Genome Analysis of Latin American Cervical Cancer: Frequent Activation of the PIK3CA Pathway

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Genome Analysis of Latin American Cervical Cancer: Frequent Activation of the PIK3CA Pathway

Hong Lou1*, Guillermo Villagran2*, Joseph F. Boland3*, Kate M. Im4*, Sarita Polo2, Weiyin

Zhou3, Ushie Odey5, Eligia Juárez-Torres6, 7, Ingrid Medina-Martínez6, 7, Edgar Roman-

Basaure7, Jason Mitchell3, David Roberson3, Julie Sawitzke1, Lisa Garland1, Maria Rodríguez-

Herrera4, David Wells1, Jennifer Troyer1, Francisco Castillo Pinto2, Sara Bass3, Xijun Zhang3,

Miriam Castillo2, Bert Gold4, Hesler Morales2, Meredith Yeager3, Jaime Berumen6, 7, Enrique

Alvirez5, Eduardo Gharzouzi2, Michael Dean4#

1Basic Science Program, Leidos Biomedical Research, Inc., Frederick, MD USA

2Instituto de Cancerologia, Guatemala City, Guatemala

3Cancer Genetics Research Laboratory, Division of Cancer Epidemiology and Genetics, Leidos

Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Gaithersburg,

MD USA

4Laboratory of Experimental Immunology, National Cancer Institute, Frederick, MD USA

5Hospital Central Universitario “Dr. Antonio M Pineda”, Barquisimeto, Lara State, Venezuela

6Unidad de Medicina Genómica, Facultad de Medicina, Universidad Nacional Autónoma de México, México, D.F. México

7Hospital General de México. México, D.F. México

*Contributed equally

#Correspondence to: Michael Dean, PhD, Building 560, Room 21-89b, Laboratory of Experimental Immunology, National Cancer Institute, Frederick, MD 21702 USA. Tel: 301-846-5931, FAX: 301-846-7042 (email: [email protected])

Running Title: Activation of PIK3CA in Latin American cervical cancer

Key Words: cervical cancer, Latin America, PIK3CA, human papilloma virus

The authors have no conflicts of interest to report.

Research. on August 14, 2015. © 2015 American Association for Cancerclincancerres.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on June 16, 2015; DOI: 10.1158/1078-0432.CCR-14-1837

http://clincancerres.aacrjournals.org/

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Statement of translational relevance: Cervical cancer is one of the most common cancers in

women worldwide with over 80% of deaths occurring in women living in poverty. Although pre-

cancerous lesions and local malignancy is curable, invasive and/or metastatic tumors have poor

survival. In invasive tumors from three Latin American countries we identify common activation

of the phosphotidyl-inositol 3 (PI3K) kinase pathway. Up to 33% of tumors have mutations in

the PIK3CA gene, predominantly at two specific helical domain sites, E542K and E545K, and

rarely in the kinase domain. The PI3K pathway can signal through the AKT1 and MTOR serine-

threonine kinases, however PIK3CA helical mutations may activate alternative pathway(s). Our

data are relevant to the development and application of therapeutic strategies for invasive

cervical tumors.




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Abstract

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.




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Introduction

Human papilloma virus (HPV) causes >90% of cervical cancer (CC), one of the most

common malignancies in women worldwide (1-3). While 70-90% of infections are cleared by the

immune system, persistent HPV infections can lead to high-grade cervical intraepithelial

neoplasia and cervical cancer (4). HPV replicates episomally but can integrate; integration is

more frequent in late stage lesions and cancer and is associated with genome alteration and

instability (5, 6). The viral E6 and E7 oncoproteins inhibit both TP53 and RB1 proteins altering

cell cycle control, apoptosis and DNA repair.

The HPV16 and HPV18 types are the most oncogenic and account for 60-70% of cervical

cancers, however at least 12 other high risk types can also be found in cervical tumors (7-9).

HPV is both highly prevalent and highly infectious, being transmitted through multiple forms of

sexual contact, and most males and females acquire one or more infections in their lifetime. Due

to the long latency of development of cervical cancer, typically 10-15 years, there is opportunity

to identify pre-cancers and eliminate them before the appearance of invasive cancer (4). The use

of the Papanicolaou (Pap) test has reduced cervical cancer mortality by up to 80% in countries

that have employed screening (3). However, women living in poverty, with inadequate health

care, receive either no screening or poorly controlled screening and nearly 90% of cervical

cancer mortality occurs in low and middle income countries (LMIC), and within minority

populations in higher income countries (3, 10).

Many Latin American countries have high incidence and mortality from cervical cancer

(8,414 deaths annually in Brazil; 4,769 in Mexico and 27,000 in the region overall

[http://globocan.iarc.fr]). Several Latin American countries have large minority and/or

indigenous populations that through poverty, discrimination, rural isolation and/or language




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barriers suffer from health disparities. Indigenous populations in Guatemala comprise 40% of the

inhabitants and speak over 20 languages, Mexico has 75 indigenous groups and Venezuela has

40 recognized indigenous peoples.

