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Alternative RNA Splicing as a Potential Major Source of Untapped Molecular
Targets in Precision Oncology and Cancer Disparities
Timothy J. Robinson1,, Jennifer A. Freedman2,3,, Muthana Al Abo3, April E. Deveaux2,
Bonnie LaCroix2, Brendon M. Patierno2, Daniel J. George2,3 and Steven R. Patierno2,3,*
1Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, 33612, USA
2Department of Medicine, Division of Medical Oncology, Duke University Medical
Center, Durham, NC, 27710, USA
3Duke Cancer Institute, Duke University Medical Center, Durham, NC, 27710, USA
Running title: RNA splicing in precision oncology and cancer disparities
Keywords: alternative RNA splicing, biomarkers, therapeutic agents, oncology, cancer
disparities
Financial support: This work was partially supported by a RSNA Resident Research
Grant to TJR PI and SRP Mentor, a DoD Prostate Cancer Research Program Health
Disparity Research Award PC131972 to SRP PI and JAF Co-I, a NIH Feasibility Studies
to Build Collaborative Partnerships in Cancer Research P20 Award 1P20-CA202925-
01A1 to SRP Overall PI and JAF PI of Pilot Project One, and a NIH Basic Research in
Cancer Health Disparities R01 Award R01CA220314 to SRP PI and JAF Co-I.
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*Corresponding Author:
Steven R. Patierno
10 Bryan Searle Drive
Durham, NC 27710
Phone: +1 919 613 5093
Fax: +1 919 681 7385
Email: [email protected]
The authors declare no potential conflicts of interest.
Word count: 2,354
Total number of figures and tables: 1 figure
These authors contributed equally to this work.
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Statement of Translational Relevance
The path forward for translational cancer research and clinical practice in oncology is
promising, as drivers of tumor biological diversity remain underexplored. One of the
underexplored mechanisms, for which there is emerging evidence that it plays a critical
role in cancer heterogeneity, aggressiveness, and therapeutic response, is Alternative
RNA Splicing (ARS). There is also emerging evidence for agents to target and exploit
ARS for therapeutic application. Despite the indications that ARS plays such critical
roles in cancer, most translational and clinical cancer research focuses on mutation and
aggregate gene expression. Increasing awareness of the significance of ARS to cancer
and coalescence of ARS bioinformatics and cancer biology have the potential to
increase incorporation of ARS into biomarker and drug development in oncology.
Ultimately, this has the potential to lead to new precision medicine interventions that are
likely to improve outcomes for cancer patients and mitigate cancer disparities among
racial groups.
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Abstract
Studies of Alternative RNA Splicing (ARS) have the potential to provide an abundance
of novel targets for development of new biomarkers and therapeutics in oncology, which
will be necessary to improve outcomes for cancer patients and mitigate cancer
disparities. ARS, a key step in gene expression enabling individual genes to encode
multiple proteins, is emerging as a major driver of abnormal phenotypic heterogeneity.
Recent studies have begun to identify RNA splicing-related genetic and genomic
variation in tumors, oncogenes dysregulated by ARS, RNA splice variants driving race-
related cancer aggressiveness and drug response, spliceosome-dependent
transformation, and RNA splicing-related immunogenic epitopes in cancer. In addition,
recent studies have begun to identify and test, pre-clinically and clinically, approaches
to modulate and exploit ARS for therapeutic application, including splice-switching
oligonucleotides, small molecules targeting RNA splicing or RNA splice variants, and
combination regimens with immunotherapies. Although ARS data holds such promise
for precision oncology, inclusion of studies of ARS in translational and clinical cancer
research remains limited. Technologic developments in sequencing and bioinformatics
are being routinely incorporated into clinical oncology that permit investigation of
clinically relevant ARS events, yet ARS remains largely overlooked either because of a
lack of awareness within the clinical oncology community or perceived barriers to the
technical complexity of analyzing ARS. This perspective aims to increase such
awareness, propose immediate opportunities to improve identification and analysis of
ARS, and call for bioinformaticians and cancer researchers to work together to address
the urgent need to incorporate ARS into cancer biology and precision oncology.
