SGPL1 Deficiency Get Involved in Imatinib Resistance via PI 3 K-Akt signaling pathway in gastrointestinal stromal tumor

SGPL1 Deficiency Get Involved in Imatinib Resistance via PI 3 K-Akt signaling pathway in gastrointestinal stromal tumor | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article SGPL1 Deficiency Get Involved in Imatinib Resistance via PI 3 K-Akt signaling pathway in gastrointestinal stromal tumor Jie Wang, Zhen Xu, Yu Wang, Xiaoyan Wang, Ning Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6647302/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor in the gastrointestinal tract. In recent years, secondary resistance to the first-line drug imatinib has become its bottleneck of targeted therapy due to the unclear mechanism. It has important clinical significance for breaking through the bottleneck by screening and identifying the critical gene of imatinib resistance. Unbiased in vivo genome-wide genetic screening is a powerful approach to elucidate new molecular mechanisms. Here the genome-scale CRISPR/Cas9 Knockout Screening was applied to investigate imatinib resistance genes in GIST 882 cell line for two rounds, and it was found that deficiency of sphingosine 1-phosphate lyase coding gene SGPL1 can inhibit tumor cell apoptosis and accelerate cell cycle G1/S, finally leading to imatinib resistance in vitro and in vivo, by regulating the expression of Bcl-2, p27kip1 and p15INK4B via PI 3 K-Akt signaling pathway. In additionally, non-synonymous mutation in the exon of SGPL1 gene has been found by comparing the TCGA clinical drug resistance patient database. It was revealed that SPGL1 gene may be the critical gene of imatinib resistance. Taken together, our study provides a resource for achieving a deep understanding of the molecular basis of imatinib resistance. Biological sciences/Cell biology Biological sciences/Molecular biology Biological sciences/Cancer Biological sciences/Cancer/Cancer screening Biological sciences/Cancer/Cancer therapy Imatinib Resistance Gastrointestinal stromal tumor The genome-scale CRISPR/Cas9 Knockout Screening SGPL1 Bcl-2 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Gastrointestinal stromal tumors (GISTs), originating from Cajal cells in soft tissues, represent the most prevalent mesenchymal tumors within the digestive system. These tumors demonstrate a spectrum of biological behaviors and carry malignant potential [ 1 ] . The global annual incidence of GIST is estimated to be 10–15 per million individuals [ 2 , 3 ] . GISTs may develop at any site within the gastrointestinal tract, with the stomach (60–70%) and small intestine (20–25%) being the most frequent locations [ 5 , 6 ] . The absence of distinctive clinical manifestations, presenting only symptoms such as gastrointestinal bleeding, abdominal mass, discomfort, and pain, combined with pathological features akin to gastrointestinal spindle cell tumors lacking smooth muscle and neural differentiation, results in GISTs being frequently misdiagnosed or overlooked. Over the past two decades, enhanced understanding of pathogenesis has revealed that GISTs are primarily induced by mutations in the c-KIT gene and the platelet-derived growth factor receptor alpha (PDGFRA) gene [ 7 – 9 ] . Consequently, clinical diagnosis and treatment protocols have become increasingly standardized. Guidelines for the diagnosis and treatment of GIST have been developed and updated by the National Comprehensive Cancer Network and the European Society for Medical Oncology. Similarly, the Chinese Society of Clinical Oncology has issued an expert consensus on GIST, noting that targeted therapy remains the sole effective treatment for patients with advanced primary tumors ineligible for surgery, as well as those experiencing postoperative recurrence, metastasis, or facing recurrence risk [ 10 ] . Tyrosine kinase inhibitors , recognized as the initial targeted drugs utilized in GIST treatment, competitively bind to the intracellular domain of tyrosine kinase by vying with adenosine triphosphate, thereby obstructing downstream signal transduction pathways such as JAK-STAT3 and RAS-MEK-ERK. This mechanism effectively suppresses tumor cell