Until recently molecular genetic studies of cervical tumors have been limited to candidate

gene tests, and studies of cell lines such as HeLa (11). Because the E6 protein of high risk types

causes the degradation of TP53, cervical tumors are one of the few cancers with a low level of

mutation in the TP53 gene (12). The highly pathogenic HPV16 and HPV18 types can

immortalize many cell types but additional lesions are required for transformation (13). The

PIK3CA gene and pathway has also been shown to be frequently mutated (14) with a 31%

mutation frequency in US cervical tumors. PIK3CA encodes an enzyme converting the signaling

molecule phospho-inositol phosphate 2 (PIP2) to PIP3. This molecule can induce the

phosphorylation of AKT , a central signaling kinase for many receptor tyrosine kinases. The

PTEN protein converts PIP3 back to PIP2 and is a tumor suppressor gene. PIK3CA is one of the

most frequently genes mutated in cancer, with most mutations occurring in the kinase domain

and resulting in constitutive activation. The helical domain of PIK3CA is also frequently mutated

at residues E542 and E545 and this domain is thought to mediate interactions with an inhibitory

subunit, and may signal through other kinases such as SGK3 (15, 16).

Genome sequencing of cervical tumors with viral integration revealed wide-spread

genome rearrangement and specific sites of integration (17). A comprehensive study of 100

Norwegian and 15 Mexican tumors with genome, exome, and RNA-seq analyses; identified

frequent driver genes, common chromosomal alterations and integration sites (18). A genome




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sequencing study of HPV integration in Chinese cervical tumors revealed diverse integration

sites and a study of 15 cervical adenocarcinomas from Hong Kong identified frequently mutated

genes (19, 20). To further understand the molecular basis of cervical cancer in high incidence

countries we undertook an analysis of cervical cancers in Guatemala and Venezuela with

validation from a cohort from Mexico to identify frequently mutated genes and correlate

mutations with histological type, HPV type and age of cervical cancer onset.




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Materials and Methods

Sample collection

Samples were obtained under Institutional Review Board (IRB) approval with informed

consent, a standardized questionnaire on socio-demographic characteristics, reproductive and

contraceptive history, smoking and Pap smear history. Protocols were approved by the Ethical

Review Committees in Guatemala, Venezuela, and Mexico and the Office of Human Research

Subjects, NIH. Subjects from Guatemala (296 FIGO stage I-IV cancers) and Venezuela (39 with

FIGO Stage I-IV, and 38 CIN 1-3) were collected from 2011-2013 and from Mexico from 2003-

2007. All patients were referred for suspected invasive cervical cancer, all consenting patients

were included, and only pregnant subjects and cancer-free women were excluded. Subjects from

Venezuela included subjects with a positive Pap smear and biopsy (CIN 1-CIN 3). Surgically

resected cervical tumors tissues were stored in RNAlater (QIAGEN) at -20° C until extraction

(Supplementary Fig. 1).

DNA and RNA extraction and HPV genotyping

DNA and RNA was extracted from the cervical cancer tissues (5-10 mg) using the

AllPrep DNA/RNA Micro Kit (QIAGEN) as described by the manufacturer. For HPV type

determination, DNA samples were amplified by PCR using Broad-Spectrum GP5+ (BSGP5+)

forward primers with inosine at selected sites, and GP6+ reverse primers along with the β-globin

MS3/MS10 primers (226 bp) as a control for DNA quality (21). Four hundred nanomolar of each

forward primer were used with ZymoTaq PreMix (Zymo Research). A 10-min denaturation step

(95° C) was followed by 40 cycles of amplification (Perkin-Elmer thermocycler). Each cycle




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was 94° C for 20 s, 38° C for 30 s, and 71° C for 80 s, and final elongation for 5 min. Ramping

rates for the Mastercycler were; 1.8°C/s from 94° C to 38° C, 2.0°C/s from 38° C to 71° C, and

2.8° C/s from 71° C to 94° C. Each PCR experiment included HeLa DNA as positive and

HEK293 and / or C-33A as negative controls, and sample lacking template DNA. Positive

samples by gel electrophoresis were sequenced on an ABI 3730XL and analyzed by assembly

and trimming in SeqMan (DNASTAR) followed by BLAST search (NCBI).

NextGen sequencing of HPV

To resolve multiple types on the Ion Torrent PGM, the BSGP6+ primers were tailed with

Ion Express barcodes and Ion Torrent A adapter and BSGP5+ primers tailed with the P1 adapter

(Supplementary Table S1). β-globin MS3/MS10 primers were included in the reaction to control

for amplification, without sequencing adapters or barcodes When samples were PCR negative

for HPV, but amplified for β-globin (by gel electrophoresis), a second PCR reaction was

performed using 2X DNA input material . Positive PCR products were quantitated on the

Caliper GX, normalized and pooled for sequencing on the Ion Torrent PGM as per

manufacturer’s instructions. Briefly, normalized, pooled libraries were amplified via emulsion

PCR using the One Touch v2, enriched on the ES2, and sequenced for 520 cycles on the PGM.

An average of 8000 reads was obtained for each sample.

There was an 83% concordance between the PCR and next-generation (NG) sequencing

methods (including both HPV+ and HPV- samples), and another 6% of samples had mixed HPV

infection by NG with Sanger sequencing detecting one of the types. A total of 8% of samples had

abundant reads of more than one HPV type by NG sequencing.




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Exome sequencing

DNA preparation

A 1 µg aliquot of high molecular weight DNA (determined by Picogreen,Invitrogen) was

used in TargetSeq exome v2 capture process with enzymatic shearing (Ion Shear Plus Reagents

Kit, Life Technologies) to a target size range of 135–165 bp.

