RESUMO
PURPOSE: To describe the surgical technique and methodology to successfully plan and execute an endoscopic foraminotomy in patients with isthmic or degenerative spondylolisthesis, according to each patient's unique characteristics. METHODS: Thirty patients with degenerative or isthmic spondylolisthesis (SL) with radicular symptoms were included from March 2019 to September 2022. Treating physician registered patients' baseline and imaging characteristics, as well as preoperative back pain VAS, leg pain VAS and ODI. Subsequently, authors treated the included patients with an endoscopic foraminotomy according to a "patient-specific" tailored approach. RESULTS: Nineteen patients (63.33%) had isthmic SL and 11 patients (36.67%) had degenerative SL. 75.86% of the cases had a Meyerding Grade 1 listhesis. One of the transforaminal foraminotomies with lateral recess decompression in degenerative SL had to be aborted because of intense osseous bleeding. Of the remaining 29 patients, one patient experienced recurrence of the sciatica pain that required subsequent reintervention and fusion. No other intraoperative or post-operative complications were observed. None of the patients developed post-operative dysesthesia. In 86.67% of the patients, the foraminotomy was implemented using a transforaminal approach. In the remaining 13.33% of the cases, an interlaminar contralateral approach was used. Lateral recess decompression was performed in half of the cases. Mean follow-up time was 12.69 months, reaching a maximum of 40 months in some patients. Outcome variables such as VAS for leg and back pain, as well as ODI, showed statistically significant reduction since the 3-month follow-up visit. CONCLUSION: In the presented case series, endoscopic foraminotomy achieved satisfactory outcomes without sacrificing segmental stability. The proposed patient-specific "tailored" approach allowed to successfully design and execute the surgical strategy to perform an endoscopic foraminotomy through transforaminal or interlaminar contralateral approaches.
Assuntos
Foraminotomia , Ciática , Fusão Vertebral , Espondilolistese , Humanos , Foraminotomia/métodos , Espondilolistese/diagnóstico por imagem , Espondilolistese/cirurgia , Espondilolistese/complicações , Endoscopia/métodos , Dor nas Costas/etiologia , Ciática/etiologia , Resultado do Tratamento , Vértebras Lombares/diagnóstico por imagem , Vértebras Lombares/cirurgia , Estudos Retrospectivos , Fusão Vertebral/métodosRESUMO
Temozolomide (TMZ) is an alkylating chemotherapeutic agent widely used in anti-glioma treatment. However, acquired TMZ resistance represents a major clinical challenge that leads to tumor relapse or progress. This study investigated the genomic profiles including long non-coding RNA (lncRNA) and mRNA expression associated with acquired TMZ resistance in glioblastoma (GBM) cells in vitro. The TMZ-resistant (TR) of GBM sub-cell lines were established through repetitive exposure to increasing TMZ concentrations in vitro. The differentially expressed lncRNAs and mRNAs between the parental U87 and U87TR cells were detected by human lncRNA microarray method. In this study, we identified 2,692 distinct lncRNAs demonstrating >2-fold differential expression with 1,383 lncRNAs upregulated and 1,309 lncRNAs downregulated. Moreover, 4,886 differential mRNAs displayed 2,933 mRNAs upregulated and 1,953 mRNAs downregulated. Further lncRNA classification and subgroup analysis revealed the potential functions of the lncRNA-mRNA relationship associated with the acquired TMZ resistance. Gene ontology and pathway analysis on mRNAs showed significant biological regulatory genes and pathways involved in acquired TMZ resistance. Moreover, we found the ECMreceptor interaction pathway was significantly downregulated and ECM related collagen Ι, fibronectin, laminin and CD44 were closely associated with the TR phenotype in vitro. Our findings indicate that the dysregulated lncRNAs and mRNAs identified in this work may provide novel targets for overcoming acquired TMZ resistance in GBM chemotherapy.