growth, proliferation, and metastasi [ 11 – 13 ] . Imatinib, a tyrosine kinase inhibitor, is recognized as a first-line targeted drug that has shown considerable efficacy in early clinical applications. Patients have achieved complete or partial remission, with a median progression-free survival (PFS) of 20–24 months and a median overall survival of five years [ 14 ] . However, with the progression of treatment, drug resistance has become increasingly prominent, emerging as a significant bottleneck limiting the efficacy of targeted therapy for GIST. Clinical data suggest that 10–20% of patients develop primary resistance within the first six months of imatinib treatment. Additionally, within 1–3 years of treatment, 40–50% of patients experience secondary resistance, with the incidence of secondary resistant cases rising by 10% annually [ 15 – 17 ] . Primary resistance mechanisms are mainly attributed to the wild-type (WT) c-KIT gene and the PDGFRA D842V mutation, whereas the mechanisms underlying secondary resistance remain unclear. Some studies have indicated that resistance in certain patients is due to secondary mutations in exons 13, 14, 17, or 18 of the c-KIT gene during treatment, resulting in structural changes in the intracellular segment of tyrosine kinase, which prevent imatinib from binding and exerting its therapeutic effect [ 18 , 19 ] . Other research proposes that in some resistant patients, the c-KIT gene does not undergo secondary mutations; instead, prolonged stimulation by imatinib leads to upregulation of hypoxia-inducible factor HIF1α expression, which promotes tumor cell proliferation and inhibits apoptosis by regulating the activity of phosphogluconate dehydrogenase [ 20 ] . Furthermore, additional studies have identified that imatinib resistance is associated with non-coding RNAs, such as LncRNA HOTAIR, which induces resistance by modulating the miR-130a/ATG2B signaling pathway [ 21 ] . Following the onset of imatinib resistance, the standard strategy involves increasing the drug dosage to sustain its efficacy. Upon reaching the maximum daily dose of 800 mg, if symptoms persist or the dose is not well-tolerated, patients are generally transitioned to second-line sunitinib or third-line regorafenib. Although sunitinib can mitigate the condition to a degree, its PFS remains relatively short, with a median of 5.6 months, and its objective response rate is comparatively low (6.8%). Additionally, the side effects of sunitinib are more severe than those of imatinib, commonly manifesting as fatigue, diarrhea, nausea, hand-foot syndrome, hypertension, neutropenia, thrombocytopenia, and anemia [ 22 ] . Regorafenib is also associated with significant toxic side effects [ 23 ] . The limited overall survival benefit and adverse reactions linked to second- and third-line drugs constrain their long-term clinical application [ 24 , 25 ] . In light of this scenario, identifying key genes responsible for imatinib resistance and delving into their resistance mechanisms, along with exploring methods to reverse the resistance, is of considerable clinical significance for enhancing the efficacy of imatinib treatment and improving the prognosis of GIST patients. Traditional approaches to investigating drug resistance genes mainly encompass the drug concentration gradient doubling method and the patient-derived tumor xenograft model. The former entails the creation of a gene mutation cell model via drug induction. Despite its simplicity, this method requires a prolonged modeling period of approximately 6–12 months, leading to low efficiency and limited genetic data acquisition. Conversely, the latter method, although it preserves the genetic characteristics of primary tumors more effectively, fails to accurately represent the comprehensive drug-resistance gene profile due to tumor heterogeneity and individual genetic variations among patients. Therefore, the research objectives of this project are as follows: Firstly, a CRISPR/Cas9 whole-genome library will be employed to screen the entire genome of GIST 882 cells. This library comprises 123,411 sgRNAs targeting 19,050 coding genes and 1,864 miRNAs within the GIST 882 cell