Library preparation for TargetSeq exome capture

Sheared genomic DNA followed the TargetSeq protocol for ligation, nick repair,

purification, size selection and final amplification. For the ligation and nick repair, a master mix

consisting of 10 µL 10x Ligase Buffer, 10 µL A and P1 adapters, 2 µL dNTP mix, 41 µL

nuclease free water, 4 µL DNA ligase and 8 µL nick repair polymerase. PCR conditions were as

follows: 25° C for 15 min, 98° C for 20 min. and a hold at 4° C. The amplified material was

cleaned with Ampure XP reagent (Agencourt) according to the TargetSeq v2 protocol, with

DNA elution in 20 µL of Low TE. Amplified sample libraries were size selected (Pippen Prep

instrument, Sage Science) and processed according to the TargetSeq protocol. The Pippen Prep

was set to elute ‘‘Tight’’ at 220 bp. The eluted size selected samples were cleaned with Ampure

XP reagent according to the TargetSeq v2 protocol, and DNA eluted in 30 µL of Low TE. The

final amplification of the size selected fragment libraries was performed using a master mix

consisting of 200 µL Platinum PCR Supermix High Fidelity and 20 µL Library Amplification

Primer Mix. PCR cycling conditions were: 95° C for 5 min, and 8 cycles of 95° C for 15s, 58° C

for 15s, 70° C for 1 min. The amplified samples were purified with Ampure XP reagent

according to the TargetSeq v2 protocol, with elution in 50 µL of Low TE, and assessment on the

Agilent Bioanalyzer (Agilent Technologies).




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TargetSeq exome capture

An aliquot of 500 ng of each size selected sample fragment library was used in the

TargetSeq Exome enrichment step with 5 µL 1 mg/mL Human Cot-1 DNA, 500 ng of sample, 5

µL each of Ion TargetSeq Blocker P1 and A. The mix was dried at 60° C for 30 min. To each

sample we added 7.5 µL TargetSeq Hybridization Solution A (29) and 3 µL TargetSeq

Hybridization Enhancer Band incubated for 10 min at 95° C to denature the DNA. The sample

was then transferred to a 0.2 mL tube containing 4.5 uL of the TargetSeq Custom Probe Pool and

incubated at 47 °C for 72 h, the samples were washed and the probe-hybridized DNA was

recovered. After wash and recovery, the samples were eluted in 30 µL of nuclease free water

and amplified according to the TargetSeq protocol. A master mix containing 200 µL Platinum

PCR Supermix High Fidelity and 20 µL Ion TargetSeq Amplification Primer Mix was added to

the 30 µL of TargetSeq capture beads; . PCR cycling conditions were as follows: 95 °C for 5

min, followed by 8 cycles of 95°C for 15s, 58°C for 15s, 70°C for 1min, purified with Ampure

XP reagent according to the TargetSeq v2 protocol, eluted in 25 µL of Low TE, quantitated and

qualitatively assessed on the Agilent Bioanalyzer.

Ampliseq Exome Sequencing

ALiquots of 100ng of genomic DNA from cervical tumor and normal samples were

processed according to the standard protocol for Ampliseq target amplification and library

preparation. Each tumor and normal library were pooled for the template emulsion prep and

sequenced as a pair using the Proton P1 chip and Ion Torrent Proton Sequencer (Thermo Fisher

Scientific). Each run produced over 10 Gb of sequence data and had an average depth of

coverage surpassing 100X. The data was aligned using TMAP




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(https://github.com/iontorrent/TS/tree/master/Analysis/TMAP) and variants were called using

Torrent Suite Variant Caller (TSVC) onboard the Proton Sequencer (Thermo Fisher Scientific).

The data was processed off-line through a custom analysis workflow utilizing the aligned reads

and a dual variant calling process, TSVC and a modified GATK variant caller optimized for

Proton data (22).

Copy number analysis

The CNV analysis was performed using tumor and matched normal sequence. A log

based 2 ratio between tumor and normal was calculated based on the ngCGH algorithm

(https://github.com/seandavi/ngCGH), using the tumor and normal BAM files. Genomic

windows are defined from blocks of 1000 reads in the normal sample and thenthe number of

reads in the tumor is quantified. A ratio is made between the number of reads in the tumor and

the number of reads in the normal. Finally, a log2 transformation is applied to each ratio and the

entire vector of the results is centered by subtracting the median to make the median of the log2

ratios zero.

The log2 ratios were imported to Nexus Copy Number Discovery Edition Version 7.5.

(BioDiscovery, Inc., Hawthorne, CA http://www.biodiscovery.com). The Fast Adaptive States

Segmentation Technique (FASST2) segmentation method (BioDiscovery, Inc.) was used to

make CNV calls. A significance threshold of 1.0E-5 was used to adjust the sensitivity of the

FASST2 segmentation algorithm. A minimum number of 20 amplicons per segment were used

to eliminate small CNVs. Cut offs of 0.2/-0.2 were used for gain/loss; and for high gain/high

loss were set to 0.6/-1.0, and the results tabulated (Supplementary Fig. S4).

