Theses and Dissertations Graduate School 2015 The Role of SRSF3 in Control of Alternative Splicing of CPEB2 in Triple Negative Breast Cancer Brian P.. THE ROLE OF SRSF3 IN CONTROL OF A
Background
Cancer
Cancer is a devastating disease that affects millions of Americans each year In 2014, 1,665,540 Americans were diagnosed with some form of cancer [1] Cancer ranks second only to heart disease in cancer-related deaths, taking a heavy toll every year The National Cancer Institute reports that 35.2% of patients diagnosed with cancer die annually [1].
2014, cancer accounted for 585,720 deaths in the United States [1] Cancer’s high mortality rate is due to the heterogeneity of tumors and the lack of effective treatment methods
Breast cancer is the most commonly diagnosed cancer in the United States, with about 235,030 new cases in 2014, and it remains the third leading cause of cancer deaths, totaling around 40,430 fatalities that year As treatments have advanced, mortality and recurrence rates have fallen, but a cure has not yet been found, leaving room for further progress As of 2011, the breast cancer mortality rate among diagnosed patients receiving treatment was 17.2%, while the five-year survival rate stood at 91.8%, indicating that many tumors metastasize or develop resistance to current therapies The subtypes most resistant to treatment are triple-negative breast cancer (TNBC) and HER2-positive breast cancer, both of which are highly metastatic and lack widely effective targeted options.
Figure 1-1 Cancer diagnoses and deaths in 2014 According to the National Cancer
Breast cancer is the most commonly diagnosed cancer subtype, with 235,030 new cases reported in 2014 It is the third leading cause of cancer deaths, with 40,430 deaths attributed to breast cancer in 2014 Source: SEER 2014 [1].
Breast cancer is the most commonly diagnosed cancer in the United States and is responsible for the third-highest number of cancer-related deaths each year The five-year survival rate for breast cancer is 91.8%, signaling strong outcomes but still leaving room for improvement Table 1-1 provides a comparative view of diagnoses, deaths, and survival rates for breast cancer alongside four other major cancers, drawing on SEER 2014 data.
Metastasis—the spread of cancer to distant areas of the body—is one of cancer's most dangerous features and a major source of treatment challenge Even with successful surgical resection of the primary tumor, metastatic cancer can persist and complicate outcomes, highlighting the need for systemic therapies and ongoing monitoring.
Metastasis unfolds in five general stages First, the primary tumor grows and locally invades surrounding tissues, accumulating mutations that promote growth and cell-cycle progression Second, tumor cells intravasate into the circulation; many undergo epithelial-to-mesenchymal transition (EMT) to enable anchorage-independent survival, while detachment from the extracellular matrix triggers anoikis unless cells acquire mutations that resist apoptotic signaling Third, the cells migrate to distant sites and extravasate by penetrating the walls of capillaries into the surrounding tissue Fourth, the disseminated cells undergo mesenchymal-to-epithelial transition (MET) to support growth in the new, anchorage-dependent environment Fifth, colonization follows as these cells establish a growing secondary tumor by proliferation.
Cancer metastasis progresses through five stages: growth, intravasation, migration, extravasation, and colonization Growth involves the primary tumor enlarging at its original site until it accumulates mutations that enable spread Intravasation occurs when tumor cells detach from surrounding tissue, undergo epithelial-to-mesenchymal transition (EMT), and enter the circulatory system Migration describes cancer cells traveling through the body's vasculature to distant sites, followed by extravasation, where they exit the bloodstream and invade new tissue Finally, colonization takes place as disseminated cells undergo mesenchymal-to-epithelial transition (MET) and establish anchored growth at distant locations.
Triple-negative breast cancer (TNBC) is an aggressive subtype defined by the lack of estrogen, progesterone, and HER2 receptor expression, which limits targeted therapy options Although TNBC accounts for only about 15–20% of all breast cancers, it is responsible for nearly 70% of breast cancer deaths due to recurrence and resistance to standard therapies These stark numbers underscore a critical clinical need to develop more effective treatments and to improve outcomes for patients with this challenging disease.
Data analyses indicate that triple-negative breast cancer (TNBC) carries a hazard ratio of 4.35 for mortality relative to standard breast cancer, signaling a substantially higher mortality risk Because TNBC lacks a specific, unique drug target, treatment options are typically broad-spectrum and less targeted in efficacy Common treatment strategies for TNBC include anthracyclines, taxanes, ixabepilone, platinum-based agents, select biological agents, and anti-EGFR therapies.