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The widespread adoption of genomic profiling of human tumors is now providing
information to researchers, patients, and providers, and influencing translational
research and clinical practice.1,2 However, studies to date have largely focused on
actionable mutations and aggregate gene expression and have predominantly included
patients of European ancestry. 3 4 As a result, these efforts may have missed drivers of
cancer biological and clinical heterogeneity among patients of different ancestries that
have the potential to aid in the development of new diagnostic and therapeutic
interventions.
As our understanding of the molecular etiology of cancer has evolved past the
“initiation-promotion” paradigm, we are increasingly appreciating the importance of
transcriptional reprogramming in early- and late-stage tumor evolution.5 For cancers
with a long developmental history, such as breast, colorectal, and prostate cancer, the
mutation burden reflects mostly late accumulation events, raising the question as to
whether or not mutations or other genetic alterations are the early oncogenic drivers.
Interestingly, it is for these same cancers for which some of the most striking disparities
in incidence and outcome among patients of different ancestries have been repeatedly
demonstrated. Here we draw attention to the emergence of novel aspects of another
level of clinically relevant genomic complexity that has the potential to explain more
clearly the dynamic diversity in human tumor biology: Alternative RNA Splicing
(ARS)(Recently reviewed by Urbanski et al. 7)
ARS is a key step in gene expression in higher eukaryotes. Humans share 99%
similarity with chimpanzees by DNA sequence, but less than 60% by alternatively
spliced exons.8 The current theory as to how such striking diversity can exist so late in
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evolution is the unique ability of ARS to provide a modular, low-risk mechanism of
protein diversification in risk-averse higher organisms.9 Given the importance of ARS to
evolutionary biological diversity, it could also be reasonably speculated that ARS likely
drives tumor-related biological diversity. Indeed, oncogenes dysregulated by ARS, but
not by mutation, have been identified (e.g. BARD1).10
ARS is the physiological process that creates different RNA variants from the
same sequence of DNA.11 It is regulated by cis-acting splicing elements (nucleotide
sequences or motifs) that recruit trans-acting splicing factors (proteins or RNAs) that
enhance or silence the use of splice sites. Variation in cis-acting splicing elements,
differential expression of trans-acting splicing factors or mutation in genes encoding
components of the RNA splicing machinery can all alter ARS and result in disease,
including cancer.12 In addition, non-canonical RNA splicing events can result in aberrant
RNAs (i.e. not normally expressed in healthy tissues or cells) in pathophysiologic
states.13
Analyses of tumors highlight the magnitude of putative actionable ARS
alterations that have yet to undergo characterization in patients, as half of such tumors
harbor ARS-altering single nucleotide variants.14 The frequency of these alterations
raises the question of whether “mutations of unknown significance” might drive changes
in ARS. Several examples of the role of ARS in tumor biology have been recently
reviewed 7. We have shown that discrepant probe set changes within the same gene,
thought to be “noise” on microarrays intended to measure aggregate gene expression,
is often a signal of changes in ARS.15,16 The ability to detect isoform-specific mRNA
changes within expression data suggests that any physiologic state, characterized by
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significant differences in gene expression is likely to exhibit comparable changes in
more nuanced metrics of alternative mRNA processing and pre-mRNA splicing.