Targeted gene sequencing




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A targeted, multiplex PCR primer panel was designed using the custom Ion Ampliseq

Designer v1.2 (Life Technologies). The primer panel covered 12kb of sequence including the

coding region of 8 genes – HRAS, CTNNB1, KRAS, STK11, CDKN2A, PIK3CA, PTEN, and

TP53 (average coverage 99%, average amplicon size 225 bp). Sample DNA (tumor or

tumor/normal pairs) was amplified and libraries prepared following the Ion Ampliseq Library

Preparation protocol (Life Technologies). Individual samples were barcoded, pooled, applied to

chips, and sequenced on the Ion Torrent PGM Sequencer using the Ion PGM Template OT2 200

and Ion PGM Sequencing 200v2 kits. Mean read length after sequencing was 116bp, and 94% of

amplicons gave an average coverage of greater than 50 reads/sample.

Sequence alignment and mutation prediction

Resulting sequence reads were aligned to the human reference genome version hg19

using the TMAP aligner (Life Technologies) and single nucleotide variants (SNVs) were called

using the Genome Analysis Tool Kit (GATK) (22, 23) and the Torrent Variant Caller (TSVC,

Life Technologies) and small insertions and deletions were called using the TSVC. The NIH

Biowulf Cluster was used for additional variant annotation. All mutations in Supplementary

Tables 1 and 2 were manually examined in IGV (24) to confirm an adequate number of mutant

reads in both directions and to eliminate false positives. Selected sites were manually examined

to identify potential false negative predictions. For the E542K and E545K sites, a minimum of

100 reads and 3% mutant reads were necessary to call the sample mutation positive. For a subset

of samples targeted sequencing was performed on both tumor and normal DNA to confirm that

reported mutations were somatic.

PIK3CA Mutation Verification




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Primers for the PIK3CA gene were described (25). The amplification (WGA; QIAGEN)

required 20 ng cervical cancer tumor or normal blood DNA and standard PCR conditions at an

annealing temperature of 63°C 10 cycle and 58°C 30 cycle, respectively. Big Dye v.3.1

chemistry (ABI) sequencing reactions were sequenced on a 3730 Genetic Analyzer (ABI), and

chromatograms examined using Sequencher, v.4.8 (GeneCodes) and Mutation Surveyor

(Softgenetics). Exons 9 and 20 were sequenced in the majority of the Venezuela and Guatemala

tumor samples and selected mutations in other gene regions were also validated.

Quantitative RT-real-time PCR

One microgram of total RNA was reverse transcribed into cDNA using the Transcriptor

First Strand cDNA Synthesis Kit (Roche) with oligonucleotide (dT)18 primer according to the

manufacturer’s instructions. Real time PCR was performed for E6 and E7 HPV transcripts, using

gene and type specific primers, in the presence of SYBR green, in HPV16 and 18 positive

tumors. Relative expression levels of E6 and E7 were multiplied by 1000. The E6 primers detect

the full-length E6/E7 transcript producing principally E6 protein and the E7 primers detect

transcripts expressing E6, E6*1, E6*2 and E7 proteins; (Supplementary Figure 10)(26). For

normalization, the expression of a 144 bp β-actin fragment was used. Each experiment included

HeLa cDNA and Ca-Ski cDNA as positive and C-33A as negative controls. The relative mRNA

expression level of PIK3CA was calibrated with HUC (Human Universal Control from

Clontech). Primers and probes for the PIK3CA gene (Hs00907966_m1) and β-actin gene

(Hs99999903_m1) were from Applied Biosystems.

Site Directed mutagenesis and phosphorylation determination.




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Site-directed mutations were introduced into a full length of PIK3CA expression vector

(Origene), and confirmed by sequencing, using the QuikChange II XL kit (Agilent). The helical

domain mutations E542K, E545K, E542K/E545K, E542Q/E545K, Q546R, D549H of p110α

were compared to the kinase domain mutation H1047R. The empty vector, wild-type PIK3CA

and mutant PIK3CA expression constructs were transiently transfected into U2OS cells using

HyliMax (DojinDo). The U2OS cells were serum starved in DMEM containing 0.5% FBS

overnight and treated with 0.1 µM Calyculin A (Cell Signaling Technology) in 0% FBS for 30

minutes prior to lysis cell. Whole cell protein (25 ug) was separated in a 4-12% NuPAGE Bis-

Tris gel, transferred to PVDF membrane (Invitrogen). The primary antibodies were monoclonal

rabbit-anti-phospho-AKTSer473, phospho-AKTThr308, total AKT (Cell Signaling Technology) at a

dilution of 1:8000 to 1:10,000, rabbit-anti-p110α antibody and β-actin was used as a control.

HRP-conjugated anti-rabbit IgG was used as secondary antibody (Cell Signaling Technology).

Statistical analyses

Mann-Whitney-U, two-tailed t-test, One Way AVOVA, Kruskal-Wallis, Pearson’s chi-

squared test and Fisher’s exact test statistical analyses were performed using GraphPad Prism

version 5 for Windows; P<0.05 was regarded to be statistically significant.

Results

Exome and targeted gene sequencing

To determine the HPV types and molecular characteristics of Latin American women

with cervical tumors, subjects were prospectively enrolled and tumor tissue and blood collected

at the Instituto de Cancerologia (Guatemala) and the Hospital Central Universitario (Venezuela).




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A comparison sample set of 330 subjects from Mexico was also included (Supplementary Fig.

