Tumor Mutational Burden in Cervical Cancer as Potential Marker for Immunotherapy Responders

<b>Background/Objectives</b>: Tumor mutational burden (TMB) has emerged as a potential biomarker of response to immunotherapy across multiple solid tumors. However, its role in cervical cancer remains insufficiently defined. This study aimed to evaluate the genomic landscape and TMB profile in a cohort of patients with cervical cancer treated at a tertiary gynecologic oncology center, with a focus on TMB's associations with clinical features, HPV infection, and treatment modalities. <b>Methods</b>: A total of 61 patients diagnosed with cervical cancer (82.0% ca. planoepitheliale, 18.0% adenocarcinoma) were retrospectively analyzed. Tumor samples were collected during primary surgery, biopsy, or conization and subjected to targeted next-generation sequencing using the ONCOaccuPanel™ and BRCAaccuTest PLUS™ (NGeneBio). TMB was calculated as non-synonymous mutations per megabase and analyzed using NGeneAnalySys^® software. Variant classification followed ACMG guidelines. Comparative analyses were conducted between TMB-high (≥10 mut/Mb) and TMB-low subgroups, and correlations with clinical and molecular variables were assessed using univariable statistics. <b>Results</b>: High TMB was identified in 36 patients (59.0%), while microsatellite instability was found in only 2 cases (3.3%). No significant associations were observed between TMB status and FIGO stage, histologic subtype, or HPV 16/18 infection. However, higher TMB values were observed in patients with nodal involvement, diabetes, and HPV52 infection. A diverse spectrum of mutations was detected, with PIK3CA and ARID1A being most frequently altered. Several variants of uncertain significance were identified in genes not classically associated with cervical cancer. <b>Conclusions</b>: TMB-high status is relatively frequent in cervical cancer and appears to be independent of FIGO stage or histological subtype. While not predictive of clinical stage, TMB correlates with specific molecular and comorbidity profiles, suggesting its potential relevance for future patient stratification in immunotherapy trials.