Triple-negative breast cancer (TNBC) initially appears to respond to treatment, but patients often face a worse long-term prognosis TNBC tumor cells seem able to develop metastatic traits that help them escape complete eradication by standard therapies Although breast cancer overall has a 5-year survival rate of 91.8%, TNBC patients exhibit only about a 30.0% 5-year survival rate, highlighting a dramatic need for clinical improvement and targeted therapy development.
Several commonly used in vitro models of triple-negative breast cancer (TNBC) rely on human tumor cell lines such as MDA-MB-231, MDA-MB-468, BT-549, and SUM1315 Derived from patient tumors, these lines are cultured to preserve the biological characteristics of the original cancers Researchers frequently combine these in vitro systems with mouse models to assess how TNBC cells respond to various treatments and to study metastatic potential In vivo mouse models provide whole-organism context, allowing controlled observation of metastasis and systemic drug effects Together, these preclinical models generate data on therapeutic efficacy and metastasis that can inform the translation of promising candidates into human clinical trials.
1.1.3 HER2/ErbB2 Positive Breast Cancer
HER2-positive breast cancer, like triple-negative breast cancer (TNBC), remains hard to treat because of its aggressive and metastatic nature These tumors overexpress the membrane protein ErbB2/HER2, a trait linked to poorer patient prognoses The National Cancer Institute reports a hazard ratio of 3.60 for HER2-positive breast cancer, ranking it as the second most dangerous breast cancer subtype.
Overexpression of ErbB2/HER2 causes accumulation at the plasma membrane and chronic activation of survival signaling pathways, including Src, STAT3, PI3K, and MAPK This sustained signaling promotes metastatic traits such as enhanced proliferation, survival, motility, and tissue invasion A key factor is the recycling of activated ErbB2 back to the plasma membrane rather than lysosomal degradation, which maintains continuous signaling The incomplete understanding of this mechanism presents a challenge for developing effective targeted therapies.
To gain a greater understanding of HER2-positive breast cancer, researchers have developed multiple models and repurposed numerous patient samples as cellular models, including established lines such as SKBR3 and MDA-MB-453 These HER2-overexpressing cell lines typically do not express estrogen or progesterone receptors, resulting in ER-negative and PR-negative status with high ErbB2/HER2 expression Similar to TNBC models, HER2-positive cell lines are often combined with animal models to study systemic metastasis, using in vivo approaches such as tumor xenografts or tissue-specific injections to model disease progression.
Alternative mRNA Splicing
Alternative RNA splicing expands protein diversity within a single cell by allowing RNA sequences to be altered through the selective inclusion or exclusion of exons at specific splice sites, leading to multiple isoforms of the same protein These isoforms can have a wide range of cellular functions despite sharing sequence similarities Splice sites act as binding regions for the spliceosome, the protein complex that generates the mature, spliced mRNA sequence.
Splicing site selection is controlled by the actions and interactions of cellular splicing factors with RNA sequences Splicing factors are RNA-binding proteins that recognize specific RNA motifs to guide enhancers or block silencers of the spliceosome, shaping which exons are included This regulation enables substantial genetic diversity from a relatively small genome by allowing alternative splicing to generate numerous protein variants As Guttmacher and Collins note, alternative splicing gives cells the ability to encode over 100,000 proteins from about 30,000 genomic bases.
Figure 1-3 Mechanism of Alternative Splicing During alternative splicing, gene exons are selectively incorporated to produce mature mRNA for translation into proteins
SR proteins act as exonic splicing enhancers that regulate the selection of alternative splice sites to promote exon inclusion in the final mRNA sequence They counteract hnRNP exonic splicing silencers, preventing them from promoting exon removal during mRNA processing Structurally, SR proteins consist of one or two N-terminal RNA recognition motifs (RRM) followed by a downstream arginine/serine-rich (RS) domain.
RS or SR repeats [11] The RRM provides substrate specificity of the particular SR protein with its target short mRNA splicer enhancer sequence [11] (Figure 1-4) As a result, each
SR proteins form selective interaction networks by binding to a specific set of partner proteins to promote defined cellular functions They participate in multiple levels of gene regulation, from RNA maturation and export to translation, positioning them as key regulators of post-transcriptional control Consequently, the SR protein family drives alternative splicing decisions and shapes downstream cellular signaling that influences cellular responses.