genome. Post-imatinib treatment, the surviving cells, presumed to be enriched with drug-resistant genes, will be harvested for high-throughput sequencing and bioinformatics analysis to identify differentially expressed drug-resistant candidate genes. Secondly, the functions of these drug-resistant candidate genes will be validated both in vitro and in vivo, and their resistance mechanisms will be further investigated. These findings, in conjunction with The Cancer Genome Atlas Program (TCGA) database, will be used to identify mutation sites of the drug-resistant genes. Method Amplification of the CRISPR-Pool TM KOUT library plasmid (1) Preparation of Escherichia coli DH5α competent cells A single Escherichia coli DH5α colony was selected and inoculated into 4 mL of antibiotic-free LB medium. The culture was incubated overnight at 37°C with shaking. The following day, the bacterial suspension was transferred to 3 mL of fresh antibiotic-free LB medium and cultured for an additional 12–14 h. Once the OD 600 reached around 0.5, the cultivation was halted. The bacterial suspension was subsequently placed in an ice-water bath for 30 min, followed by centrifugation at 4°C. After discarding the supernatant, the pellet was resuspended in 20 mL of pre-chilled ddH 2 O. This process was repeated, and the final pellet was resuspended in 20 µL of ddH 2 O, forming the competent cells. (2) Transformation of Escherichia coli DH5α competent cells To 30 µL of freshly prepared competent cells, 1 µL each of CRISPR library plasmids A and B (hGeCKOa and hGeCKOb) were added, and the mixture was placed in an ice-cold water bath for 10 min. The competent cells were then transferred to pre-chilled electroporation cuvettes for electroporation transformation. Post-transformation, incubation of the cells was carried out at room temperature with shaking for 1 h. Following this, 10 µL of the transformed cells was plated and incubated for 14 h. The next day, the resultant colonies were harvested and cultured with shaking at 37°C for another 14 h. (3) Extraction of library plasmids Using the PureLink Hipure Plasmid Miniprep Kit, the library plasmids hGeCKOa and hGeCKOb were extracted. Agarose gel electrophoresis was employed to observe the target bands, which were subsequently excised from the gel and recovered for sequencing. After this, 1 ml of bacterial culture was inoculated into 250 ml of LB liquid medium and incubated at 37°C with shaking for 14 h. The bacterial cells were then harvested. Extraction of plasmids was performed using the PureLink Hipure Plasmid Maxiprep Kit, followed by determination of plasmid concentration. Virus packaging HEK293 cells in the logarithmic growth phase were seeded at a density of 5 × 10 6 cells per 10 cm culture dish. Upon reaching a cell density of 80–90%, preparations for transfection were initiated. The complete culture medium was replaced 2 h before transfection. In tube A, 35 µL of transfection reagent was mixed with 1.25 mL of Opti-MEM™ Medium and incubated for 5 min. In tube B, hGeCKOa and packaging plasmids were combined in a 4:3 ratio with 1.25 mL of Opti-MEM™ Medium and incubated for 5 min. The contents of the two tubes were then gently mixed and incubated for 25 min before being added to the HEK293 culture dish. Eight hours later, the culture medium was replaced. After 48 h, the culture supernatant was collected, and the viral titer was determined. The packaging of the library plasmid hGeCKOb followed the same procedure. Transfected GIST 882 cells GIST 882 cells were seeded into culture dishes at a density of 5 × 10 6 cells per dish, across a total of 20 dishes. Two dishes were designated as the control group, receiving no viral addition. The following day, upon reaching a cell density of 50%, the culture medium was replaced with 5 ml of DMEM complete medium containing 10 µg/ml polybrene. After a 30-minute incubation period, 4 ml of culture medium and 1 ml of virus solution were added. The medium was replaced 24 h later. On the third day, puromycin selection was initiated. The surviving cells in the treatment group were deemed to have successfully integrated the sgRNA, and the multiplicity of infection (MOI < 0.3) was