Work from our laboratories and others has begun to highlight the importance of
ARS in cancer biology and cancer disparities19,20 and demonstrate that dysregulation of
ARS may be a principal feature differentiating cancers from their host tissues of origin.21
In prostate cancer, a role of ARS is emerging in association with local22 (for example,
SRPK1, which regulates ARS of VEGF, associates with local prostate cancer stage and
invasion) and distant23 (for example, transcriptome-wide changes in ARS associate with
metastatic colonization) disease progression. Our team participated in a multi-
institutional study demonstrating differences in expression of RNA splice variants
between prostate cancer in African American and white patients. Approximately one-
third of the variants enriched in prostate cancer in African American patients were
likewise present in patient-matched normal prostate specimens, indicating germline
origin and potential clinical significance as biomarkers.19 The number of differentially
expressed, ancestry-related RNA splice variants far exceeded the aggregate gene
expression differences in the same tissues. Ancestry-specific prostate cancer cell lines
and xenografts were used to demonstrate the functional significance of these RNA
splice variants to driving ancestry-related prostate cancer aggressiveness and
influencing drug responses to targeted therapeutics. As one example of the power of
this comparative spliceomics24 approach, Phosphatidylinositol-4,5-bisphosphate 3-
Kinase delta (PI3K) was identified as a novel driver of prostate cancer aggressiveness
and RNA splice variants of PI3K were discovered with distinct functions that serve as
biomarkers of drug response. Studies in metastatic prostate cancer suggest that
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aberrant RNA splicing may play roles in progression25 and studies have identified high-
frequency tumor-associated differences in ARS in breast, liver and lung cancer.26
Furthermore, the Androgen Receptor (AR), a driver of prostate cancer progression and
treatment target, undergoes aberrant RNA splicing with predictive and prognostic
treatment implications in castration-resistant disease.27 Additional examples of the role
of ARS in cancer are emerging in the dysregulation of tumor suppressor genes and
oncogenes, including TP53, BARD1, AR and BCL210, and oncogenes, including MYC,
appear to rely on the spliceosome to drive transformation.28 In fact, ARS has been
causally demonstrated across all of the hallmarks of cancer.20 Recently, the plastic
nature of ARS and the bridge between ARS and therapeutic effect has been
demonstrated with the discovery that ionizing radiation induces senescence through
ARS of TP53.29, and that hypoxia, a fundamental driver of both chemotherapy and
radiation resistance, regulates ARS of genes involved in the hallmarks of cancer in
breast cancer cells.30
Germline or somatic genetic variation in cis-acting splicing elements has also
been found to associate with cancer risk and prognosis. We have identified associations
between germline single nucleotide polymorphisms predicted to regulate RNA splicing
of stemness genes and disparities in prostate cancer risk and prostate cancer
survival.31,32 Work focusing on somatic mutations in BRCA1 has shown that African
American women have 24% of mutations associated with cis-acting splicing elements,
greater than in women of other ancestries.33 In addition, others have observed higher
rates of germline “variants of uncertain significance” in African Americans as compared
to whites with early onset breast cancer34, suggesting that ARS might be relevant to
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disease as a function of ancestry. Somatic mutations in genes encoding core units of
the spliceosome have been identified in cancers.35 Dysregulated trans-acting splicing
factors have also been identified, with roles in genomic stability (via inhibition of
destabilizing RNA:DNA complexes)36 and are overexpressed in breast, colon and lung
tumors.37 In breast cancer, an appreciation of trans-acting splicing factors as drivers of
progression is emerging, with such factors being differentially expressed during
progression.38
Therapeutic approaches to manipulate ARS, correct aberrant RNA splicing or
produce novel RNA splice variants are being developed and tested in human clinical
trials. Splice-switching oligonucleotides (SSOs) can modulate pre-mRNA splicing by
binding to target pre-mRNAs and blocking access of the RNA splicing machinery to a
particular splice site.39 Thus, SSOs can simultaneously limit production of pathogenic
variants and induce expression of variants with therapeutic value, as reported in spinal
muscular atrophy40, leading to the first FDA-approved splicing-targeted therapy
(Spinraza) in December 2016. Additional SSOs exhibit therapeutic potential in mouse
models of disease, including cancer.41 These successes dovetail with advances in RNA
therapeutic delivery.42 In addition to SSO-based approaches, studies have used
phenotypic screens and splicing-specific reporters to conduct high throughput screens
of small molecules and have identified modulators of RNA splicing, including those with
activity in cancer cells.43,44 A small molecule modulator of RNA splicing is in clinical trials
for spinal muscular atrophy.45 Despite such proofs of principle, relatively limited effort
focuses on adopting these technologies in cancer drug development. Much as in
current targeted therapy approaches, it is likely that the ultimate efficacy of any
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proposed “splice targeted” therapy will strongly depend on the hallmark of cancer5 and
gene-specific splicing profile under consideration.