Figure 1-4 outlines the general structure of the SR protein family All SR proteins share a common architecture consisting of an N-terminal RNA-binding domain (RRM) and a C-terminal arginine/serine-rich (RS) domain The number and length of these domains vary among SR family members, contributing to the diversity of functional capabilities within the family.
SRSF3, also known as SRp20, is a member of the SR family of splicing factors Emerging evidence links SRSF3 to protein translation and mRNA polyadenylation, as well as a range of cellular pathways that regulate growth, epithelial–mesenchymal transition (EMT), and RNA processing Overexpression of SRSF3 is observed in various cancers, indicating a potential role in growth control Moreover, Jia and colleagues showed that elevated SRSF3 levels constitute a critical step for tumor initiation, progression, and maintenance.
High SRSF3 levels are positively associated with greater severity of mammary tumorigenesis, highlighting SRSF3 as a potential driver of cancer progression In contrast, reduced SRSF3 expression slows cell growth, increases sensitivity to anoikis, and promotes apoptosis in proportion to the extent of SRSF3 loss Dysregulation of SRSF3 has also been linked to the alternative splicing of p53, a pivotal tumor suppressor that is frequently mutated across cancers, suggesting SRSF3 participates in oncogenic pathways beyond mammary tumors Although the connection between SRSF3 and cancer is supported by multiple studies, the precise mechanism remains to be fully clarified.
Cytoplasmic Polyadenylation Element Binding Protein 2…
CPEB2, a member of the cytoplasmic polyadenylation element-binding (CPEB) protein family, regulates protein translation This family is defined by RNA recognition motifs and C-terminal zinc finger domains that enable specific interaction with U-rich mRNA elements By binding these mRNAs, CPEB2 drives complete polyadenylation of immature transcripts and promotes ribosome assembly by selectively recruiting eIF4F, a key factor required to initiate translation.
CPEB2 exhibits substrate specificity, directly engaging TWIST1 and influencing HIF1α through eEF2, linking CPEB2 function to key cancer-related pathways Given that TWIST1 and HIF1α are frequently mutated in cancers, this suggests a meaningful connection between CPEB2 activity and tumor biology CPEB mRNAs are downregulated in numerous tumor samples, indicating that cancer cells may lose the ability to regulate translation Hagele et al reported an inverse relationship between CPEB2 and HIF1α activation, hinting that CPEB2 could modulate HIF1α-driven malignancy, though this has not been experimentally confirmed Additionally, organ-specific patterns of CPE activation point to tissue-specific functionality of CPEB2.
Beyond its known downstream actions, researchers are exploring alternative roles for CPEB activation and its effects Di Nardo et al suggest that CPEB2 may promote polyadenylation after stimulation by the mTOR pathway The mTOR pathway is naturally activated by cellular stresses such as hypoxia or insulin Other studies indicate that CPEB activation can involve diverse phosphorylation pathways, including the phosphoinositide 3-kinase (PI3K)/GSK3 axis, aurora A kinase, and CDC2 signaling.
Wang et al show that CPEB2 generates multiple isoforms through exon inclusion in mature mRNA, reflecting alternative splicing These isoforms exhibit different substrate specificities and three-dimensional structures that drive distinct functions The A and B isoforms are the most common, with exon 4 included in CPEB2B Early data suggest that CPEB2B promotes metastatic activity in cells, contributing to highly aggressive tumors A deeper understanding of CPEB2 alternative splicing could lead to more effective patient therapies in the future.
Figure 1-5 illustrates the alternative splicing of CPEB2, with the two most common isoforms differing solely by whether exon 4 is included The inclusion or skipping of exon 4 defines the major splice variant, and the splicing factor that controls this regulation has not yet been identified.
Determination of CPEB2 Splicing Factor
Introduction
Although extensive research has unraveled many mechanisms driving cancer and metastasis, key questions remain A critical step in metastasis is anoikis resistance, which enables disseminated tumor cells to survive in the bloodstream and colonize distant sites, complicating surgical and other conventional treatments This has fueled clinical interest in strategies that limit a tumor’s ability to evade anoikis An emerging but underexplored avenue is the study of alternative splicing in signaling molecules, since upstream pathways that regulate splicing may influence metastatic potential By mapping how these pathways control splicing in cancer, researchers may identify ways to modulate splicing and prevent metastasis.