calculated. Determination of imatinib IC50 GIST 882 cells in the logarithmic growth phase were seeded into 96-well plates at a density of 6 × 10 3 cells per well. Following a 24-hour incubation, the medium was replaced with DMEM containing varying concentrations of imatinib (0, 20, 40, 60, 80, and 100 µg/ml). Each concentration was tested in triplicate wells. After a 48-hour exposure, the culture medium was removed, and 10 µl of CCK8 reagent in fresh medium was added to each well. The plates were then incubated in the dark for 4 h. Absorbance at 450 nm was measured, and the IC50 was calculated to establish the optimal imatinib concentration for treatment. Imatinib treatment GIST 882 WT cells and GIST 882 cells transduced with the sgRNA library were separately seeded at a density of 5 × 10 6 cells per dish. Imatinib was administered to both cell groups at a concentration of 40 µg/ml and maintained for a duration of 4 days. A control dish of GIST 882 cells transduced with the sgRNA library was left untreated. Upon complete apoptosis or death of GIST 882 WT cells, the surviving GIST 882 cells transduced with the sgRNA library were deemed to be a population enriched for imatinib-resistant genes. Cells from each group, along with the library plasmids, were subsequently collected for high-throughput sequencing. High-throughput sequencing analysis Clustering analysis and positive/negative gene screening were utilized to calculate RRA scores for the candidate drug resistance genes. From the top 50 ranked genes, ten genes associated with cell growth, proliferation, apoptosis, and drug resistance were selected for further screening. The sgRNA sequencing was conducted by Genewiz (Suzhou) Company. Establishment of stable GIST 882 cell lines with SGPL1 knockout/overexpression sgRNA sequences targeting SGPL1 were designed and inserted into the CRISPRlentiV2 vector to create the knockout plasmid for the drug resistance target gene. The overexpression sequence of SGPL1 was designed and inserted into the pCDH-CMV-EF1-mcherry vector to generate the overexpression plasmid. Both constructs were verified by sequencing. Lentiviruses were packaged, and the SGPL1 knockout and overexpression plasmids were transduced separately into GIST 882 cells to establish stable cell lines with SGPL1 knockout or overexpression. Observation of imatinib sensitivity in GIST 882 cells after SGPL1 gene knockout Culturing and passaging were performed for SGPL1 knockout, overexpression, and WT GIST 882 cell lines. Cells in the logarithmic growth phase were seeded into 96-well plates at a density of 6 × 10 3 cells per well. After 24 h of incubation, the medium was replaced with culture medium containing 40 µg/ml imatinib, and the treatment was maintained for four days. Daily observations of cell growth were conducted, and survival rate curves were generated to evaluate the sensitivity of cells to the drug. Western Blot (Wb) Proteins were isolated from cultured GIST 882 cells treatment with different virus. Equal amounts of proteins were subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis. The resolved proteins were electrotransferred to a nitrocellulose membrane (Bio-Rad, Hercules, CA). The membrane was blocked with 5% skim dry milk in Tris-HCl buffered saline and incubated with anti-SGPL1 (CST), p-AKT(CST), AKT(CST), PI 3 K (CST), JNK(CST), P53(CST), CDK2(CST), P27 Kip1 (CST), Bcl-2 (Abcam), P15 Ink4b (CST) and anti-β-actin (Abcam) primary antibodies. Next, the membrane was incubated with enzyme-labeled species-specific secondary antibodies. Immunoreactive signals were developed using enhanced chemiluminescence (Pierce Chemical Company, Rockford, IL). CCK-8 analysis GIST 882 cells were inoculated into 96-well plates at a concentration of 2×10 4 / well, and cultured for 4d with a concentration of 40 µg/ml imatinib. After 96 h of drug treatment, 20 µl CCK-8 (Dojindo, Japan) solution was added to each well and incubated at 37℃ for 4 h, following the manufacturer's instructions. The absorbance at 450 nm was measured by the Bio-Tek automatic enzyme-labeler. The cell survival rate was calculated as a percentage of CCK-8 absorbance, calculated as follows: [(absorbance of drug