?Background: Chronic infection by HPV is associated with the development of virtually all cases of cervical cancer. There are more than 450 HPV types characterized, with types 16 and 18 being the most common, responsible for 70% of cervical cancer cases. Viral infections can induce mechanisms of innate immunity, such as APOBEC enzymes. Although APOBEC enzymes can act as a restriction factor for HPV, they can also induce mutations on the host genome, and mutational signatures characteristic of these enzymes have been found in multiple cancer types, such as cervical tumor samples. Objectives: The current study aims to explore the mutational profiles in the genomic DNA of cervical cancer cells infected by different HPV types. Methods: Two cohorts are being analyzed in this study, one composed by 47 samples from patients from the Brazilian National Cancer Institute (INCA) and another from the TCGA-CESC cohort (n=163) exome and clinical data. The Sarek (nf-core) pipeline was applied for functional annotation of mutations of INCA's patients. Mutational signatures were extracted using the SigProfileMatrixGenerator and SigProfileExtractor packages and results compared statistically for each type of HPV-infected tumors and clinical information. Results: The mutational profile from the TCGA-CESC cohort generated three de novo signatures, later decomposed for the COSMIC signatures. Among those, a contribution of SBS1, SBS5, (clock-like signature) SBS10a, SBS15 (related to defective DNA mismatch repair processes) and both APOBEC signatures, SBS2 and SBS13, was observed. Samples were grouped by hierarchical clusterization in six distinct groups, composed by distinct frequency of signatures, defined as COSMIC Signature Profiles (CSPs A-F). The difference in the distribution of CSPs between Alphapapillomavirus 7 (contains HPV18) and Alphapapillomavirus 9 (contains HPV16) HPV species adjusted by tumor staging and age of patients assessed by a multinomial logistic regression model had a marginal p-value (p=0.053) between the CSPs A and E. The analysis regarding INCA’s samples revealed a similar signature profile representing a distinct profile from the exome data (TCGA) but with distinct frequencies, being the clock-like mutations SBS1 and SBS5 the two most frequent signatures, followed by APOBEC-associated signatures. Nonetheless, two signatures associated with defective DNA mismatch repair (SBS3 and SBS20), were also found in INCA patients. For signatures regarding the exonic regions of INCA patients, most of the samples analyzed so far (20/25) clusterized closely to the CSP that contained higher frequency of clock-like signatures SBS1 and SBS5, grouped in an almost exclusive cluster of INCA patients’ samples. Conclusions: The exome and whole-genome profiles of mutational signatures in cervical cancer differs between the cohorts in frequency, but they share similar signatures and biological tumorigenic processes. Further analyses are being performed to correlate signatures and other clinical variables. This is the first assessment of genome-wide mutational profiles of cervical cancer cases from Brazil, a country with large number of those cancers. Additional analyses will be conducted with Dr. Paul Brennan from IARC, and will include a short-term training of the first author in his group / branch.