1).There was no significant difference between squamous carcinoma and adeno- and

adenosquamous tumors in age at collection, reproductive factors, HPV type, or smoke exposure;

however adeno- and adenosquamous tumors are more often diagnosed at Stage I (P=0.061, Table

1).To identify potential cancer genes, 23 Guatemalan CC and corresponding normal blood DNAs

were subjected to exome sequencing. Variants in genes predicted to be mutated in two or more

tumors, and in known somatic cancer genes (18, 27, 28) are shown (Fig. 1). The tumors

contained a predominance of C-T and T-C mutations (Supplementary Fig. 2). Predicted somatic

mutations were found in known cancer genes including PIK3CA, RB1, TP53, MAPK1, HRAS,

KRAS, TSC1, BRCA1, BRCA2, BAP1, and ATM. The tumor and normal exome sequence was

also used for copy number determination and as seen previously (18, 29), nearly all Guatemalan

tumors tested have 3-5 copies of chromosome 3q, 43% have gain of 5q and 14/23 (61%) have

chromosome loss at 17p containing the TP53 loci (Fig. 1, 2). In total 8/23 cervical tumors show

extensive chromosomal rearrangement (>100 chromosome breaks) (Fig. 1). Interestingly one

squamous tumor (A4) has amplification of the 2p region containing MYCN, 10q containing the

FGFR2 locus, and a region of 6q21 (Fig. 1, Supplementary Fig. S3).

To further explore the role of the major genes identified in this study and previously

reported in at least 5% of tumors in the Catalogue of Somatic Mutations in Cancer (COSMIC)

database, an eight-gene targeted sequencing panel was developed (CDKN2A, HRAS, KRAS,

CTNNB1, PIK3CA, PTEN, STK11 and TP53 genes). The targeted panel was applied to 280 CC

from Guatemala, 75 CC and pre-malignant lesions from Venezuela, and a replication set of 330

CC from Mexico, with up to 1000x coverage of targeted nucleotides (500x average,

Supplementary Figs. 1 and 4). Predicted variants are shown (Supplementary Tables S2 and S3).




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Mutations in HRAS, KRAS, CDKN2A, and CTNNB1 were infrequent; however, genes in the

phosphatidyl inositol (PI3K) pathway were frequently mutated. Specifically, activating

mutations were common in PIK3CA, and inactivating mutations in PTEN and STK11 were also

found (Table 2 and Supplementary Tables S2 and S3).

Distribution of mutations in the PIK3CA gene

Somatic PIK3CA mutations were detected in 33% (91 of 280) of carcinomas from

Guatemala, 28% (11 of 40) from Venezuela, and 28% (91 of 325) from Mexico. Only 2 of 27

cervical intraepithelial neoplasia (CIN) grade 1, 2, or 3 lesions from Venezuela (one CIN 2 and

one CIN 3) had PIK3CA mutations (8%), indicating that these mutations occur predominantly in

malignant tumors. When tumors were divided by histological type 155/499 squamous cell

carcinomas (31%), 16/67 adenocarcinomas (24%) and 5/21 adenosquamous carcinomas (24%)

have a PIK3CA mutation. A total of 95% of all PIK3CA mutations were located in the ABD,

ABD-RBD linker, C2, and helical domains of PIK3CA, whereas mutations in the kinase domain

were rare (Fig. 3A and B). In fact, two specific mutations (E542K, E545K) account for 81% of

the PIK3CA mutations in Mexico and 76% in Guatemala (Fig. 3), and helical domain mutations

are significantly more common in squamous cell versus adenocarcinomas (P=0.017,

Supplementary Fig. S5). Helical PIK3CA mutations are more frequent in cervical and bladder

cancer as compared to breast, endometrial or intestinal tumors (P< 0.0001) (Fig. 3C). Several

tumors had more than one PIK3CA or PTEN mutation. For adjacent mutations their presence on

either the same DNA strand (cis) or different strands (trans) could be determined, and both cis

and trans examples were found (Supplementary Fig. S6).




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Interestingly, despite tumors having 70% or greater tumor cells by pathological

examination, many tumors with PIK3CA mutations have a low percentage of mutant reads. A

total of 79% of tumors with a PIK3CA mutation have between 4 and 33% mutant reads, and this

is constant across grades I-IV (78-83%); suggesting that there is considerable tumor

heterogeneity. Targeted sequence on tumor and normal DNA and Sanger sequencing was used to

confirm selected PIK3CA mutations were somatic variants and the approximate mutated allele

fraction was comparable to that obtained from next-generation sequencing (Supplementary Fig.

S7). The high frequency of E542K and E545K mutations allowed the determination of the

mutation fraction of each individual mutation and for double mutants (Supplementary Fig. S8A,

S8B). E542K is found 31% of the time at a mutation fraction greater than 20%, whereas 51% of

E545K-containing tumors have >20% mutant reads (X2=5.5; P=0.019). However, for the six

E542K/E545K double mutants, the two mutations are always on different haplotypes and E542K

is usually more prevalent (Supplementary Fig. S8B).

