Trial Information

Gene-expression Profile as Predictor of Central Nervous System Metastasis Development in Non-small Cell Lung Cancer: a Prospective Study

Brain metastases occur in 30-50% of lung adenocarcinoma (LAC) patients and confer a worse
prognosis and quality of life. A better selection of in-risk patients through a more
accurate biomarker could improve the benefit of prophylactic therapies. The aim of this
prospective study was to determine a gene-expression profile of primary tumor associated
with brain metastasis (BM) and to evaluate the overall survival (OS) in patients with
advanced LAC.

Introduction.Lung cancer is the first cause of cancer death in the world. Eighty five
percent of patients are diagnosed yearly with non-small cell lung cancer (NSCLC). Despite
efforts, innovations, and progress in diagnosis and treatment of these patients, overall
survival (OS) at 5 years of diagnosis is only 15%. The central nervous system (CNS) is a
devastating and frequent site of metastasis development in NSCLC. The reported incidence of
CNS metastasis in patients with NSCLC is 54% with an OS of <1 year after diagnosis. Age,
clinical stage, gender, and initial treatment period are some of the reported with CNS
metastasis development-related factors in patients with NSCLC. We recently described that
high carcino-embryonic antigen (CEA) serum levels (>40 ng/dL) at diagnosis and
adenocarcinoma histological type are independently associated with higher risk if brain
metastasis development. However, due to their lack of specificity of all this reported
factors, we are required to detect biomarkers to predict brain metastasis in patients with
NSCLC with the objective to prevent their development.Metastasis process is complex it
involves well-defined molecular-printed steps, as invasion, vascular intravasation,
implantation and growing at the new specific organ. Higher motility, capacity for
extracellular matrix degradation, immune system evasion, and adhesion at the new specific
organ are some of the tumoral cell characteristics required to metastasize. In particular,
molecular events for brain metastasis development from primary NSCLC even if no at al
described, are currently well understood. Gene-expression microarray allow analyzing the
expression changes of thousands of genes simultaneously, distinguishing the altered
expression of neoplastic cell genes from normal tissue. Identification of biological
patterns, pharmacological molecular targets, and biomarkers for prognosis and evaluation for
therapeutic response, and even a more specific neoplasia classification are some of the
results of gene-expression microarray studies in hematological, breast and NSCLC cancer.
Determination of tobacco-smoke transcriptional changes in oncogenes and antioncogenes had
been determined by the use microarray data. A gene-expression profile of 20 genes
differentiates health lung tissue and lung cancer with higher specificity than
histopathologic evaluation. Furthermore, gene-expression microarray studies had been
developed for predicting survival and recurrence in early NSCLC stages for identification of
patients who could have benefit of adjuvant therapy, with promising result.The objective of
this study was to identify a gene-expression profile from primary lung adenocarcinoma
related with brain metastasis, and to evaluate in a prospective manner their prognostic
significance on survival in patients with advanced disease.Experimental Design These study
used clinical, longitudinal, prospective, observational, and analytical cohort s with the
selection of a nonprobabalistic-type sample.In a prospective manner, from January 2009 to
June 2011, patients admitted to our Institute confirmed histologically confirmed stage IIIb
and IV of LAC were eligible for study inclusion. Analyzed clinical variables comprised
smoking history, gender, age, general condition and brain metastasis development. Primary
tumor core-biopsy was performed prior to any treatment and snap-frozen. A single pathologist
evaluated all tumors. Standard platinum-based chemotherapy was employed for all patients.
All patients were submitted to Magnetic resonance imaging (RM) to evidence the presence or
absence of brain metastasis (BM). During follow-up, we carried out Computed tomography (CT)
of the brain stem for this purpose. Preliminary statistical analysis was performed utilizing
the Student t, the Mann-Whitney U, the χ2, or the Fisher exact test. Once the study ends, we
will conduct logistic-regression multivariate analysis. Global survival time will be
analyzed with the Kaplan-Meier technique, and comparisons among groups will be performed
with the log-rank test. High Risk characteristics as gender, histology, and age related with
greater frequency of development of metastasis to CNS were analyzed.The study was carried
out according to the principles of ClinicalTrials and accepted by the INCan Bioethical and
Scientific Committees (reference numbers INCAN/CC/067/08). A collaboration agreement was
signed with the INMEGEN and was approved within the Health Research Sectorial Fund (FSIS)
CONACyT-México (SALUD-2009-01-115552).

