{"id":38024,"date":"2021-03-30T10:32:03","date_gmt":"2021-03-30T10:32:03","guid":{"rendered":"https:\/\/biomedpharmajournal.org\/?p=38024"},"modified":"2021-04-09T06:36:01","modified_gmt":"2021-04-09T06:36:01","slug":"targeted-hot-spot-sequencing-of-uzbek-lung-cancer-patients","status":"publish","type":"post","link":"https:\/\/biomedpharmajournal.org\/staging\/vol14no1\/targeted-hot-spot-sequencing-of-uzbek-lung-cancer-patients\/","title":{"rendered":"Targeted Hot Spot Sequencing of Uzbek Lung Cancer Patients"},"content":{"rendered":"<p style=\"text-align: justify;\"><b><span lang=\"EN-GB\" style=\"color: black; background: white;\">Introduction<\/span><\/b><\/p>\n<p style=\"text-align: justify;\">Majority of cancer deaths worldwide both in men and women occur as an outcome of lung carcinoma.(1). Non-small cell lung cancer (NSCLC) represents the from 80 to 85% of diagnosed lung cancer cases(2,3). Despite having the same aetiology, types of lung cancer can vary on molecular level: epigenetic changes, protein expression, mutations etc, which are reported as diagnostic markers and can influence the therapy outcome Although platinum based doublet therapy has been used as the standard treatment for late stages for many years, accumulating evidence suggests that lung non small cell lung cancer patients with activated EGFR, KRAS, BRAF and some other genes represent positive outcome, while treated with\u00a0targeted therapy methods.(4,5). Thus, it is important to identify the mutation status of NSCLC patients prior to treatment tactic selection.Advanced stages of lung cancer are\u00a0currently unpreventable.Clinical assays define using molecular subtype, clinical and histological features of cancer as a basis of therapy methods [1]. Large-scale investigations are proving lung cancer heterogeneity and its development into progressive disease [2,\u00a03]\u00a0<span lang=\"EN-GB\">and, paired with the dramatical advancement of therapy methods, illustrate the need for more complex diagnostics in cancer management [<a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC6368740\/#CR4\"><span style=\"color: windowtext; text-decoration: none; text-underline: none;\">4<\/span><\/a>].<\/span><\/p>\n<p style=\"text-align: justify;\">Diagnostics based on next generation sequencing (NGS) are creating an opportunity for researchers and clinicians to identify specific modification occurring in tumor cells. Basically, identifying pathologic transformation on gene and protein level enables clinicians to diagnose oncologic diseases on early stages as well as predict therapy responses more exactly.At the meantime current methods comprise of realtime polymerase chain reaction (PCR) and Sanger sequencing, where each selected region of studied gene in a given sample is studied on separate basis. Sanger sequencing method has yet several challenges to overcome while detecting somatic mutations, associated with cancer development. These\u00a0mutations are detected at low prevalence, due to specific localisations features of the tumor or the variations in mixture rates of normal and tumor tissues in studied samples, therefore,\u00a0require reliable DNA library preparation and highly sensitivemethods for successful detection. To accomplish this, highly sensitive next-generation sequencing, with its\u00a0remarkable throughput, is dramatically entering the clinical testing area. However to date, limited use of this method in clinical diagnostics is observed[5]. Primary lung, colon, pancreatic and other cancers were shown to be conveniently detected by theAmpliSeq Cancer Hotspot Panel [7],<\/p>\n<p style=\"text-align: justify;\"><strong>Materials and methods<\/strong><\/p>\n<p style=\"text-align: justify;\"><strong>Subjects<\/strong><\/p>\n<p style=\"text-align: justify;\">The subjects were recruited from people, undergoing treatment in the Department of Thoracic surgery National Cancer Center of Uzbekistan. 