[CANCER RESEARCH 63, 655–657, February 1, 2003]
Computational Analysis and Experimental Validation of Tumor-associated
Alternative RNA Splicing in Human Cancer
Zhining Wang, H. Shuen Lo, Howard Yang, Sheryl Gere, Ying Hu, Kenneth H. Buetow, and Maxwell P. Lee1
Laboratory of Population Genetics, National Cancer Institute, Gaithersburg, Maryland 20877
A genome-wide computational screen was performed to identify tumor-
associated alternative RNA splicing isoforms. A BLAST algorithm was
used to compare 11,014 genes from RefSeq with 3,471,822 human ex-
pressed sequence tag sequences. The screen identified 26,258 alternative
splicing isoforms of which 845 were significantly associated with human
cancer, and 54 were specifically associated with liver cancer. Further-
more, canonical GT-AG splice junctions were used significantly less fre-
quently in the alternative splicing isoforms in tumors. Reverse transcrip-
tion-PCR experiments confirmed association of the alternative splicing
isoforms with tumors. These results suggest that alternative splicing may
have potential as a diagnostic marker for cancer.
Most mammalian genes consist of multiple exons interspersed with
introns. Introns are removed from a primary transcript by RNA
splicing, which generates a mature translatable mRNA (1). In some
cases, more than one mRNA is generated from a single primary
transcript via an alternative splicing mechanism. It is well documented
that alternative RNA splicing plays a biologically important function.
For example, membrane-bound IgM and secreted IgD are produced by
alternative splicing of the same primary transcript (2), and sex deter-
mination is regulated by alternative RNA splicing of sxl, tra, and dsx
(3) in Drosophila. Several studies have analyzed alternative RNA
splicing on a genome-wide basis (4–8). These studies showed that
35–59% of human genes have at least one alternative splicing isoform.
Several studies show that alternative RNA splicing occurs frequently
in human cancer cells (9–11). This study examines alternative splic-
ing associated with cancer on a genome-wide basis and provides
experimental validation for the tumor-associated alternative splicing.
The results suggest that alternative splicing may have potential as a
diagnostic marker for cancer.
MATERIALS AND METHODS
Computational Analysis of Alternative RNA Splicing. Each human Ref-
Seq (NM?xxxxxx) sequence was compared with the human EST2database to
identify alternative splicing isoforms using a BLAST parser. The algorithm
defined an alternative splicing event as when two perfectly aligned regions
between the EST and RefSeq were separated by a gap. An E-value of less than
10?10was required for the flanking aligned sequences, and the gap was
required to be ?10 bp. The following z statistic was used to estimate the
probability that an alternative splicing isoform is associated with tumor cells:
z ? (pt? pn)/?p(1 ? p)(1/Ct? 1/Cn). For a given alternative splicing
isoform, ptand pnare the frequency of that alternative splicing event in tumor
and normal libraries, respectively, and p is the average frequency of the
alternative splicing event. Ctand Cnare the number of ESTs in the tumor and
normal libraries, respectively. We used one-side z test for each alternative
splicing site using the z-statistics defined above. Because the two proportions
ptand pnare approximately normally distributed by the central limit theorem,
the difference pt? pnis also approximately normally distributed. Under the
null hypothesis pt? pn? p, the variance is p(1 ? p)(1/Ct? 1/Cn). We defined
the statistics z as the difference of the proportions divided by SD. So z is an
approximately standard normal variable. An alternative splicing isoform is
considered tumor-associated if it has a P ? 0.05. Tumor-associated alternative
splicing isoforms for the tissue-specific type of cancer were identified by
selecting ESTs from cancer and normal tissues.
Experimental Validation. Primers were designed with Primer3 software
(12) to detect regular and alternative splicing products. Primer sequences are
available online.3Total RNA was isolated using RNAzol B (Tel-Test, Inc.,
Friendswood, TX) according to the manufacturer’s protocol. cDNA synthesis
was carried out using avian myeloblastosis virus reverse transcriptase (Invitro-
gen Corp., Carlsbad, CA) and oligo(dT)12–18primers (Invitrogen Corp.). A
Packard MultiPROBE II EX robotic liquid handling system (Packard Instru-
ment Company, Meriden, CT) was used for PCR. PCR was carried out in a
15-?l reaction in 1? buffer [1.5 mM Mg2?, 0.2 mM dNTP, 0.5 ?M primers, 1
unit of Taq DNA polymerase (Applied Biosystems)] and 2 ?l of cDNA.