Several PIK3CA mutations described here have not previously been reported (delN107,

E1034Q in Venezuela; T229I, Q861R, K942M and V952G in Guatemala and V146I, M299V,

delH419_C420 and G914R in Mexican tumors), whereas the R38H, R88Q, K111E, K111N,

E453K, E542K, E545K, and H1047R variants are documented somatic gain-of-function alleles

(25, 30-32) (Fig. 3A). Both combined PIK3CA mutations and overall mutations are statistically

significantly increased in patients diagnosed at a later age and are less common in HPV18- and

HPV45-positive tumors (P=0.0016) (Supplementary Fig. 9, Supplementary Table 4). While

adenocarcinomas occur with a younger average age, and a lower tumor stage and may confound

these relationships, squamous cell subjects diagnosed before age 50 have significantly fewer

PIK3CA mutations (P=0.0001). Comparison of our Latin American data with data from other




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countries [(14, 18, 33), COSMIC database] demonstrates differences in frequency of PIK3CA

mutations in individual domains, as well as the E542K, E545K, and H1407H sites (Fig. 3C;

Supplementary Table S5).

HPV type and PIK3CA gene expression

It has been shown that the HPV E6 and E7 proteins can activate the PI3K/AKT pathway

(34). We determined the mRNA expression levels of the PIK3CA, and HPV E6 and E7

transcripts in 65 HPV16+ tumors. The mRNA levels for PIK3CA were higher in PIK3CA

mutation-positive tumors compared to PIK3CA WT tumors (P = 0.029), and HPV E6 and E7

expression was also elevated in PIK3CA mutant tumors (P=0.040, Supplementary Fig. S10A, B).

Phosphorylation of AKT by specific PIK3CA mutations

To determine whether specific PIK3CA mutations lead to increased AKT

phosphorylation in vitro, U2OS cells were transfected with mutant constructs and used for WB

analysis. Total PIK3CA (p110α), AKT, β-actin and p-AKT (Ser473) were constant. However,

the kinase domain mutation H1047R led to increased p-AKT at Thr308, however neither E542K,

E545K nor the double mutant significantly increased p-AKT at Thr308 levels (Fig. 4).




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Discussion

Our study combines exome and targeted sequencing to examine the relationship between

genetic mutations and cervical cancer in tumors in three countries with high incidence and

mortality. We identified frequent PIK3CA gene mutations in Latin American cervical tumors that

had a distinct distribution from those found in most other cancers (25, 30). Latin American

tumors have a similar PIK3CA mutation frequency as US tumors (33% vs. 31%), and display a

somewhat higher prevalence in squamous carcinomas (Supplementary Table 5). However, the

PIK3CA mutation frequency is significantly lower in Swedish tumors (8.2 %; X2= 35, 2.89 X 10-

08) (14, 18). Most PIK3CA mutations are located in the ABD and ABD-RBD linker, and helical

domain, especially in the Arg532 and Arg535 residues in the helical domain, particularly in

squamous carcinomas. Recent structural studies of the PIK3CA protein (p110α) indicate that the

helical domain of PIK3CA acts as a scaffold for the assembly of p110α domains and for

interactions with the inhibitory p85α (35-37). While E545K mutations are also common in

colorectal, breast, intestine, ovary, and endometrial cancers (25, 30, 38)(COSMIC database),

these tumors also have frequent mutations in the kinase domain. In contrast, we found only six

mutations within the kinase domain in cervical cancer. The most common PIK3CA mutation in

all tumors, H1047R, which has been associated with an increased response rate to

PI3K/AKT/mTOR inhibitors (39), is very rare in our study, consistent with US tumors (14). The

distribution of mutations in PIK3CA/p110α suggests that there is a selective advantage to

disrupting the ABD and ABD-RBD linker interactions in cervical cancers. Interestingly a similar

pattern was recently identified in bladder and HPV+ oral cancer with more helical domain

mutations than kinase domain mutations, and a role for APOBEC has been proposed (38, 40-42).




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Our study has several limitations: 1) the small size of the mutation discovery cohort (24

tumors of different histology and HPV type) would not allow the discovery of all frequently

mutated genes or copy number changes, and without paired-end whole genome sequence we

cannot fully evaluate the high rearrangement tumors for chromothripsis or chromoplexy (43); 2)

we lack a cancer-free cohort to explore risk factors for invasive cancer (apart from HPV

infection); 3) our data on tumor mutation heterogeneity lack a direct assessment of tumor purity

and would require a detailed microdissection, immunohistochemistry, and/or single cell

sequencing component to fully explore; 4) to date we have limited treatment outcome data to

understand how molecular events may predict survival. However we feel that data on tumors

from high prevalence countries is important in understanding cervical cancer worldwide.

PI3K signaling has been shown to be important in HPV transformation (44). In this study,

we show that PIK3CA mRNA expression is (41) elevated in tumors with PIK3CA mutations, and

associated with upregulated E7 mRNA expression at least in HPV16-positive tumors. The

PIK3CA gene is on chromosome 3q, in a region known to be duplicated in most invasive cervical

cancers and in 19/22 of the tumors we report (29). Our data indicate that in approximately 20%

of tumors with PIK3CA mutation (5% of all tumors), mutation is an early event and the 3q

duplication involves the mutant PIK3CA allele, whereas in the remaining tumors the mutation

occurs on the non-duplicated allele, or after duplication (Supplementary Fig. S11).