20 people were asked to participate and 12\u00a0accepted. Subjects with the history of small cell carcinoma and tuberculosis were excluded from the study. Finally, the baseline data of 10 Uzbek adults(7 males and 3 females), 38-66\u00a0years of age were analyzed in this study. Written informed consent in a form approved by the Ethics Committee under the Ministry of Health of the Republic of Uzbekistan was obtained\u00a0from all subjects for participation in the current study. Geno typing and data analyses were performed according to lab protocols approved by the same Ethics Committee. Patients with\u00a0histologically confirmed lung adenocarcinomas and squamous cell carcinoma of different stages were eligible for enrolment in his study.All patients provided clinic-pathological as\u00a0well as demographic data, including age at diagnosis, gender, nationality, profession, workplace, place of birth,concomitant diseases history, tumor stage, prior therapy, family\u00a0history. Formalin fixed paraffin embedded tumor tissue specimens, previously studied for adequacy via histopathological assessment were included in this study.<\/p>\n<p style=\"text-align: justify;\"><strong>DNA extraction<\/strong><\/p>\n<p style=\"text-align: justify;\">Tumor cells from archive FFPE tissue samples were initially micro dissected manually. DNA from10 FFPE tissue slides was extracted according to Relia Prep\u2122 FFPE gDNA Mini prep\u00a0System Promega protocol at the laboratory of Biotechnology Centre for advanced Technologies under the Ministry of Innovative development of the Republic of Uzbekistan.\u00a0Assessment of DNA quality and quantity was conducted using a Shimadzu BioSpec-nano Micro-volume UV-Vis Spectrophotometer (Japan) and Qubit dsDNA HS Assay Kit and a\u00a0Qubit 2.0 fluorometer. All DNA samples were aliquoted and stored at\u221220 \u00b0C until analysis.<\/p>\n<p style=\"text-align: justify;\"><strong>Library Preparation and Quality Control <\/strong><\/p>\n<p style=\"text-align: justify;\">Illumina AmpliSeqCancer Hotspot Panel v2,containing probes to generate 207 amplicons from 50genes, associated with cancer,to identify around 2800 mutations in hotspot regions\u00a0was used to prepare sequencing amplicon libraries. The amplicons of target regions were generated using 207 oligonucleotide pairs, during thermocycling in GeneAmp\u00ae PCR-amplifier Verity AB. Further target amplicons were partially digested to form and phosphorylate sticky ends to facilitate bar-coded adapter ligation. The amplicons were\u00a0flanked with index sequences, during multiplex PCR to create unique index combinations for dual index sequencing. After library clean-up, quality of library was assessed on a Qubit dsDNA HS Assay Kit and a Qubit 2.0 fluorometer. Afterwards, libraries were reamplified to\u00a0ensure required quantity for Illumina sequencing with further two round clean-up. In order to provide optimum cluster density on the flow cell the library was checked on Qubit 2.0 fluorometer, normalized, diluted to 2.8ng\/\u03bcl, before pooling equal volumes for final\u00a0sequencing library generation, after which libraries were quantified and diluted to starting concentration. MiSeq instrument was used for pooled library sequencing applying a 2 150 paired-end sequencing design<\/p>\n<p style=\"text-align: justify;\"><strong>Data analysis<\/strong><\/p>\n<p>Raw data was processed in FASTQ Generation Version: 1.0.0 within Base Space to generate fastq file. The IGV16 (Broad Institute, Cambridge, Massachusetts) was applied to align paired-end fastq format raw reads to the hg19 reference genomeand produce VCF files. Illumina Variant Studio version 1.0 (Illumina) vs Annovar were used for variants annotation.<\/p>\n<p>Variant effect predictor(VEP) on ENSEMBLE and CRAVAT version 4.3 (http:\/\/hg19.cravat.us\/CRAVAT\/)\u00a0 was implemented for identification of variants from aligned reads. Variants representing a global minor allele frequency more than 0.1% were\u00a0excluded from further studies, being considered as common SNPs as well as non-coding variants.<\/p>\n<p style=\"text-align: justify;\"><strong>Results<\/strong><\/p>\n<p style=\"text-align: justify;\">Molecular-genetic analysis was finalised, and reports formed in 30 days, after receiving agreement consent from patients to be enrolled in this study.Variant Effect Predictor was used to perform annotation, by classifying variants into 8 various classes (\u201cFrame Shift\u00a0Insertion\u201d, \u201cMissense Mutation\u201d, \u201cFrame Shift Deletion\u201d,\u201cIn Frame Insertion\u201d, \u201cIn Frame Deletion\u201d, \u201cNonsense Mutation\u201dand\u201cSplice Site\u201d). Variants having allele frequency less than 0.05% and SIFT score &lt;0.05 (Deleterious) were retained.