Implication of Long Non-coding RNA HOTTIP Haplotype on Liver Cancer Metastasis

Overview

Hepatocellular carcinoma (HCC) represents the fourth common cancer and the most common cause of mortality-caused and morbidity-related cancer. Different reports implied several lncRNAs role in the progression and metastasis of HCC such as Homeobox A (HOXA) transcript at the distal tip (HOTTIP). Dysregulation of HOTTIP is associated with various malignancies including HCC, affecting survival and prognosis of cancer patients. HOTTIP promoted HCC cell proliferation/metastasis and might act as an oncogenic-lncRNA in HCC. Genetic variations such as single-nucleotide polymorphisms (SNPs), when inherited together, as a group, known as haplotypes. Haplotypes can alter the expression of coding genes and the protein non-coding genes like lncRNAs, therefore, affecting the disease course, including liver, a hypothesis to be addressed. Only few studies have focused on the polymorphisms of the onco-lncRNA HOTTIP gene. A study found that specific HOTTIP SNPs have the potential to be biomarkers for HCC risk and prognosis, where one haplotype of HOTTIP "rs17501292-rs2067087-rs17427960" showed a 1.91-fold increased risk of HCC.

1. Introduction Hepatocellular carcinoma HCC is a complex disease, which could be caused by viruses as hepatitis B and C infection, drug abuse, and chemicals such as aflatoxin. However, treatments for HCC are limited, and most of them are only effective at an early stage. At an advanced stage, this cancer is associated with a poor prognosis, due to frequent cancer metastasis, tumor recurrence and a lack of curative treatment. Different reports implied several lncRNAs role in the progression and metastasis of HCC such as HOXA transcript at the distal tip (HOTTIP). HOTTIP might act as an oncogenic-lncRNA in HCC. Genetic variations such as single-nucleotide polymorphisms (SNPs), when inherited together, as a group, because of high Linkage Disequilibrium (LD), there tends to be redundant information. The regions of the genome with high LD, that harbor a specific set of SNPs, are inherited together, known as haplotypes. Haplotypes can alter the expression of coding genes and the protein non-coding genes like lncRNAs. Only few studies have focused on the polymorphisms of the onco-lncRNA HOTTIP gene. A recent study found that specific HOTTIP SNPs have the potential to be biomarkers for HCC risk and prognosis, where one haplotype of HOTTIP gene "rs17501292-rs2067087-rs17427960" showed a 1.91-fold increased risk of HCC (P = 0.006) in Chinese patients' samples. .............. 2. Objectives 2.1. Genotype different haplotype SNPs of lncRNA HOTTIP in whole blood samples (Liquid biopsy) from metastatic HCC patients, and to be compared with sex and age-matched non-metastatic patients. 2.2. Correlate HCC clinicopathological characteristics (tumor stage and grade, tumor progression (TNM) and different clinical presentations as presence/absence of metastasis, and other classical clinico-pathological prognostic biomarkers such as α-fetoprotein (AFP), carcinoembryonic antigen (CEA), alkaline phosphatase (ALP), alanine transaminase (ALT), aspartate transaminase (AST), International normalized ratio (INR), prothrombin concentration (PC), total bilirubin, Gamma-glutamyltransferase (GGT), and complete blood count (CBC), blood pressure, blood glucose level, serum insulin, and body mass index (BMI), c-reactive protein (CRP), albumin, blood urea nitrogen (BUN) and prognostic marker(s)/outcome to HOTTIP genotypes or different haplotype SNPs. 2.3. Correlate HOTTIP lncRNA influence on some HCC hallmarks (tumor growth, proliferation, and/or metastasis). 2.4. Molecular Docking for exploring potential drugs that could be re-purposed to inhibit our target oncogenic lncRNA HOTTIP. ................... 3. Subjects - 198 HCC patients attending the Faculty of Medicine, Ain Shams University Hospital, with 1:1 or 1:2 ratio for the HCC groups metastatic vs non metastatic HCC groups (according to clinical evidence/relevance and/or availability). Group 1; non-metastatic HCC patients, Group 2; metastatic HCC patients, diagnosed with primary HCC receiving any type of therapy (neoadjuvant or radiotherapy). Eligibility criterion are adult age and male/female 1:1. Criteria for HCC diagnosis following the Ain Shams University (ASU) hospital role relying on AFP level and CT scan or the fine needle biopsy. Groups to be matched socioeconomically, in age range, sex Male/Female 1:1, residence (case-controlled study). \- Exclusion criteria. HCC patients who have history of liver transplantation, have other cancer types at the time of selection, presented by renal insufficiency, and thyroid dysfunction will be excluded from the study. Additionally, patients