Our laboratory studies reveal that cytoplasmic polyadenylation element binding protein 2 (CPEB2) promotes a metastatic phenotype in triple-negative breast cancer (TNBC) We show that CPEB2 splicing is altered in TNBC patients, producing a higher abundance of the larger CPEB2 isoform B.
Recent findings indicate that CPEB2B promotes cell proliferation when endogenously expressed in MDA-MB-231 parental cells, whereas CPEB2A does not produce the same growth effect Targeting CPEB2B splicing to prevent its expression emerges as a highly promising anti-metastatic cancer strategy Given its low basal expression in non-tumorigenic cells, CPEB2-based therapies could selectively affect cancer cells, highlighting substantial therapeutic potential and warranting further research.
Materials and Methods
The lab obtained MDA-MB-231 parental TNBC cells (231 Par) from ATCC and cultured them in RPMI 1640 (Invitrogen) supplemented with 10% fetal bovine serum (Invitrogen) and 1% penicillin/streptomycin (BioWhittaker) at 5% CO2 and 37°C When 231 Par cells reached approximately 70% confluence, they were passaged up to a maximum passage number of 9 Anoikis-resistant MDA-MB-231 TNBC cells (231 AnR) were generated by plating 231 Par cells on 10 cm dishes coated with 20 mg/mL poly(2-hydroxyethyl methacrylate) (polyHEMA) for at least 3 passages on polyHEMA-coated plates.
To identify splicing factors that regulate the alternative splicing of CPEB2, we targeted exon 4 interactions, the exon included in the CPEB2B isoform We prepared nuclear extracts from 231 AnR cells under standard culture conditions and added either specific or non-specific competitor sequences as loading controls The samples were then combined with FITC-conjugated exon 4 of CPEB2, and the resulting complexes were analyzed on a DNA polyacrylamide gel until bands appeared; the visible bands were excised and sent to The Ohio State University Proteomics Core for analysis to determine their interactions with known splicing factors The resulting list of interacting proteins was examined using online protein databases to identify potential splicing factors for experimental validation.
Candidate splicing factors were experimentally tested for their impact on CPEB2 alternative splicing Silencer siRNA (Ambion by Life Technologies) targeting SRFS3, hnRNPA2B1, hnRNPF, and hnRNPH1 was reconstituted to 20 µM 231 Par cells (2 × 10^5) were plated in 6-well plates in the appropriate medium siRNA was added at 25 nM following the DharmaFECT protocol After 6 hours, the medium was replaced, and cells were harvested 48 hours post-transfection to ensure maximal siRNA effect.
Bradford Reagent (Bio-Rad) was used to determine protein concentration to ensure consistent loading for gel runs, with 10 µg of each sample loaded onto a 7.5% polyacrylamide gel and run at 60 mV for 3 hours in 1X Tris/Glycine/SDS buffer The gel was then transferred to PVDF membranes for 2 hours in transfer buffer (70 H2O:20 MeOH:10 10X Tris/Glycine Buffer) After transfer, membranes were blocked in 5% milk for 30 minutes at room temperature and washed 3 times in wash buffer (1X PBS + 0.1% Tween-20) Primary antibodies diluted in 5% milk (Actin 1:8000, SRSF3 1:1000, CPEB2 1:1000) were incubated overnight at 4°C The following morning, membranes were washed 3 times in wash buffer and incubated with the appropriate secondary antibodies (Actin-Mouse 1:8000, SRSF3-Rabbit 1:1000, CPEB2-Rabbit 1:1000) for 1 hour at room temperature Finally, membranes were washed and developed with SuperSignal Pico Developing Solution reagents (Thermo) and imaged using a film developer.
Results
After determining that alternative splicing of CPEB2 affects the metastatic potential of triple-negative breast cancer cells, the next step was to identify the splicing factors that govern this action To do this, we ran samples on a DNA polyacrylamide gel as described in 2.2.2 and selectively excised distinct gel bands (Figure 2-1) Results from The Ohio State University provided a list of proteins that bind to exon 4 of CPEB2—the exon alternatively spliced between the A and B isoforms—offering numerous candidates interacting with the region of interest While many candidates were recognized as artifacts of the proteomics screen and discounted, the remaining factors to examine were SRSF3, hnRNP A2B1, hnRNP A0, hnRNP F, and hnRNP H1; all are known splicing factors that have been shown to be dysregulated in cancer These results directed our studies to investigate the specific roles of those factors in MDA-MB-231 cell metastasis.