\u00a0All patients, included in the study\u00a0had mutations in genes, responsible explicitly or implicitly for carcinogenesis and drug sensitivity and involved in Hot Spot Cancer v2 panel. Overall mutations in 18 genes, 11 of which were reported as oncogenes and 7 as tumor suppressor genes were identified.All the\u00a0mutations identified except 5 appeared to be initiating aminoacid change in coded proteins.<\/p>\n<p style=\"text-align: justify;\">Hot-spot mutationswere identified in below mentioned genes during data analysis:\u00a0ALK, APC, BRAF, ERBB4, EGFR, FGFR1, FBXW7, HRAS, FGFR3, KIT, KDR, MET, PDGFRA, PTEN, RET, SMAD4, SMARCB1, TP53, illustrated in COSMIC database.<\/p>\n<table style=\"width: 70%;\" border=\"1\" cellpadding=\"5\">\n<tbody>\n<tr>\n<td><a href=\"https:\/\/biomedpharmajournal.org\/wp-content\/uploads\/2021\/03\/Vol14No1_Tar_Mir_fig1.jpg\"><img decoding=\"async\" class=\"alignnone size-thumbnail wp-image-38032\" src=\"https:\/\/biomedpharmajournal.org\/wp-content\/uploads\/2021\/03\/Vol14No1_Tar_Mir_fig1-150x150.jpg\" alt=\"Vol14No1_Tar_Mir_fig1\" width=\"150\" height=\"150\" srcset=\"https:\/\/biomedpharmajournal.org\/staging\/wp-content\/uploads\/2021\/03\/Vol14No1_Tar_Mir_fig1-150x150.jpg 150w, https:\/\/biomedpharmajournal.org\/staging\/wp-content\/uploads\/2021\/03\/Vol14No1_Tar_Mir_fig1-256x256.jpg 256w, https:\/\/biomedpharmajournal.org\/staging\/wp-content\/uploads\/2021\/03\/Vol14No1_Tar_Mir_fig1.jpg 378w\" sizes=\"(max-width: 150px) 100vw, 150px\" \/><\/a><\/td>\n<td><strong>Figure 1: Illustration of genes with hot spot mutations in Uzbek NSCLC patients.<\/strong><\/p>\n<p><a href=\"https:\/\/biomedpharmajournal.org\/wp-content\/uploads\/2021\/03\/Vol14No1_Tar_Mir_fig1.jpg\" target=\"_blank\">Click here to view figure<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify;\">Identified SNPs population minor allele frequency range was from 0,06% to 0,95% according to the 1000 Genomes database.<\/p>\n<p style=\"text-align: justify;\"><strong>Table 1: Single-Nucleotide Polymorphisms \u00a0inAmpliSeq Cancer Hotspot Panel with MAF greater than or equal to 0.05%.<\/strong><\/p>\n<table style=\"width: 95%;\" border=\"1\" cellspacing=\"0\" cellpadding=\"4\">\n<tbody>\n<tr>\n<td style=\"text-align: center;\"><strong>Gene<\/strong><\/td>\n<td style=\"text-align: center;\"><strong>rs number<\/strong><\/td>\n<td style=\"text-align: center;\"><strong>cDNA change<\/strong><\/td>\n<td style=\"text-align: center;\"><strong>Aminoacid change<\/strong><\/td>\n<td style=\"text-align: center;\"><strong>RefNumber<\/strong><\/td>\n<td style=\"text-align: center;\"><strong>MAF %*<\/strong><\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\"><strong>APC<\/strong><\/td>\n<td style=\"text-align: center;\">rs41115<\/td>\n<td style=\"text-align: center;\">c.4479G&gt;A<\/td>\n<td style=\"text-align: center;\">T1493T<\/td>\n<td style=\"text-align: center;\">NM_000038<\/td>\n<td style=\"text-align: center;\">0.66<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\"><strong>EGFR<\/strong><\/td>\n<td style=\"text-align: center;\">rs1050171<\/td>\n<td style=\"text-align: center;\">c.2361G&gt;A<\/td>\n<td style=\"text-align: center;\">Q787Q<\/td>\n<td style=\"text-align: center;\">NM_005228<\/td>\n<td style=\"text-align: center;\">0.43<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\"><strong>FGFR3<\/strong><\/td>\n<td style=\"text-align: center;\">rs7688609<\/td>\n<td style=\"text-align: center;\">c.1953A&gt;G<\/td>\n<td style=\"text-align: center;\">T653T<\/td>\n<td style=\"text-align: center;\">NM_000142<\/td>\n<td style=\"text-align: center;\">0.95<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\"><strong>HRAS<\/strong><\/td>\n<td style=\"text-align: center;\">rs12628<\/td>\n<td style=\"text-align: center;\">c.81T&gt;C<\/td>\n<td style=\"text-align: center;\">H27H<\/td>\n<td style=\"text-align: center;\">NM_005343<\/td>\n<td style=\"text-align: center;\">0.29<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\"><strong>KDR<\/strong><\/td>\n<td