Amplification parameters were as follows: 95°C for 10 min; 40 cycles of 95°C
for 45 s; 60°C for 30 s; and 72°C for 60 s, followed by extension at 72°C for
10 min. Reaction products were analyzed by agarose gel electrophoresis.
Reactions containing multiple PCR products were purified using the QIAquick
purification kit (Qiagen, Inc., Valencia, CA).
To confirm the identity of PCR products, 18 PCR fragments were se-
quenced using ABI Prism BigDye Terminator Cycle Sequencing Ready Re-
action Kit (Applied Biosystems) and an ABI Prism 3100 or 3700 Genetic
Analyzer (Applied Biosystems). Sequencing traces were analyzed using Se-
quencher software (Gene Code Corporation, Ann Arbor, MI) and Phred/Phrap
(13). The results confirmed the expected DNA sequence in all cases.
RESULTS AND DISCUSSION
Genome-wide Screening for Tumor-associated Alternative
Splicing Isoforms. Alternative RNA splicing isoforms were identi-
fied for 11,014 RefSeq sequences using a BLAST search algorithm to
compare each RefSeq pairwise with 3,471,822 sequences in the hu-
man EST database. The algorithm identified 26,258 alternative splic-
ing isoforms, one-third of which had two or more ESTs. The majority
of ESTs aligned perfectly with a cognate RefSeq sequence (i.e.,
regular splicing event); however, in many comparisons, two perfectly
aligned regions were separated by a gap (i.e., alternative splicing
event). An EST that does not match its cognate RefSeq perfectly is an
alternative splicing isoform. Each alternative RNA splicing isoform
has unique parameters, including the location of the splice junctions
and the length of the inserted or deleted sequence.
If alternative RNA splicing isoforms are associated with specific
cancer cell types, then they could potentially serve as diagnostic
markers for cancer. This idea was tested as follows. Alternative
splicing isoforms were classified as tumor or normal based on the
source of the mRNA used to construct the relevant cDNA library and
P that the isoform was present at higher frequency in tumor cDNA
libraries than in normal cDNA libraries (see “Materials and Methods”
for details). This analysis showed that 845 alternative RNA splicing
isoforms (3.2%) were significantly (P ? 0.05) associated with tumor
libraries. A complete list of 845 tumor-associated alternative splicing
isoforms is available online.3The alternative splicing isoforms that
Received 9/12/02; accepted 12/2/02.
The costs of publication of this article were defrayed in part by the payment of page
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1To whom requests for reprints should be addressed, at Phone: (301) 435-1536; Fax:
(301) 402-9325; E-mail: firstname.lastname@example.org.
2The abbreviations used are: EST, expressed sequence tag; RT-PCR, reverse tran-
3Internet address: leelab.nci.nih.gov/ASCA.
are associated with liver, brain, placenta, lung, kidney, and prostate
cancers were also identified (Table 1). Some examples of tumor
associated alternative splicing isoforms in various tissues were listed
in Table 1.
Splice junctions in the alternative RNA splicing isoforms were
analyzed and categorized into eight subgroups. The frequency was
calculated for each splicing subgroup (Fig. 1). Interestingly, GT-AG
splice junctions were used significantly less frequently in alternative
splicing isoforms than in regular splice events. GC-AG splice junc-
tions were used in 16.8% of type I insertions in alternative splicing
isoforms but in ?0.43% of regular splicing events (39-fold increase).
GC-AG usage increased specifically in tumors (P ? 0.002 in ?2test).