Figure 2-1 illustrates that EMSA can selectively identify exon 4 binding factors Nuclear extracts from 231 AnR cells were incubated with FITC-conjugated exon 4 of CPEB2, and the mixture was resolved on a DNA polyacrylamide gel until discrete bands appeared Each band was excised and sent to The Ohio State University for proteomics analysis to characterize the exon 4–binding proteins.
F IT C -C PB+ N SC F IT C -C PB + S C
To explore the role of a splicing factor in CPEB2 alternative splicing, we performed siRNA knockdown of each candidate factor and assessed changes in CPEB2 splice variant abundance Using siRNA cocktails specific to individual factors, and combining siRNAs for hnRNP H1 and hnRNP F due to reported cooperative effects, we observed a pronounced reduction in the CPEB2 B isoform when SRSF3 was targeted, while other siRNAs produced no significant effect on CPEB2 splicing Comparing the A:B splice variant ratios provides a clear visualization of SRSF3 knockdown effects on CPEB2 alternative splicing, as the relative abundance of the pro-growth B isoform decreases and the A:B ratio increases, with high A:B samples being less metastatic and more amenable to treatment Collectively, the results suggest that SRSF3 mediates CPEB2 alternative splicing and promotes the production of the pro-survival B isoform.
Figure 2-2 shows the siRNA panel for CPEB2 alternative splicing In this experiment, 231 Par cells were treated with 25 nM siRNA for 6 hours, after which the medium was replaced Forty-eight hours later, cells were harvested and analyzed by Western blot to detect CPEB2 isoforms Densitometry was performed on the A and B isoforms, as indicated by arrows, and the resulting densitometry ratios were calculated for each sample.
N o T rea tm en t s iRNA Co n tr o l s i SR SF 3 s i h n RNP H1 s i h n RNP F s i h n RNP H1
Following the siRNA screen, we confirmed that knockdown of SRSF3 alters alternative splicing in both 231 Par and 231 AnR cell lines As shown in Figure 2-3, SRSF3 silencing reduces the B isoform and thereby increases the A:B ratio in these samples Notably, 231 Par cells exhibit a higher basal A:B ratio than 231 AnR cells, and the difference is more pronounced in 231 Par because of their naturally lower B isoform levels This pattern is consistent with the metastatic nature of the 231 AnR cell line.
To determine whether the enhanced metastatic phenotype of 231 AnR cells is linked to SRSF3 expression, we compared SRSF3 levels in 231 Par and 231 AnR lines Figure 2-4 shows that 231 AnR cells overexpress SRSF3 relative to 231 Par cells Importantly, siSRSF3 treatment markedly reduces SRSF3 in both lines, restoring the SRSF3 level in 231 AnR cells to the basal level observed in 231 Par cells, indicating that alterations in SRSF3 occur during the acquisition of anoikis resistance in these cell lines.
To optimize SRSF3 knockdown and maximize the observed cellular effects, we evaluated the three siRNA components of the purchased cocktail individually to determine which provided the strongest reduction of SRSF3 expression Knockdown was quantified by densitometry comparing SRSF3 to Actin As shown in Figure 2-5, the second and third siRNA components produced the greatest reduction in SRSF3 expression and the lowest SRSF3:Actin ratio Consequently, future experiments used a combination of these siRNAs.
Figure 2-3 Knockdown of SRSF3 Causes Decrease in CPEB2B 231 Par and 231
AnR cells were treated with siRNA (25 nM) for 6 hours, then media was replaced After
Samples were collected at 48 hours and analyzed by Western blot to detect CPEB2 isoforms Densitometric analysis quantified the A and B isoforms of CPEB2, and A:B ratios were calculated for each sample and then averaged within each treatment group to assess differences across conditions.
Par AnR s iCo n 1 s iCo n 2 s iCo n 2 s iCo n 1 si SR SF 3 1 si SR SF 3 1 si SR SF 3 2 si SR SF 3 2
Figure 2-4 shows that SRSF3 is upregulated in anoikis-resistant (AnR) cells compared with parental (Par) cells In this experiment, 231 Par and 231 AnR cells were treated with 25 nM siRNA for 6 hours, after which the medium was replaced Forty-eight hours later, cells were collected and subjected to Western blot analysis to assess SRSF3 knockdown.