treated sample - blank)/ (absorbance of control sample - blank) ]×100%. Immunohistochemical staining Tumor tissues were fixed in 4% paraformaldehyde (PFA) for overnight and then were sliced into 10-µm thick sections on adhesive slides. The tissue sections were permeabilized with 0.3% Triton X-100 (Sigma, St. Louis, USA) in 1×phosphate-buffered saline (PBS) for 10 min, and blocked with immunofluorescence blocking solution (Beyotime, Shanghai, China) for 30 min at room temperature. The neurons were then washed and probed with anti-SGPL1 primary antibodies (1:500) overnight at 4℃. After washing with 1×PBS, the neurons were incubated with Alexa Fluor 488-conjugated donkey anti-rat secondary antibodies (Jackson, USA) (1:400) for 2 h at room temperature. The neurons were washed again with 1×PBS and stained with 4′,6-diamidino-2-phenylindole (DAPI) (Cell Signaling Technology, USA). The fluorescence signals were observed under an orthogonal fluorescence microscope (Leica, Germany). Axon regeneration was quantified based on the axon length using Leica QWin V3 image analysis software. Establishment of SGPL1 knockout/overexpression BALB/c-nu nude mouse xenograft models The SGPL1 knockout/overexpression GIST 882 stable cell lines were combined with Matrigel (thawed overnight at 4°C) in a 1:1 volume ratio. This mixture, at a concentration of 1 × 10 6 cells/100 µL per mouse, was subcutaneously injected into the left dorsal area near the axilla of 6-week-old nude mice. The injections for each group were as follows: Group 1: Phosphate-buffered saline (PBS); Groups 2 and 3: GIST 882 stable cells with SGPL1 knockout; Group 4: GIST 882 cells transfected with an empty knockout plasmid; Groups 5 and 6: GIST 882 stable cells overexpressing SGPL1; Group 7: GIST 882 cells transfected with an empty overexpression plasmid. Each group included 10 mice, totaling 70 mice. Body weight and tumor volume were recorded daily. Commencing on the 7th day post-tumor cell inoculation, imatinib was delivered via intratumoral injection at a dose of 0.1 mg/g/day, administered once daily for a duration of 21 days. Imatinib was injected into mice in groups 2, 4, 5, and 7, while the remaining groups received an equivalent volume of PBS. Following the treatment period, euthanasia was performed on the mice, and tumor tissues were collected. Tumor weight and volume were subsequently measured. Growth curves were generated to evaluate the sensitivity of mouse tumor cells to imatinib following SGPL1 knockout. The expression levels of SGPL1 in mouse tumor tissues were assessed via Wb and immunostaining. Immunohistochemistry was employed to evaluate cell proliferation and apoptosis, and flow cytometry was used to analyze cell cycle distribution. Results Screening for candidate genes of imatinib resistance using CRISPR-Pool TM KOUT library The screening roadmap was showed in Fig. 1 A. The CRISPR-Pool TM KOUT library-lentivirus system, as illustrated in Fig. 1 B, was successfully packaged. An average titer of 2.57 TU/ml was achieved. Post-infection of GIST 882 cells, the MOI value was maintained below 0.3, thereby ensuring comprehensive coverage of the CRISPR library within the cells. The IC50 of imatinib for GIST 882 cells has been established at 40 µg/ml. Through preliminary experiments assessing various drug concentrations, 40 µg/ml emerged as the optimal dosage. Concentrations below 40 µg/ml proved inadequate for effective screening, whereas those surpassing 40 µg/ml, particularly at 60 µg/ml or higher, resulted in significant cell death (Fig. 1 C). This dosage aligns with the findings presented by Jie Cao et al. in their research [ 26 ] . Imatinib at a concentration of 40 µg/ml was administered to both the sgRNA screening group and the control group (WT) of GIST 882 cells, and the treatment was continued for 4 days. Upon cessation of the drug, starting from day 4, nearly all cells in the control group (WT) perished, whereas a portion of cells in the sgRNA screening group remained viable (Fig. 1 D). Cells from both the sgRNA + imatinib group and the sgRNA group were harvested on the 6th day post-imatinib treatment for high-throughput sequencing. Cluster analysis along with positive