ARS is also likely a mechanism generating immunogenic epitopes in cancer and
a predictive indicator of immunogenic diversity. Examples of ARS driving immunogenic
potential date back 20 years, but further pursuit has not occurred in the immune
checkpoint therapy era.46 Molecular analyses of melanoma support the potential for
ARS to affect immunotherapy; for example, melanomas that have mutations in the RNA
splicing regulator RNA Binding Motif protein, X-linked Like 1 (RBMXL1) may have
corresponding widespread ARS,47 although the prevalence of mutated RBMXL1 may be
low (~8%). 48 It has been confirmed that novel alternatively spliced gene fusion products
may provide novel immunogenic epitopes.49 50 Further, interventions to drive ARS may
synergize with immune checkpoint inhibitors. For example, small molecule and drug
screens have identified both new and existing RNA splicing modulators, e.g. digoxin,51
although the efficacy of such agents in combination with immunotherapies remain
untested.
Despite the significance of ARS to cancer, clinically-oriented reviews of cancer
biomarkers, therapeutics, and profiling of tumor heterogeneity often fail to mention or
only peripherally reference RNA splicing52,53,54, suggesting that this aspect of genomic
regulation has remained outside the mainstream of discussions of clinical cancer
genomics. We are only now starting to appreciate the translational importance of ARS in
cancer; for example, patients having exon 14 splice site alterations in MET exhibit
positive clinical response to MET inhibitors.55 These examples of missed “hits” suggest
that many RNA splice variants with potential as targets in precision oncology have yet to
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be discovered. ARS can yield targets relevant to all aspects of precision oncology. As
described herein and shown in Figure 1, RNA splice variants can pre-exist in normal
cells and persist following transformation or can be expressed de novo in cancer cells.
Such RNA splice variants and variation in cis-acting splicing elements can serve as
biomarkers. RNA splice variants can serve as targets for RNA-targeted therapeutics,
including SSOs and RNA-targeted small molecules. The proteins encoded by RNA
splice variants and trans-acting splicing factors can serve as targets for protein-targeted
therapeutics, including protein-targeted small molecules. RNA splice variants and their
encoded proteins can also serve as neoantigens.
There are likely reasons that ARS has not risen to the forefront of translational
research, despite its enormous potential. ARS is complex and related analyses must
specify details of the structures of the events and reference this information with respect
to the relative abundance of one RNA variant to another within the same gene. Exon-
level annotation is highly variable by data source. Definitions of RNA splice variant
ratios or other non-standardized metrics must be used to quantify ARS. Lastly, the
distinction between RNA splice variant-specific expression versus overall expression is
not always made and may in some circumstances be more accurately described by
mRNA transcript-specific changes in abundance.
Technical limitations and analyses of ARS are not trivial. Standardized
computational approaches to analyzing these data do not exist. Sequence-based
approaches are typically described as structural or count-based.56 Count-based
approaches require selecting a database to provide the coordinates or “bins” with which
to quantify exon abundance, and can produce variable results depending on bin
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definition. Thus, the same software, using a different reference genome or alignment,
can produce different results. Liu et al. compared the ability of current RNA-seq based
methods to detect ARS within a heat shock dataset in plants.56 The study did not detect
a single gene as alternatively spliced by the seven programs included in the analysis,
underscoring the need to understand the relative strengths and limitations of various
ARS analysis methods. The application of novel bioinformatics techniques to existing
data with an ARS focus is resulting in substantial advances in understanding tumor
genomic heterogeneity,57 58 and efforts are underway to better understand how ARS
interrelates to other genomic phenomena including long non-coding RNAs, miRNAs,
and protein translation.59 Although we focused on the role of ARS of mRNAs, it is
important to note that long non-coding RNAs have been demonstrated to undergo, as
well as regulate, ARS. 60,61 Lastly, it should be noted that there are emerging
technologies such as single-molecule real-time (SMRT) isoform sequencing (Iso-Seq)
that are used in conjunction with the commercial RNA-seq platforms (i.e. “third
generation sequencing). This technology and companion software permit
comprehensive analysis of entire molecules and variants of RNA (messenger, non-
coding, circular, etc).62 This technology holds much potential for the future of ARS
analyses, however its present utility in clinical oncology remains limited, given that it is
not incorporated in clinically used genomic assays in oncology and its analytic
performance in this setting remains to be confirmed.