Figure 2-5 Selective Components of siSRSF3 Promote Greatest SRSF3 Reduction
In 231 Par cells, individual siRNA components at a concentration of 25 nM were applied for 6 hours, after which the culture medium was replaced Forty-eight hours post-treatment, cells were collected and analyzed by Western blot to assess knockdown of SRSF3.
SRSF3 s iCo n tro l s iSR SF 3 - 1 s iSR SF 3 - 3 s iSR SF 3 - All s iSR SF 3 - 2
Discussion
Analysis of our results provides insight into the mechanisms altered in triple-negative breast cancer Among a panel of candidate splicing factors, SRSF3 was found to regulate the alternative splicing of CPEB2 and to promote expression of the metastatic CPEB2B isoform The association is reinforced by higher SRSF3 levels in anoikis-resistant cells, indicating SRSF3's role in driving metastatic behavior These findings outline potential directions for future research and identify SRSF3—and the resulting CPEB2 isoform balance—as a viable target; therapies that modulate SRSF3 activity could offer an effective complement to existing cancer treatments.
Initial observations showed that CPEB2 alternative splicing is altered in cancer, guiding investigation; now that SRSF3 is known to control this interaction, additional research directions emerge The most important next step is to determine whether reducing SRSF3 expression translates to a measurable change in the metastatic phenotype, which can be assessed by examining cell growth or resistance to apoptosis For growth, use proliferation assays or measure cell doubling times in culture To evaluate resistance to apoptosis, employ Western blot analysis of apoptotic markers such as caspase-3, caspase-8, cleaved PARP, and cytoplasmic cytochrome c; flow cytometry with Annexin-V and 7-AAD; luciferin-based fluorescence assays; or post-apoptosis colonization assays.
Measuring Metastatic Effect of SRSF3
Introduction
Building on the observation that SRSF3 regulates CPEB2 alternative splicing in triple-negative breast cancer (TNBC), we next explored whether reducing SRSF3 triggers broader changes in cellular function In the absence of an in vivo model, we leveraged in vitro approaches that yield rapid results and avoid the complexities of animal experiments Consequently, we employed flow cytometry and Western blot assays to assess the metastatic function of cells with reduced SRSF3.
Materials and Methods
MDA-MB-231 parental triple-negative breast cancer (TNBC) cells (231 Par) were obtained from ATCC and cultured in RPMI 1640 with 10% fetal bovine serum and 1% penicillin/streptomycin, at 37°C in a 5% CO2 incubator When the 231 Par cells reached 70% confluence, they were passaged with a maximum passage number of 9 Anoikis-resistant MDA-MB-231 TNBC cells (231 AnR) were obtained by plating.
231 Par cells on 10cm 2 culture dishes coated with 20 mg/mL poly(2-hydroxyethyl methacrylate) (polyhema) (Sigma-Aldrich) for at least 3 passages on polyhema-coated plates
3.2.2 Flow cytometry anoikis resistance assay
To assess the effect of SRSF3 knockdown on TNBC cell resistance to anoikis, multiple 231-derived cell lines (parental 231 Par, anoikis-resistant 231 AnR, 231 pcDNA, and 231 CPB) were treated with siRNA targeting SRSF3 or a non-targeting control, then re-plated onto either untreated or polyHEMA-coated surfaces to induce detachment After an overnight incubation, cells and conditioned media were collected for downstream analyses to evaluate survival under nonadherent conditions and related phenotypes.
To analyze cell death by flow cytometry, we resuspended and washed the cells in 1X Binding Buffer (eBioscience) The pellet was then resuspended in staining buffer (1X Binding Buffer, 7-AAD, and Annexin-V), and the samples were kept on ice during staining.
Fifteen minutes after staining, the reaction was neutralized by adding additional 1X Binding Buffer On ice, the samples were brought to the VCU Flow Cytometry Core Samples were gated by Forward Scatter and Side Scatter detectors, then grouped into regions based on the 7-AAD and Annexin-V signals Each sample was run in triplicate, and the data were analyzed statistically using ANOVA.
