Identification of differential expressed transcripts in cervical cancer of Mexican patients

Upregulation of long non-coding RNA ENSG00000267838 is related to the high risk of progression and non-response to chemoradiotherapy treatment for cervical cancer

Cervical cancer (CC) is a global public health concern, primarily caused by persistent infection with oncogenic types of human papillomavirus (HPV). The World Health Organization (WHO) has established a plan to eliminate CC as a public health issue by the year 2100. However, the implementation of the HPV vaccine is impeded by vaccine restrictions and misinformation despite its demonstrated effectiveness. The CC treatment is influenced by the disease stage, with an unfavorable prognosis for those in advanced stages. This study aimed to investigate the potential of long non-coding RNAs (lncRNAs) in CC by identifying and characterizing related lncRNAs, elucidating their regulatory mechanisms and molecular interactions, and analyzing their expression patterns in patients with diverse responses to chemoradiotherapy. Non-stem cells from CC were isolated using flow cytometry sorting and used for total RNA extraction. The RNA was used to build libraries that were subsequently sequenced using the Illumina Nextseq 550.417 lncRNAs that showed differentially expressed between CC patients who responded or not to treatment. Further analysis demonstrated that these lncRNAs significantly interact with several molecules, which play crucial roles in CC progression and therapeutic resistance. Statistical analysis correlated the expression profile of these lncRNAs with treatment efficacy. Three lncRNAs, ENSG00000267838, ENSG00000266340, and FRMD6-AS1, were identified with positive expression related to non-response to chemoradiotherapy and worse progression-free survival in CC patients. Specifically, lncRNA ENSG00000267838 has its up-regulation related to non-response and down-regulation to response to chemoradiotherapy treatment.

Protein Expression Analysis in Uterine Cervical Cancer for Potential Targets in Treatment

Specific markers in lesions of the human uterine cervix cancer (UCC) are still needed for prognostic, diagnostic and/or therapeutic purposes. In this study we evaluated key molecules at protein level between normal epithelium, cervical intraepithelial neoplasia (CIN1-3) and invasive cancer of a group of molecules previously reported at mRNA level. For that purpose, human formalin-fixed paraffin embedded tissue microarrays (TMAs) were constructed containing 205 Mexican tissue core specimens. Immunohistochemistry and quantitative analysis of histological staining was performed against twenty-two distinct proteins for each core and the processing platform ImageJ. In the progression of the disease we found key statistical differences for the proteins SEL1, Notch3 and SOCS3. High expressions of SEL1L, Notch3 and SOCS3 have potential value to increase the prognostic of UCC in combination with markers such as p16^INK4a. This study identified key drivers in cervical carcinogenesis that should be evaluated for the development of UCC therapies.

Transcriptomic analysis in diabetic nephropathy of streptozotocin-induced diabetic rats

Diabetic nephropathy (DN) is a major complication of diabetes and is caused by an imbalance in the expression of certain genes that activate or inhibit vital cellular functions of kidney. Despite several recent advances, the pathogenesis of DN remains far from clear, suggesting the need to carry out studies identifying molecular aspects, such as gene expression, that could play a key role in the development of DN. There are several techniques to analyze transcriptome in living organisms. In this study, the suppression subtractive hybridization (SSH) method was used to generate up- and down-regulated subtracted cDNA libraries in the kidney of streptozotocin (STZ)-induced diabetic rats. Northern-blot analysis was used to confirm differential expression ratios from the obtained SSH clones to identify genes related to DN. 400 unique SSH clones were randomly chosen from the two subtraction libraries (200 of each) and verified as differentially expressed. According to blast screening and functional annotation, 20.2% and 20.9% of genes were related to metabolism proteins, 9% and 3.6% to transporters and channels, 16% and 6.3% to transcription factors, 19% and 17.2% to hypothetical proteins, and finally 24.1 and 17.2% to unknown genes, from the down- and up-regulated libraries, respectively. The down- and up-regulated cDNA libraries differentially expressed in the kidney of STZ diabetic rats have been successfully constructed and some identified genes could be highly important in DN.