphoric, and had ataxia, dysarthria. Following hemodialysis treatments, he became conscious and appeared healthy. Organ evaluations and his laboratory tests were normal. Toxicological evaluation of his blood showed a high methanol level 12.2 mg/dL (3.8 mmol/L), normal range up to 3.5 mg/dL (1.09 mmol/L) while the formaldehyde level was undetectable. The finding of liver function tests that were within normal limits, coupled with a normal eye examination and size of the liver, elevated blood methanol levels and an undetectable formaldehyde level, suggested ADH insufficiency. Adding zinc to the drug regimen 15 mg/daily dramatically reduced the patient's methanol level and alleviated the abnormal symptoms. When zinc supplementation was discontinued, the patient relapsed into a coma and hemodialysis was once again required. A homozygous mutation in ADH1C gene located at exon 3 was found, and both parents were heterozygous for this mutation. Conclusion: Accumulation of methanol due to mutation in ADH1C gene may result in drunkenness and ataxia, and leads to coma. This condition can be successfully treated with zinc supplementation as the cofactor of ADH. © 202

The Role and Importance of Genome Sequencing in Prediction of Cancer Risk

The role and relative importance of intrinsic and extrinsic factors in the development of complex diseases such as cancer still remains a controversial issue. Determining the amount of variation explained by these factors needs experimental data and statistical models. These models are nevertheless based on the occurrence and accumulation of random mutational events during stem cell division, thus rendering cancer development a stochastic outcome. We demonstrate that not only individual genome sequencing is uninformative in determining cancer risk, but also assigning a unique genome sequence to any given individual (healthy or affected) is not meaningful. Current whole-genome sequencing approaches are therefore unlikely to realize the promise of personalized medicine. In conclusion, since genome sequence differs from cell to cell and changes over time, it seems that determining the risk factor of complex diseases based on genome sequence is somewhat unrealistic, and therefore, the resulting data are likely to be inherently uninformative

Proteome analysis of ground state pluripotency

The differentiation potential of pluripotent embryonic stem cells (ESCs) can be manipulated via serum and medium conditions for direct cellular development or to maintain a naïve ground state. The self-renewal state of ESCs can thus be induced by adding inhibitors of mitogen activated protein kinase (MAPK) and glycogen synthase kinase-3 (Gsk3), known as 2 inhibitors (2i) treatment. We have used a shotgun proteomics approach to investigate differences in protein expressions between 2i- and serum-grown mESCs. The results indicated that 164 proteins were significantly upregulated and 107 proteins downregulated in 2i-grown cells compared to serum. Protein pathways in 2i-grown cells with the highest enrichment were associated with glycolysis and gluconeogenesis. Protein pathways related to organ development were downregulated in 2i-grown cells. In serum-grown ESCs, protein pathways involved in integrin and focal adhesion, and signaling proteins involved in the actin cytoskeleton regulation were enriched. We observed a number of nuclear proteins which were mostly involved in self-renewal maintenance and were expressed at higher levels in 2i compared to serum - Dnmt1, Map2k1, Parp1, Xpo4, Eif3g, Smarca4/Brg1 and Smarcc1/Baf155. Collectively, the results provided an insight into the key protein pathways used by ESCs in the ground state or metastable conditions through 2i or serum culture medium, respectively.10 page(s

Temporal activation of LRH-1 and RAR-gamma in human pluripotent stem cells induces a functional naive-like state

Naive pluripotency can be established in human pluripotent stem cells (hPSCs) by manipulation of transcription factors, signaling pathways, or a combination thereof. However, differences exist in the molecular and functional properties of naive hPSCs generated by different protocols, which include varying similarities with pre-implantation human embryos, differentiation potential, and maintenance of genomic integrity. We show here that short treatment with two chemical agonists (2a) of nuclear receptors, liver receptor homologue-1 (LRH-1) and retinoic acid receptor gamma (RAR-gamma), along with 2i/LIF (2a2iL) induces naive-like pluripotency in human cells during reprogramming of fibroblasts, conversion of pre-established hPSCs, and generation of new cell lines from blastocysts. 2a2iL-hPSCs match several defined criteria of naive-like pluripotency and contribute to human-mouse interspecies chimeras. Activation of TGF-beta signaling is instrumental for acquisition of naive-like pluripotency by the 2a2iL induction procedure, and transient activation of TGF-beta signaling substitutes for 2a to generate naive-like hPSCs. We reason that 2a2iL-hPSCs are an easily attainable system to evaluate properties of naive-like hPSCs and for various applications