Purpose Cervical cancer is one of the most common causes of cancer mortality for women living in poverty, causing over 28,000 deaths annually in Latin America and 266,000 worldwide. To better understand the molecular basis of the disease we ascertained blood and tumor samples from Guatemala and Venezuela and performed genomic characterization. Experimental Design We performed HPV typing and identified somatically mutated genes using exome and ultra-deep targeted sequencing with confirmation in samples from Mexico. Copy number changes were also assessed in the exome sequence. Results Cervical cancer cases in Guatemala and Venezuela have an average age-of-diagnosis of 50 years, and 5.6 children. Analysis of 675 tumors revealed activation of PIK3CA and other phosphatidyl inositol (PI3K)/AKT pathway genes in 31% of squamous carcinomas and 24% of adeno- and adenosquamous tumors, predominantly at two sites (E542K, E545K) in the helical domain of the PIK3CA gene. This distribution of PIK3CA mutations is distinct from most other cancer types, and does not result in the in vitro phosphorylation of AKT. Somatic mutations were more frequent in squamous carcinomas diagnosed after age 50. Frequent gain of chromosome 3q was found and low PIK3CA mutation fractions in many tumors suggest that PI3K mutation can be a late event in tumor progression. Conclusions PI3K pathway mutation is important to cervical carcinogenesis in Latin America. Therapeutic agents that directly target PI3K could play a role in the therapy of this common malignancy.

BackgroundA low cost and accurate method for detecting high-risk (HR) human papillomavirus (HPV) is important to permit HPV testing for cervical cancer prevention. We used a commercially available HPV method (H13, Hybribio) which was documented to function accurately in a reduced volume of cervical specimen to determine the most prevalent HPV types and the distribution of HPV infections in over 1795 cancer-free women in Guatemala undergoing primary screening for cervical cancer by cytology.MethodsHR-HPV detection was attempted in cervical samples from 1795 cancer-free women receiving Pap smears using the Hybribio™ real-time PCR assay of 13 HR types. The test includes a globin gene internal control. HPV positive samples were sequenced to determine viral type. Age-specific prevalence of HPV was also assessed in the study population.ResultsA total of 13% (226/1717) of women tested HPV+, with 78 samples (4.3%) failing to amplify the internal control. The highest prevalence was found in younger women (< 30 years, 22%) and older ones (≥60 years, 15%). The six most common HR-HPV types among the 148 HPV+ typed were HPV16 (22%), HPV18 (11%), HPV39 (11%), HPV58 (10%), HPV52 (8%), and HPV45 (8%).ConclusionsIn this sample of cancer free women in Guatemala, HPV16 was the most prevalent HR type in Guatemala and the age-specific prevalence curve peaked in younger ages. Women in the 30-59-year age groups had a prevalence of HR-HPV of 8%, however, larger studies to better describe the epidemiology of HPV in Guatemala are needed.Electronic supplementary materialThe online version of this article (10.1186/s12885-018-4438-y) contains supplementary material, which is available to authorized users.

Background: A low cost and accurate method for detecting high-risk (HR) human papilloma

<p>Supplementary Tables 1-6. Supplemental Table 1. Primers used in Ion Torrent sequencing of HPV. Supplemental Table 2. Predicted somatic mutations in PIK3CA discovered by targeted sequencing of cervical tumors from Mexico, Venezuela, and Guatemala. Supplementary Table 3. Predicted somatic mutations in 5 candidate genes discovered by targeted sequencing of cervical tumors. Supplementary Table 4. Association of HPV type and PIK3CA mutation. Supplementary Table 5. PIK3CA mutations in histologic subtype in this and other published studies Supplementary Table 6. Fig.3A_B_C raw data</p>

<p>Supplementary Figures 1-11. Supplementary Figure 1. Sample and analyses diagram. Supplementary Figure 2. Aggregate mutation spectrum of Guatemalan cervical tumors. Supplementary Figure 3. Highly amplified regions of chromosome (Chr.) 2, 6 and 10 in tumor A4. Supplementary Figure 4. Chromosome breakpoints in cervical tumors. Supplementary Figure 5. PIK3CA mutation and pathology. Supplementary Figure 6. Co-occurring mutations in the PIK3CA and PTEN genes. Supplementary Figure 7. Sanger sequence concordance of mutant read percentage. Supplementary Figure 8. Mutation Fraction of PIK3CA mutations. Supplementary Figure 9. Age range associations with PIK3CA mutation and HPV type. Supplementary Figure 10. PIK3CA and HPV E6 and E7 mRNA expression. Supplementary Figure 11. Model of cervical cancer progression.</p>