and negative screening analyses were employed to identify the top 50 drug resistance candidate genes based on RRA scores from the pool of resistance candidates (Fig. 1 E). Out of these 50 genes, 17 genes associated with cell proliferation, apoptosis, and the cell cycle, including FLI1, ZNF, SGPL1, and hsa-mir-4461, were selected for a second screening round. To enhance screening efficiency in this round, a mixed library of sgRNAs targeting these 17 genes was generated and introduced into GIST 882 cells. Following imatinib treatment, resistant cells and control group cells were collected for sgRNA sequencing, with SGPL1 sgRNA showing the highest degree of enrichment. Moreover, mRNA microarray differential gene analysis revealed significant downregulation of SGPL1 gene expression in resistant cells (Fig. 1 F). Integrating the results from the second round of sgRNA sequencing, microarray bioinformatics analysis, and prediction, SGPL1 might be the drug resistance target gene. Knockout of SGPL1 induced drug resistance and promoted proliferation in GIST 882 cells The lentiV2-SGPL1 sgRNA for SGPL1 knockout and lenti–SGPL1 for overexpression infected GIST 882 cells. WB were applied to evaluate the efficiency of SGPL1 gene knockout and overexpression (Fig. 2 A). Imatinib was administered to GIST 882, SGPL1 sgRNA group, and SGPL1 PLV group cells. The expression level of SGPL1 in the SGPL1 sgRNA group was markedly lower compared to the WT and overexpression groups (Fig. 2 B). On the first day post-imatinib treatment, the survival rate of GIST 882 cells was 75%, which declined markedly on the second and third days, culminating in the near-total death of cells by the fourth day. Conversely, GIST 882 cells in the SGPL1 sgRNA group demonstrated a survival rate of approximately 90% on the first day after imatinib treatment. These cells remained quiescent on the second and third days, initiated proliferation on the fourth day, and proliferated extensively by the fifth and sixth days. The SGPL1 sgRNA control group cells, without imatinib treatment, exhibited increased cell proliferation following SGPL1 gene knockout (Fig. 2 C). In addition, we found that the downregulation of SGPL1 in tumor tissues of imatinib-resistant GIST patients. Detection of SGPL1 protein in tumor tissues from both imatinib-resistant and non-resistant GIST patients indicated that SGPL1 expression was low or absent in the tumor tissues of resistant patients. Conversely, high expression levels were observed in the tumor tissues of non-resistant patients as well as in normal gastric mucosal epithelium (Fig. 2 D-E). Knockout of SGPL1 accelerated the proliferation of GIST 882 cells in the transplanted tumor model in nude mice Forty 6-week-old female BALB/C-nude mice were divided into 3 groups with GIST 882 WT cells, GIST 882 cells with SGPL1 sgRNA and GIST 882 cells with Nontarget sgRNA (Fig. 3 A). The cells were injected into the subcutaneous dorsal ventral side of nude mice by 1x10 6 . The weight of mice was measured before inoculation, and the weight of mice was measured the day after inoculation, and the tumor length and short diameter were measured, and the tumor volume was calculated to establish the transplanted tumor model (Fig. 3 B). Two weeks after inoculation of nude mice with tumor cells, mice inoculated with GIST 882 WT cells were divided into two groups. One group served as the control group, and the other group received imatinib treatment together with the SGPL1 sgRNA group or the Nontarget sgRNA group. Imatinib was intraperitoneally injected at 150 mg/kg and the mice were killed after continuous administration for 7 days. Knockout of SGPL1 accelerated the growth of GIST 882 cells in the transplanted tumor model in nude mice (Fig. 3 C-D). In addition, the expression of SGPL1 gene in tumor tissues of mice in each group was detected. SGPL1 showed strong positive expression in transplanted tumors of Nontarget group, control group and GIST 882 WT + IM group, and negative expression in transplanted tumors of SGPL1 knockout group (Fig. 3 E-F), with significant difference (p < 0.05). Knockout of SGPL1 inhibited apoptosis and promoted drug resistance by upregulating Bcl-2 