The presumed late occurring PIK3CA mutations could represent tumor evolution or

represent the accumulation of somatic passenger mutations driven perhaps by HPV induction of

APOBEC enzymes (42). Given the roles of PI3K in cellular proliferation, metastasis, cell cycle,

and cell survival, PIK3CA mutations may impart a more aggressive and treatment-resistant

phenotype (44, 45). However, it should be pointed out that our study is limited in having few




21

early stage lesions, no normal cervical tissue control, and exome and targeted sequencing can

miss mutations, especially insertions/deletions (46). Sampling of multiple areas of the same

tumor as well as primary and metastatic lesions from the same patients could address this issue.

While kinase domain mutations in PIK3CA have been shown to result in elevated AKT

phosphorylation and mTOR activation, consistent with other reports, helical domain mutations

do not (47). Several groups have documented that the AKT-related kinase SGK3 is activated by

PIK3CA helical domain mutations (15, 16). Interestingly, in a clinical trial of AKT inhibitors,

cervical and other cancers patients with the E542K mutation had a shorter median progression-

free survival than those with the H1047R mutation (14, 39); suggesting that this subtype may be

more refractory to therapy. And a recent trial showed PIK3CA to be a marker of poor response

(48). The data from our study and others would suggest that agents directly targeting PIK3C

would have the best chance of benefit.

Our data are consistent with data (18) that cervical tumors have a relatively low level of

driver gene mutations and group with glioblastoma, ovarian, breast, kidney, and acute

myelogenous leukemia as tumors with an average of 2-4 driver gene mutations (28). Given that

HPV expresses the two viral oncogenes, E6 and E7, this is expected. However, RB1 and TP53

are mutated in a subset of tumors suggesting that further inactivation of these genes is sometimes

required. In squamous tumors these additional drivers are more frequently found in tumors in

older women.

While HPV infection is the dominant risk factor in cervical cancer, tobacco use is a major

co-factor in developed countries, (49) and is variable within the subjects in this study.

Interestingly, tobacco use is very low in Guatemala, but exposure to wood smoke is high (Table




22

1). Whether cooking with wood in the home contributes to cervical cancer similar to tobacco will

require further study. We find that the distribution of HPV types is similar in the three

populations studied, but that the PIK3CA and overall mutation load is higher in patients

diagnosed after age 50 and in HPV16+ patients (Supplementary Fig. S9, data not shown).

HPV18 and HPV45 negative tumors are also more common in older patients (Supplementary

Fig. S9B).

In summary, Latin American cervical tumors have a high frequency of mutations in the

PIK3CA gene, especially at the E542 and E545 residues in the helical domain. PIK3CA kinase

domain mutations more extensively phosphorylate AKT and are independent of RAS activity

(47, 50). Furthermore, clinical trials of PI3K/AKT/mTOR inhibitors have shown that patients

with the H1047R mutation in the PIK3CA kinase domain had better response (39). Therefore

these two classes of PIK3CA mutations, while both displaying activating/gain-of-function

properties denote functionally distinct classes of cancers. Our data adds to the literature

published to date demonstrating that although PIK3CA mutations are common in cervical cancer,

they are not predicted to respond well to AKT/mTOR targeted agents. However, comprehensive

surveys of other high prevalence countries are needed to fully understand the worldwide

heterogeneity of this disease.




23

Acknowledgements

The authors thank the staff and health professionals from the Instituto de Cancerologia,

Guatemala City, Guatemala, and Hospital Central Universitario “Dr. Antonio M Pineda”,

Barquisimeto, Lara State, Venezuela, as well as Patricia Zaid, Martha Balsells de Sechel, Keyla

Guerra, Esther Avila and Lineth Boror for sample and data collection and shipping, Russ Hanson

for approvals, and the BSP-CCR Genetics Core for technical support.

Funding Information

The work was supported in part by the Intramural Research Program of the National

Institutes of Health, National Cancer Institute, Center for Cancer Research, and by Leidos

Biomedical Research, Inc., under contract # HHSN261200800001E and the National University

of Mexico (www.unam.mx), grant number SDI.PTID.05.2 (to JB). The content of this

publication does not necessarily reflect the views or policies of the Department of Health and

Human Services, nor does mention of trade names, commercial products, or organizations imply

endorsement by the U.S. government.




24

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27

Figure Legends

Figure 1. Driver gene mutations in 23 Guatemalan cervical cancers. Genes frequently mutated

or amplified in other cancers are indicated, with their gene names at the left and the mutation

percentages (%) on the right. The predominant HPV type and pathology is indicated at the top

(unlabeled tumors are squamous cell carcinomas). Below the main section, the presence of

chromosome rearrangement (>100 chromosome breaks, CHR re), gain of chromosome 3q and

loss of 17p are shown.

Figure 2. Copy number changes in cervical tumors. The predicted copy number changes from 23

tumors analyzed by AmpliSeq Exome were combined. Deletions are displayed by red bars to the

left of the chromosome ideograms, and gains by blue bars to the right. The height of the bars

indicates the combined effect of the CNV. Darker shades of red and blue indicate CNVs above a

cutoff of log2 ratio value of above 0.6 and below -1.0, respectively.