style=\"text-align: center;\">rs1870377<\/td>\n<td style=\"text-align: center;\">c.1416A&gt;T<\/td>\n<td style=\"text-align: center;\">Q472H<\/td>\n<td style=\"text-align: center;\">NM_002253<\/td>\n<td style=\"text-align: center;\">0.21<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\"><strong>KIT<\/strong><\/td>\n<td style=\"text-align: center;\">rs3822214<\/td>\n<td style=\"text-align: center;\">c.1621A&gt;C<\/td>\n<td style=\"text-align: center;\">M541L<\/td>\n<td style=\"text-align: center;\">NM_000222<\/td>\n<td style=\"text-align: center;\">0.06<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\"><strong>PDGFRA<\/strong><\/td>\n<td style=\"text-align: center;\">rs1873778<\/td>\n<td style=\"text-align: center;\">c.1701A&gt;C<\/td>\n<td style=\"text-align: center;\">P567P<\/td>\n<td style=\"text-align: center;\">NM_006206<\/td>\n<td style=\"text-align: center;\">0.95<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\"><strong>RET<\/strong><\/td>\n<td style=\"text-align: center;\">rs1800861<\/td>\n<td style=\"text-align: center;\">c.2307T&gt;G<\/td>\n<td style=\"text-align: center;\">L769L<\/td>\n<td style=\"text-align: center;\">NM_020975<\/td>\n<td style=\"text-align: center;\">0.71<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center;\"><strong>TP53<\/strong><\/td>\n<td style=\"text-align: center;\">rs1042522<\/td>\n<td style=\"text-align: center;\">c.215C&gt;G<\/td>\n<td style=\"text-align: center;\">P72R<\/td>\n<td style=\"text-align: center;\">NM_000546<\/td>\n<td style=\"text-align: center;\">0.54<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify;\">*Minor allele frequency (MAF) according to the 1000 Genomes database<\/p>\n<p style=\"text-align: justify;\">All participants underwent adjuvant chemotherapy as standard treatmentmethod prior to analysis. Mutations in PDGFRA, FGFR3, APC, EGFR and TP53genes being the most frequently were revealed in 70% of studied samples. According to ClinVar database rs7688609 in FGFR3 gene was associated with Crouzon syndrome with acanthosis nigricans, rs1873778 in PDGFRA gene, rs1050171 in EGFR gene and rs1042522 in TP53gene were associated with Idiopathic hypereosinophilic syndrome, Lung cancer and Glioma\u00a0susceptibility respectively. The second and third most common mutations with 50% and 60% were reported to bemissense variants rs3822214 and rs1870377 in KIT and KDR genes respectively, associated with Gastrointestinal stromal tumor and Hemangioma, capillary infantile. Synonymous variants in rs1800861 in \u00a0RET and rs12628 in HRAS genes, giving\u00a0association with Congenital central hypoventilation and Epidermal nevus syndrome respectively came fourth with the index of 40%. Worth noting that each participant of this study had at least one variant, associated with lung cancer development, in addition, involved in drug metabolism.<\/p>\n<p style=\"text-align: justify;\"><strong>Discussion<\/strong><\/p>\n<p style=\"text-align: justify;\">Lung cancer is multi factorial disease, occurring in majority cases because of genetic translocations in organism. Each type of lung cancer has specific treatment methods, based on histological subtype, stage, aetiology. Over the past decade, targeted therapy of lung\u00a0cancer has become one of the standard methods of treatment for non-small cell lung cancer. Mutational spectra identified during the research was found to be potential targets in the implementation of targeted therapy.Validation of identified EGFR mutations was conducted\u00a0by classic mutant enriched PCR method, showing 96% concordance, proving trustfulness of Hot Spot Cancer Sequencing results.Study of c.2361A&gt;G mutation in patients with colorectal, breast and lung cancer revealed better clinical outcome after anti-EGFR\u00a0treatment[3].The frequency of missense mutation in EGFR genec.2361A&gt;G, leading glycine to histidine change in amino acid strain of coded protein, was rather high than reported in other studies, researching European (4,9-15%)[2,6,7,12,15]and Asianlung cancer\u00a0patients(3,8-49,1%), however no correlation was identified between the mutation status and patients&#8217; characteristics of age, gender, smoking history[16, 17].Although, several studies were conducted showing the role