We suggest that key factors that have limited incorporation of ARS in genome-
wide studies within the clinical oncology community are lack of awareness, cost, and
technical complexity and interpretation. We hope that this Perspective and ongoing
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research will increase awareness. Fortunately, cost of such analyses continues to
decrease. The largest barrier is technical complexity and interpretation. We call for
attention to spliceomics, and the need for increased collaboration between
bioinformaticians and cancer biologists to develop improved methods to identify and
analyze ARS. Of particular value would be the expansion of RNA-Seq software to
include analyses of ARS in parallel to standard gene expression pipelines, which would
greatly remove current time and technical barriers to investigator examination of RNA
splicing. Such software should also provide pathway analysis, analysis of factors that
regulate ARS, and be accessible without sophisticated bioinformatics expertise.63
Lastly, there are immediate opportunities to standardize variant names, exon
descriptions and numbering and the approaches that report RNA splicing events.
In summary, ARS is a principal driver of biological diversity and plays a role in
every hallmark of cancer, yet is rarely examined in profiling of tumors and is largely
overlooked in biomarker and drug development in oncology. We believe the primary
barrier to taking advantage of this plethora of potentially actionable data is the difficulty
of analyzing ARS data and call for a partnership between bioinformaticians and cancer
researchers to address this need. Although the time and learning curve associated with
these analyses is steep, such efforts are likely to solve unmet challenges in cancer
biology, including cancer disparities, and patient care.
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43. Younis I, Berg M, Kaida D, et al: Rapid-response splicing reporter screens identify differential regulators of constitutive and alternative splicing. Mol Cell Biol 30:1718-28, 2010 44. Pawellek A, McElroy S, Samatov T, et al: Identification of small molecule inhibitors of pre-mRNA splicing. J Biol Chem 289:34683-98, 2014 45. ClinicalTrials.gov: An Open Label Study of LMI070 (Branaplam) in Type 1 Spinal Muscular Atrophy (SMA), 2014 46. Scanlan MJ, Chen YT, Williamson B, et al: Characterization of human colon cancer antigens recognized by autologous antibodies. Int J Cancer 76:652-8, 1998 47. Cifola I, Pietrelli A, Consolandi C, et al: Comprehensive genomic characterization of cutaneous malignant melanoma cell lines derived from metastatic lesions by whole-exome sequencing and SNP array profiling. PLoS One 8:e63597, 2013 48. Berger MF, Hodis E, Heffernan TP, et al: Melanoma genome sequencing reveals frequent PREX2 mutations. Nature 485:502-6, 2012 49. Volpe G, Cignetti A, Panuzzo C, et al: Alternative BCR/ABL splice variants in Philadelphia chromosome-positive leukemias result in novel tumor-specific fusion proteins that may represent potential targets for immunotherapy approaches. Cancer Res 67:5300-7, 2007 50. Smart AC, Margolis CA, Pimentel H, et al: Intron retention is a source of neoepitopes in cancer. Nat Biotechnol, 2018 51. Stoilov P, Lin CH, Damoiseaux R, et al: A high-throughput screening strategy identifies cardiotonic steroids as alternative splicing modulators. Proc Natl Acad Sci U S A 105:11218-23, 2008 52. Zardavas D, Irrthum A, Swanton C, et al: Clinical management of breast cancer heterogeneity. Nat Rev Clin Oncol 12:381-94, 2015 53. Jamal-Hanjani M, Wilson GA, McGranahan N, et al: Tracking the Evolution of Non-Small-Cell Lung Cancer. N Engl J Med 376:2109-2121, 2017 54. Garman B, Anastopoulos IN, Krepler C, et al: Genetic and genomic characterization of 462 melanoma patient-derived xenografts, tumor biopsies and cell lines. Cell Rep 21:1936-52, 2017 55. Frampton GM, Ali SM, Rosenzweig M, et al: Activation of MET via diverse exon 14 splicing alterations occurs in multiple tumor types and confers clinical sensitivity to MET inhibitors. Cancer Discov, 2015 56. Liu R, Loraine AE, Dickerson JA: Comparisons of computational methods for differential alternative splicing detection using RNA-seq in plant systems. BMC Bioinformatics 15:364, 2014 57. Jayasinghe RG, Cao S, Gao Q, et al: Systematic Analysis of Splice-Site-Creating Mutations in Cancer. Cell Rep 23:270-281 e3, 2018 58. Jian X, Boerwinkle E, Liu X: In silico tools for splicing defect prediction: a survey from the viewpoint of end users. Genet Med 16:497-503, 2014 59. Soreq L, Guffanti A, Salomonis N, et al: Long non-coding RNA and alternative splicing modulations in Parkinson's leukocytes identified by RNA sequencing. PLoS Comput Biol 10:e1003517, 2014 60. Ernst C, Morton CC: Identification and function of long non-coding RNA. Front Cell Neurosci 7:168, 2013 61. Niland CN, Merry CR, Khalil AM: Emerging Roles for Long Non-Coding RNAs in Cancer and Neurological Disorders. Front Genet 3:25, 2012 62. Gao Y, Wang H, Zhang H, et al: PRAPI: post-transcriptional regulation analysis pipeline for Iso-Seq. Bioinformatics 34:1580-1582, 2018 63. Han S, Kim D, Kim Y, et al: CAS-viewer: web-based tool for splicing-guided integrative analysis of multi-omics cancer data. BMC Med Genomics 11:25, 2018
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Figure 1. Roles of RNA splicing events and RNA splice variants in precision oncology.