Validation of Tumor-associated Alternative Splicing Isoforms
by RT-PCR. To validate the computation-predicted alternative RNA
splicing isoforms, 12 pairs of matched tumor and normal RNA sam-
ples from lung, breast, liver, and prostate tumors were analyzed by
RT-PCR. Primers were designed to specifically amplify regular or
alternative splicing products (Fig. 2). Seventy-six alternative RNA
splicing isoforms were selected for analysis based on a P ? 0.05, or
because they were known to be involved in cancer. Fifty-five (72%)
of the expected products were detected by PCR. Forty-five of these
alternative RNA splicing isoforms were expressed in tumor but not
matched normal samples. For example, three lung cancer samples
expressed alternative splicing products, but none of their matched
normal samples expressed the same mRNA isoform (Fig. 2, Lanes
1–6, the alternative splicing marked with deletion). However, this
pattern was not observed for all samples; alternative splicing products
were detected in tumor and matched normal samples from liver (Fig.
2, Lanes 7–8).
Alternative splicing is differentially associated with specific tissues
or types of cancer. Some tumor-specific splicing isoforms were de-
tected in several tumor tissues, whereas others were less prevalent
(Fig. 3). For example, the NME1 alternative RNA splicing isoform
was detected in all five lung cancer samples but not in any of the
breast or liver cancer samples. However, the RAB1A alternative RNA
splicing isoform was present in all four types of cancer tissues.
Interestingly, three genes, RAB1A, RBBP8, and AXL, expressed
alternative but not regular splicing variants in tumors. Conversely, the
matched normal tissues expressed only regular splicing products. The
absence of regular splicing products in tumors suggests that loss of
regular splicing isoforms may be associated with tumorigenesis.
Our validation results show that 45 of 76 (59.2%) selected alterna-
tive splicing isoforms were tumor specific. This observation is con-
sistent with previous reports that alternative splicing often increases in
Fig. 1. Splicing junctions in eight alternative splicing subgroups. The splicing junction
sequences were analyzed as described in “Materials and Methods” and “Results and
Discussion.” The percentage of GT-AG splice junctions are indicated for the junction
unique to the alternative transcript. NA indicates that splice junction sequences are not
Fig. 2. Experimental validation of alternative splicing using RT-PCR. N and T denote
normal and tumor, respectively. Regular and deleted splicing products are indicated.
Arrows represent primers and open boxes designate exons. The horizontal lines between
exons represent introns. Diagonal lines indicate alternative splicing events.
Fig. 3. Summary of tumor-associated alternative splicing validation experiments. Four
breast, one liver, five lung, and two prostate cancer samples and their matched normal
samples were used in the validation experiment. The Y axis represents the number of
sample pairs that specifically expressed alternative splicing isoforms in the tumor sample
and expressed regular splicing products in the normal sample. Regular splicing products
may or may not have been detected in the tumors. Data are shown from 10 representative
genes. Additional data are available online.3
Table 1 Identification of tumor-associated alternative splicing isoforms in various tissues
No. of ESTs
No. of significant
CYP2C8, KNG, AMBP, AHSG, ANG, TDO2, BHMT2, ADH4, HFL1
MAD2L1, RAD1, MAPK8IP1, PCMT1, MCK, POLR2I, PKIA, DLEU2
LDHC, ADM, ATP6S1, ENG, IFNGR2, GPS1, DSPG3, HHLA2, UROD
LRP1, SFTPC, TCEB1L, SKP1A, RCL, HCG1V.9
CD9, PCK2, HIBCH, TINAG, TSPAN-1
TGM4, KLK2, PPP2R5A, HT012
RAB1A, NME1, NEU2, TOP1, MRE11A, NCOA1, RNPEP, IRAK1
aThis is the number of alternative splicing isoforms that are significantly associated with tumors in the given tissue; see “Materials and Methods” for details.
ALTERNATIVE RNA SPLICING IN CANCER
human cancer (9–11), although the cause of the increase is not known.
One possibility is that splicing fidelity is compromised in tumors
because of mutations or altered gene expression affecting the splicing
machinery. The mechanisms stimulating tumor-associated alternative
splicing may be related to microsatellite instability in cancer cells,
which is caused by defects in mismatch repair (14). Future experi-
ments are required to test this hypothesis.
We thank Drs. David Kaufman, Kent Hunter, and Tzu-ling Tseng for
helpful comments on the manuscript.
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