Results
3.3.1 Flow Cytometry Anoikis Resistance Assay
To evaluate the effects of SRSF3 knockdown in TNBC cells, we first quantified the fraction of cells undergoing apoptosis after plating on polyhema-coated plates (Figure 3-1) This setup induces anoikis, a detachment-induced cell death seen in normal cells Cells harboring metastasis-promoting mutations may not be positive for 7-AAD or Annexin-V because they have developed resistance to anoikis.
7-AAD is a fluorescent dye that binds to double-stranded DNA, marking cells with compromised plasma membrane integrity during late apoptosis when DNA is released Annexin-V is a fluorescent dye that binds to phosphatidylserine, which is normally located on the cytosolic side of the plasma membrane but becomes externally exposed when flippase activity stops during apoptosis Together, these signals identify apoptotic cells and provide a measure of cell viability By gating on both 7-AAD and Annexin-V signals, we can determine the percentage of the cell population undergoing apoptosis (Figure 3-2).
Figure 3-1 outlines the Metastatic Effect Experimental Workflow To study cell resistance to apoptosis, we developed a method to accurately measure the influence of SRSF3 on anoikis In the schematic, 231 Par or 231 AnR cells are plated in a 6-well plate at 2 × 10^5 cells per well After 24 hours, the cells are transfected with siRNA.
Apoptosis is induced by treating cells with 25 nM for 6 hours, after which the media is replaced After an additional 24 hours, the cells are transferred to poly-HEMA-coated plates to stimulate apoptosis Depending on the apoptotic stage under study, cells can be collected after 3–6 hours for early apoptosis or after 18–24 hours for late apoptosis.
Transfer to polyhema coated plates
Analyze cell death via flow cytometry
Figure 3-2 shows a representative flow cytometry plot used to quantify the proportion of a collected cell population expressing specific fluorescent markers In this plot, Annexin-V on the x-axis indicates early apoptosis, while 7-AAD on the y-axis marks late apoptosis or necrosis Gates are configured to distinguish apoptotic cells (Q2 and Q3) from living cells (Q1 and Q4), and comparing the proportions of these populations reveals resistance to apoptosis in the sample.
Following the protocol as described in section 3.2.3, we first looked at 231 Par and
In an experiment with 231 AnR cells treated with either control siRNA (siCon) or siRNA targeting SRSF3 (siSRSF3), apoptotic populations revealed several key findings: first, 231 Par cells showed higher basal apoptosis when grown on poly-HEMA-coated plates, consistent with their transformation history toward the 231 AnR phenotype; second, knockdown of SRSF3 increased cell death in both the 231 Par and 231 AnR lines, indicating that SRSF3 contributes to anoikis resistance in TNBC cells; and finally, silencing SRSF3 restored the anoikis sensitivity of 231 AnR cells to the level seen in parental 231 Par cells, suggesting that alteration of SRSF3 may have been one of the mutations acquired during the development of the 231 AnR cell line.
Figure 3-3 shows that reduction of SRSF3 increases sensitivity to anoikis Cell populations were quantified by flow cytometry across experimental groups, with apoptosis assessed using 7-AAD and Annexin-V markers Gates were set to include populations with sufficient signal, and cells exceeding the gating threshold for both Annexin-V and 7-AAD were counted as apoptotic The data presented are representative of three independent experiments (n = 3), and error bars denote ±1/2 standard deviation.
Discussion
Looking into the effects of knocking down SRSF3 in metastatic TNBC cells provided us with some very interesting insights into signaling pathways altered in cancer
These data demonstrate that SRSF3 modulates the alternative splicing of CPEB2, but this finding only translates to a potential therapeutic target if it can be leveraged for patient treatment To test this, we used siRNA to knock down SRSF3 in TNBC cell models and assessed how changing SRSF3 levels affects metastatic behavior Across several assays, SRSF3 reduction altered metastatic function and increased cellular sensitivity to apoptosis Conversely, cells that are more resistant to apoptosis tend to overexpress SRSF3, indicating that SRSF3 contributes to anoikis resistance and may represent a target for overcoming metastasis in TNBC.
Our data indicate that anoikis resistance arises through the alternative splicing of CPEB2 to the more metastatic isoform, CPEB2B Yet endogenous CPEB2B expression did not alter anoikis resistance in our experiments, so we hypothesize that SRSF3 drives this effect by promoting inclusion of exon 4 in CPEB2 This inclusion enables CPEB2B to activate cellular signaling that promotes enhanced cellular growth and inhibits apoptotic signaling The precise mechanism remains unknown and will be explored in future studies.
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