Genetic variation in cis-acting splicing elements in different populations can result in
expression of alternative RNA splice variants, as exemplified by pre-mRNA #1. Some of
these can be oncogenic RNA splice variants that pre-exist in normal cells and persist in
cancer cells, as exemplified by pre-mRNA #1. Alterations that occur during
transformation e.g. differential expression of trans-acting splicing factors can result in
oncogenic RNA splice variants that arise de novo in cancer cells, as exemplified by pre-
mRNA #2. Such RNA splicing events and RNA splice variants can be biomarkers,
therapeutic targets and/or neoantigens. Ultimately, such RNA splicing events and RNA
splice variants can influence cancer aggressiveness and drug response. Solid lines
within pre-mRNAs, RNA splicing patterns. E, exon. I, intron. Joined Es depict RNA
splice variants and schematics below joined Es depict corresponding encoded protein
isoforms. Gray oval, nucleus. Red letters, single nucleotide polymorphism in cis-acting
splicing element. SF, trans-acting splicing factor. SSOs, splice-switching
oligonucleotides.
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GTGG
GTGG GTGG
Normal Cell in Ancestral Population 1
E1 E3 E2
SF1 SF2 GTGG
GTAG GTAG
Normal Cell in Ancestral Population 2
E1 E3
E1 E2 E3 E4 I1 I2 I3
pre-mRNA
#1
SF1 SF2
E1 E2 E3 E4 I1 I2 I3
pre-mRNA
#1
E1 E2 E3 E4 I1 I2 I3
pre-mRNA
#2
E1 E3 E2 E4
E1 E2 E3 E4 I1 I2 I3
pre-mRNA
#2
E4 E1 E3 E2 E4 E4
Figure 1
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Tumor Cell in Ancestral Population 2
GTGG
GTAG GTAG
E1 E3 E4
E1 E2 E3 E4 I1 I2 I3
pre-mRNA
#1
SF1 SF2
E1
E1 E2 E3 E4 I1 I2 I3
pre-mRNA
#2
SF2
Tumor cells have different aggressiveness and drug response depending
on RNA splice variants/corresponding protein isoforms expressed
RNA-Targeted
Therapeutics
(SSOs, small
molecules)
Tumor Cell in Ancestral Population 1
Protein-
Targeted
Therapeutics
(small
molecules)
GTGG
GTGG GTGG
E1 E3 E2
SF1
SF2
E1 E2 E3 E4 I1 I2 I3
pre-mRNA
#1
E1 E2 E3 E4 I1 I2 I3
pre-mRNA
#2
E1 E2 E4
SF1
CD8+
T Cell
Neoantigens
Biomarkers
Biomarkers
E4 E4
Figure 1
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Published OnlineFirst February 12, 2019.Clin Cancer Res Timothy J Robinson, Jennifer A Freedman, Muthana Al Abo, et al. DisparitiesUntapped Molecular Targets in Precision Oncology and Cancer Alternative RNA Splicing as a Potential Major Source of
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