of exon 20 EGFR mutation in chemotherapy response, it\u00a0wasn\u2019t included in PharmGKB database up to date.CC geno type in rs1042522 of TP53 gene was reported as one of the risk factors, leading to lung cancer development in Bangladeshi population[4]. According to Pharm GKB, rs1042522 is associated with decreased response to\u00a0capecitabine and paclitaxel, in patients with stomach neoplasms, while patients with ovarian neoplasms, carrying this mutation, suffered from more severe form of Neutropenia while being treated with cyclophosphamide and cisplatin. According to 1000Genomes, studies\u00a0conducted in aggregated populations showed the frequency of TP53 mutations from 30 to 68%[9]. In our study the frequency of TP53 mutation was higher than reported elsewhere, although further studies are yet to be conducted. Regarding the study of rs1873778 in\u00a0PDGFRA gene and rs7688609 in FGFR3, which was present in 70% of studied samples, association with cervical adenosquamous carcinoma and colorectal cancer to add withafatinib resistance in non-small cell lung cancer patients was reported[1]. KIT gene mutation\u00a0rs3822214 identified in studied samples was shown to have clinical significance in partial albinism, gastrointestinal stromal tumor, hereditary cancer-predisposing syndrome, mastocytosis, chronic myelogenous leukemia[14]. According to results of multivariate\u00a0analysis, conducted in 163 patients with various types of cancer,major homozygous rs1870377 genotype of KDR had negative effects on both TTF and OS, when compared to the effects of the heterozygous or minor homozygous genotypes, while being treated with sunitinib as an complementary therapy[10], in addition kinase insert domain receptor\u00a0polymorphisms are associated with the increased protein concentration in serum plasma and correlate with an increased risk of stomach, lung and breast neoplasms progression[8,11,13].<\/p>\n<p style=\"text-align: justify;\"><strong>Conclusion<\/strong><\/p>\n<p style=\"text-align: justify;\">In conclusion, particular polymorphisms and mutations affect treatment response and the toxicity level among patients with lung cancer, undergoing chemotherapy. Variety of SNPs were reported to have impact on disease outcomes of those patients therefore, they should be validated in an independent population, prior to being adopted for pre-personalised therapy screening.<\/p>\n<p style=\"text-align: justify;\"><strong>Availability of data and materials<\/strong><\/p>\n<p style=\"text-align: justify;\">The datasets during and\/or analysed during the current study are available from the corresponding author on reasonable request.<\/p>\n<p style=\"text-align: justify;\"><strong>Acknowledgement<\/strong>.<\/p>\n<p style=\"text-align: justify;\">We thank Professor M.TillyashakhovDirector of the Republic Specialized Scientific Practical Medical Centre of Oncology and Radiology and his vice-director Professor A.A. Yusupbekov and the staff of the departments of Thoracic surgery and Pathomorphology for clinical data and sample collection support and D. Dalimova the head of the laboratory of Biotechnology Centre for Advanced Technologies under the Ministry of Innovative Development of the Republic of Uzbekistan and the staff of the laboratory for practical support in organizing the initial sample preparation works. Authors are grateful to the Ministry of Innovative Development of the Republic of Uzbekistan for providing funding opportunity to conduct this research.<\/p>\n<p style=\"text-align: justify;\"><strong>Conflict of interest<\/strong><\/p>\n<p style=\"text-align: justify;\">Authors of the manuscript Mirakbarova Z and TurdikulovaSh don\u2019t have a potential conflict of interest to declare.<br \/>\nThe funders of current research had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript and have no potential conflict of interest to declare.<\/p>\n<p style=\"text-align: justify;\"><strong>Funding Source <\/strong><\/p>\n<p style=\"text-align: justify;\">This research was supported by Scientific Research Projects PZ-2014-0915210258 and MU-PZ-20171025473, funded by the Ministry of Innovative Development of the Republic of Uzbekistan. 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