expression mRNA microarray analysis was conducted on SGPL1 knockout and GIST 882 WT cells. Integration with differential gene screening and GO database analysis revealed significant enrichment of the PI 3 K-Akt pathway (Fig. 3 A). Following the sequencing results, relevant proteins were examined. Post SGPL1 gene knockout, an upregulation in PI 3 K and AKT expression was observed. Additionally, an increase in Bcl-2 expression and a decrease in P27 kip1 and P15 INK4b expression were noted (Fig. 3 B). Immunohistochemical detection of transplanted tumor tissues of nude mice showed negative or low expression of p-AKT and Bcl-2 in the control group, control treatment group and Nontarget treatment group, and strong positive expression in the treatment group with knockout SGPL1 (Fig. 3 C-D). To further elucidate the potential interactions between SGPL1 and these genes, information from the Pathway Commons database was utilized. Protein function enrichment analysis indicated correlations between SGPL1 expression and the MAPK, ErbB, PI3K-Akt, and JAK-STAT signaling pathways (Fig. 3 E). Subsequently, the Stringdb database was used to corroborate the gene interactions identified in the Pathway Commons database. It was revealed that SGPL1 could indirectly affect AKT1 and influence Bcl-2 through Akt or other genes. Furthermore, interactions with genes such as MAPK8, EGFR, and MYC were also identified (Fig. 3 F). SGPL1 gene mutations A preliminary bioinformatics analysis of SGPL1 gene mutations in patients with gastric cancer and leiomyosarcoma was executed utilizing the cBioPortal ( https://www.cbioportal.org/ ) and TCGA databases. The analysis demonstrated that among 434 gastric cancer patients, an A > C mutation in exon 7 of the SGPL1 gene was identified in a chemotherapy-resistant patient, which resulted in an amino acid alteration at position 191 (I191L, Fig. 4 ). Among 253 leiomyosarcoma patients, three instances exhibited abnormal SGPL1 gene fragment copy numbers, and one instance displayed a base mutation. However, it remains indeterminate if these mutations induce functional alterations in the gene. Furthermore, a study identified an A > G mutation in the SGPL1 gene within a pediatric alveolar rhabdomyosarcoma patient, resulting in an amino acid alteration at position 321 in the coding region. Discussion In the preliminary study, a genome-wide CRISPR/Cas9 library was utilized to screen for imatinib resistance genes in GIST 882 cells through two rounds of selection. The top 50 resistance candidate genes were ranked by robust rank aggregation (RRA) scores in the first round of screening (Fig. 1 F). Among these, ten genes or microRNAs, including FLI1, ZNF, SGPL1, and hsa-mir-4461, which are associated with tumor cell growth, proliferation, apoptosis, and drug resistance, were chosen for the second round of screening. Following the second round of sgRNA screening, sequencing, and microarray bioinformatics analysis, SGPL1 was identified as the resistance target gene. SGPL1 encodes sphingosine-1-phosphate lyase, an enzyme that irreversibly degrades sphingosine 1-phosphate (S1P) [ 30 ] . Under physiological conditions, SGPL1, along with sphingosine kinase (SphK), maintains the dynamic balance of S1P metabolism and is involved in regulating cell growth, proliferation, metastasis, and angiogenesis [ 31 , 32 ] . Studies have shown that SGPL1 is expressed at low levels in oral squamous cell carcinoma [ 33 ] and breast cancer [ 34 ] tissues, and is associated with promoting tumor cell proliferation, migration, and invasion. When the SGPL1 gene is mutated [ 35 ] or its expression is dysregulated [ 36 – 39 ] , S1P accumulates, activating multiple signaling pathways, including STAT3, ERK, and NF-κB, by binding to cell surface receptors, thereby promoting tumor cell proliferation and metastasis, and inhibiting apoptosis. The current study found that knocking out the SGPL1 gene in GIST 882 cells led to drug resistance and enhanced proliferation (Fig. 2 ). Clinical research results indicated that SGPL1 protein was expressed at low levels in tumor tissues of imatinib-resistant GIST patients, while it was highly expressed in tumor tissues of non-resistant