with incomplete data or histopathology diagnosis. * Data to be collected HCC patients' Clinico-pathological Criteria. Clinical data will be obtained from medical records and the original pathology reports. These data to be compiled in an Excel sheet. Clinical data to be recorded and assessed: * Cancer family history, * Individual cancer history and the tumor clinical assessment done using the tumor-node-metastasis (TNM) classification of the American Joint Committee on Cancer (AJCC). * HCC histological grading made in accordance to Edmondson-Steiner (ES). * The characteristics of the HCC patients with regards to Ultrasound (US) findings (cirrhosis, ascites, and splenomegaly), Total and direct bilirubin, ALP, Prothrombin time (PT), PC, INR, hemoglobin (HB), CBC, White Blood Cells (WBCs), Platelets and ALT to Platelet Ratio index (APRI) score\[The formula for the APRI score is (AST/upper limit of the normal AST range) X 100/Platelet Count\], serum insulin, blood glucose level, BMI, BP, albumin, BUN. * Tumor size, as well as clinico-pathological biomarkers AFP, CEA, GGT data will be collected from patient files for further correlations and statistical analysis. * For both groups treatment type and for group 2 the site of metastatic destination, disease-free survival (DFS), overall survival (OS), the duration of patient survival from the time of treatment initiation will be considered as a universally accepted direct measure of clinical benefit. * Methodology 4.1. Bioinformatic Analysis: Selected Polymorphic Sites The investigators selected polymorphisms using 1000 Genome data (http://www.internationalgenome.org/home), as reported previously. The tag SNPs were selected separately using the following criteria: (1) Haploview with the Tagger function was used; (2) the population of the HapMap selected Yoruba in Ibadan, Nigeria (YRI) population; (3) those for which pairwise tagging had r2 of ≥ 0.8; and (4) those with a minor allele frequency of ≥ 5%. The selection area was enlarged by 10 kb both upstream and downstream for HOTTIP lncRNA gene. Fast SNP and f SNP searches were used to predict the potential SNP function (http://compbio.cs.queensu.ca/F-SNP/). After block identification, many SNPs were detected, among them, 2 SNPs with high LD (\< 0.8) were selected: rs17501292-rs2067087. 4.2. Blood Samples. Genomic DNA will be extracted from whole ethylenediaminetetraacetic acid (EDTA) blood samples from all subjects using the DNA Mini Kit (Qiagen, Valencia, CA) according to the manufacturer's instructions. The yield will be measured by Nano Drop 2000 (Thermo Fisher Scientific, UK) and will be aliquoted into 5 clean Eppendorf tubes and stored at -80°C, until biochemical assessment at the Faculty of Pharmacy, Ain-Shams University, Advanced Biochemistry Research Lab (ABRL). 4.3. SNPs Genotyping rs17501292 (NC\_000007.14:27201853: T:C, NC\_000007.14:27201853: T: G ;T \> C, G), rs2067087 (NC\_000007.14:27202040:G:C,NC\_000007.14:27202040:G:T ; G\> C,T),will be genotyped using real-time polymerase chain reaction (RT-PCR) with the TaqMan allelic discrimination assay on a 7900 system using predesigned primer/probe (Applied Biosystems Inc). ............................ * STATISTICAL ANALYSIS 5.1. SPSS v.25 USA (SPSS, Chicago, IL) or Stat or Graph Pad will be used for statistical analysis. 5.2. Data will be collected, excel tabulated and tested for normality by Kolmogorov-Smirnov test. 5.3. Between-group differences in sex variability will be compared by the χ2 test and by analysis of variance for age variability. Multivariate logistic regression with adjustments for age and sex will be used to show the association between selected lncRNA polymorphisms and HCC risk. 5.4. Normally distributed variables will be expressed as mean+ (S.E.M) and analyzed using two samples independent t-test. Median (interquartile range) will be used to express nonparametric data, and subsequently analyzed using Mann Whitney U test. 5.5. The two-way pairwise interactions of lncRNA SNP-SNP will be calculated using multivariate logistic regression. Univariate then multivariate survival analyses will be carried out by the log-rank test and the Cox proportional hazards model. 5.6. Pearson's Chi-square analysis or Fisher's exact test will be employed to compare the difference of categorical variables. 5.7. Receiver Operating Characteristics (ROC) curves will be drawn using Medcalc to get the sensitivity and specificity of some markers together with the SNPs. 5.8. Survival curves will be drawn using Kaplan-meier curve. 5.9. Hardy-Weinberg test will be used to assure equilibrium of our study participants with the population or not. 5.10. For all analyses, a two-tailed P value of 0.05 or less will be considered as statistically significant