Selection for obtaining tumor biopsies depended on the characteristics of the patient and of
the tumor. The biopsy could be taken by means of CT guided tru-cut needle, open
thoracoscopy, or bronchoscopy with optic fiber. Each tumor sample was divided into two; one
sample was analyzed by the INCan Pathology Service (by a sole observer blinded to the
clinical variables) for their histological clinical diagnosis and quantification of
neoplastic cellularity, and the remaining half was immediately stored at ‒80°C until
processing for RNA extraction.RNA Extraction:RNA was extracted from frozen tumor biopsies,
weighted and cryofractured in liquid nitrogen. Extraction and purification of total RNA from
tissue (up to 5 mg tissue) procedure was done using RNeasy Micro Kit (QIAGEN, Germany) (cat.
217084). RNA was analyzed using the Agilent 6000 Chip (Agilent Technologies, Santa Clara,
C.A.). RNA quality consisted on the obtention of RNA Integrity Number (RIN) > 8. RNA samples
were chosen for microarray analysis when quality and concentration were obtained for this
purpose. Microarray Expression:We are using an Affymetrix platform, which consists of an in
situ synthesized oligonucleotide microarray. The GeneChip® that we are employing is the
Human Gene 1.0 ST Array, which allows analyzing the expression of 28,869 different genes
(each transcript is represented by 26 disperse probes along its entire length, present in
the human genome, which covers 99% of the sequences present in the RefSeq data bank of the
GenBank. The Two-Cycle Target Labeling protocol is followed as suggested by the manufacturer
and described succinctly as follows and shown graphically in the figure at the end of this
Materials and Methods section: Total RNA (100 ng/uL) is retro-transcribed using T7-Oligo(dT)
Promoter primers in the synthesis reaction of the first complementary DNA chain (cDNA).
After treatment with RNAase H, the second cDNA chain is synthesized, which will serve as
template in the Transcription reaction in vitro (TVI). The first TVI reaction is carried out
with T7 polymerase RNA and unmarked ribonucleotides for the amplification of complementary
RNA (cRNA). These cRNAs are retro-transcribed in the synthesis step of the first cDNA chain
of the second cycle using random primers. Subsequently, T7-Oligo(dT)-Promoter primers are
employed for the synthesis of the second chain of cDNA, generating the double-helix cDNA
template that contains the promoter T7 sequence. This cDNA is amplified and marked in a
second TVI reaction using the T7 polymerase DNA and a mixture of
ribonucleotides/biotinylated nucleotide analog. These target biotinylated cDNAs are cleaned,
fragmented, and hybridized to the GeneChip® expression microarrays. After hybridization,
fluorescent marking was performed with a streptavidin-phycoerythrin and biotinylated
anti-streptavidin antibody amplifier system. Fluorescence is detected with a high-resolution
laser scanner.Reading and Analysis of Expression Microarrays:We will utilize the Expression
Console of Affymetrix software to evaluate the quality of the microarrays and will correct
the background signal with standard methods [49,50]. For signal intensity-level
normalization, we will employ "non-supervised" methods, which use the data of all of the
experiment's microarrays; this will allow us to render these comparable among themselves,
because what a microarray assay evaluates is gene expression by means of fluorescence
intensities; thus, it is important to establish cut-off points from which we can consider
under- or overexpression. Once the data are normalized, the final stage is to resume the
values of all the probes that exist for each gene in the microarray in a sole value, which
is the gene's expression level. For detection of differentially expressed genes, we will
construct a linear model that includes all of the experiment's microarrays simultaneously;
in this manner, we will be able to analyze contrasts between group A (patients with
metastasis to CNS during the follow-up period) and group B (patients without metastasis to
CNS during the same period). As internal control, we will prove the differential expression
of some genes by RT-PCR in real time. Results will be represented in blocks of heat maps and
in tables, in which the most active genes are listed along with their functional
description. For risk-profile validation, we will perform leave-one-out cross validation
method and will postulate a second cohort for this objective.