Figure 3. The distribution of somatic PIK3CA mutations. A). Mutations in patients from

Guatemala (red triangles), Venezuela (black triangles), and Mexico (green triangle) are shown

relative to functional domains (ABD, p85 binding domain; RBD, RAS binding domain; C2

domain; Helical domain; and Kinase domain) of the PIK3CA protein. The percentage of

mutations detected within each region and the amino acid positions are indicated below. Blue

indicates novel mutations from this study and purple indicates mutations without published

functional analyses. * indicates the patient with ≥1 PIK3CA mutation. B) Proportion of PIK3CA

mutations in cervical cancer in different countries. The domain location of PIK3CA mutations




28

are shown in comparison with the cervical tumors in this study. The brackets denote comparison

of helical versus kinase domain in Latin American cervical tumors to breast, endometrial and

intestinal tumors (****= P<0.0001). The frequency of PIK3CA mutations is noted above and

details are in Supplementary Table 6C) The frequency and location of PIK3CA mutations from

colon, breast, endometrial, intestine, ovary, bladder from the literature and the COSMIC

Catalogue of Somatic Mutations in Cancer; http://www.sanger.ac.uk/cosmic) database and

cervical cancers from this study are displayed (14, 18, 33).

Figure 4. PIK3CA mutation effect on AKT phosphorylation.

Expression and analysis of the phosphorylation of AKT in U2OS transfected with empty vector,

wild type and mutant PIK3CA constructs. The H1047R constructs showed a significant increase

in p110α and Thr308 levels compared with wild type (WT) control, but the 3 helical domain

mutations E542K, E545K and E542K/E545K showed a minimal level at Thr308. A H1047R

mutant was used as a positive control. Densitometric analysis of specific signals using Image J

software, on three independent blots, were quantitated and normalized to actin. One Way

AVOVA and Kruskal-Wallis Statistical method was performed using GraphPad Prism version 5

(P<0.05).




29

Table 1. Patient Demographics and Disease Characteristics

Characteristic Total

(n=531) Squamous

(n=466)

Adenocarcinoma/ Adenosquamous

(n=65) P value

Mean age at collection 52 ±13.2 52.3 ±13.3 49.8 ±12.4 0.055a

Mean age menarche 13.3 ±1.5 13.3 ±1.5 13.4 ±1.6

Mean pregnancies 5.9 ±3.3 6.0 ±3.3 5.3 ±3.0

Mean age at first birth 18.5 ±2.7 18.6 ±2.6 17.7 ±2.9

Human Papiloma Virus 0.21b

HPV 16 252 (51.5) 221 (51.5) 31 (51.7)

HPV 18 48 (9.8) 38 (8.9) 10 (16.7)

HPV 45 38 (7.8) 33 (7.7) 5 (8.3)

All others 151 (30.8) 137 (31.9) 14 (23.3)

Grade 0.0061b

I 122 (23.3) 96 (20.8) 26 (40.6)

II 213 (40.7) 193 (41.9) 20 (31.2) **

III 173 (33.0) 157 (34.1) 16 (25.0) **

IV 16 (3.0) 14 (3.0) 2 (3.1)

Country 0.010c

Guatemala 208 (39.2) 192 (41.2) 16 (24.6)

Mexico 323 (60.8) 274 (58.8) 49 (75.4)

Cooking Method 0.75b

Gas 57 (22.3) 25 (22.1) 3 (27.3)

Wood 155 (60.6) 74 (65.5) 6 (54.6)




30

Gas&Wood 44 (17.2) 14 (12.4) 2 (18.2)

** P <0.001

aMann-Whitney test

bPearson's chi-squared test

cFisher's exact test

Included are all samples with known pathology that are either squamous carcinoma, adenocarcinoma or adenosquamous carcinoma. Means are followed by standard deviation and numbers by percentages.




31

Table 2. Summary of mutations in targeted gene panel

Legend: Mutations in targeted genes are shown for each country along with the percentage and sum of PIK3CA and PTEN (PIK3CA+PTEN) and PIK3CA< PTEN and STK11 (All PI3K). CIN, cervical intraepithelial neoplasia; CC, cervical cáncer, Guat., Guatemala, Venez., Venezuela. Total excludes Venezuela CIN.

Gene Guat. % Venez. CIN

% Venez. CC

% Mexico % Total

PIK3CA 91/280 33% 2/30 7% 11/40 28% 91/325 28% 30%

TP53 15/280 5.4% 0/30 0% 2/40 5% 15/325 5% 5.0%

STK11 11/280 3.9% 0/30 0% 2/40 5% 6/325 2% 2.9%

PTEN 14/280 5.0% 0/24 0% 2/40 5% 22/325 7% 5.9%

KRAS 2/280 0.7% 0/24 0% 1/40 3% 12/325 4% 2.3%

HRAS 2/280 07% 0/24 0% 0/40 0% 5/325 2% 1.1%

CDKN2A 0/280 0% 1/24 3% 1/40 32% 0/325 0% 0.2%

CTNNB1 0/280 0% 1/24 3% 1/40 3% 0/325 0 0.2%

PIK3CA+PTEN 105/280 38% 13/40 33% 108/325 33% 35%

All PI3K 111/280 40% 15/40 38% 104/325 32% 36%







Figure 2




A

B

C

Fig. 3







Published OnlineFirst June 16, 2015.Clin Cancer Res Hong Lou, Guillermo Villagran, Joseph F. Boland, et al. Activation of the PIK3CA PathwayGenome Analysis of Latin American Cervical Cancer: Frequent

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