patients (Fig. 2 D-E). To further elucidate the pathways and mechanisms by which SGPL1 promotes GIST 882 cell proliferation and drug resistance, microarray differential gene expression results (Fig. 4 A), Western blot results (Fig. 4 B), and SGPL1 interaction information from the Pathway Commons database (Fig. 4 E) were analyzed. It was found that SGPL1 expression correlated with the PI 3 K-Akt, MAPK, and JAK-STAT signaling pathways. The PI 3 K and Akt genes are crucial nodes in the PI 3 K/Akt/mTOR signaling pathway, which is essential for promoting tumor cell proliferation, inhibiting apoptosis, and developing chemotherapy drug resistance. Gene interaction relationships identified in the Pathway Commons database were further validated using the Stringdb database, revealing that SGPL1 could indirectly influence Bcl-2 through AKT1 or other genes (Fig. 4 F). Experiments confirmed that after knocking out the SGPL1 gene, PI3K and Akt gene expression was upregulated, along with Bcl-2 expression. Additionally, the expression of inhibitory factors P27 kip1 and P15 INK4b , involved in cell cycle regulation, was downregulated (Fig. 4 B). These findings suggest that SGPL1 may regulate the expression of Bcl-2, P27 kip1 , and P15 INK4b genes through the PI3K-Akt signaling pathway. The absence of SGPL1 inhibits GIST 882 cell apoptosis, accelerates the G1/S cell cycle transition, and ultimately leads to imatinib resistance. The implementation of this project will further investigate the molecular mechanisms of drug resistance based on the functional identification of resistance genes. Finally, bioinformatics analysis utilizing cBioPortal and TCGA databases has identified an A > C mutation in exon 7 of the SGPL1 gene in a chemotherapy-resistant gastric cancer patient, leading to an amino acid substitution from isoleucine to leucine at position 191 (I191L) (Fig. 5 ). Furthermore, among 253 leiomyosarcoma patients, 3 cases displayed SGPL1 gene fragment copy number abnormalities, and 1 case exhibited a mutation, although its impact on gene function remains unclear. This project aims to sequence the SGPL1 gene in imatinib-resistant patients. If gene mutations are discovered, efforts will be made to repair the A > C mutation site at the cellular level using PE technology to potentially reverse imatinib resistance. In conclusion, the limitations inherent in traditional drug resistance research methods, marked by low efficiency and poor representativeness, were successfully addressed in this project. Through the integration of gene function and phenotype, the CRISPR/Cas9 whole-genome library was utilized to efficiently screen and identify critical genes and mechanisms underlying imatinib resistance. Subsequent efforts were made to repair these identified genes, thereby establishing a comprehensive theoretical basis for the development of novel imatinib treatment strategies. Declarations Funding This study was supported by the Suqian Sci&Tech Program (No. M202110), the Research Project of Jiangsu Provincial Health Commission (No. M2021098) and the Scientific Research Project (Key Project) of the Jiading District Health Commission in Shanghai (No. 2024-KY-ZD-11). Author Contribution XW, NZ; Experiment conductance and data analyses: JW, ZX, YW, XW, NZ; Contributed reagents/materials/analysis tools: YW, XW; Wrote the manuscript:JW, ZX, XW, NZ. Acknowledgment We thank GENEWIZ (Suzhou) for bioinformatics analysis. References Kelly CM, Gutierrez Sainz L, Chi P. The management of metastatic GIST: current standard and investigational therapeutics. J Hematol Oncol. 2021 Jan 5;14(1):2. Blay JY, Kang YK, Nishida T, et al. Gastrointestinal stromal tumors. Nat Rev Dis Primers. 2021 Mar 18;7(1):22. Svatoň R, Kala Z, Kysela P, et al. Gastrointestinal Stromal Tumours of the Rectum-Evaluating the National Registry Data with Respect to its Use in Clinical Practice. Klin Onkol. 2019 Spring;32(2):117-123. Li J, Shen L. The current status of and prospects in research regarding gastrointestinal stromal tumors in China. Cancer. 2020 May 1;126 Suppl 9:2048-2053. Begum FA, Rahman MA, Rabbi H, et al. Primary Jejunal Gastrointestinal Stromal Tumor: Diagnosis Delay of 3 Years but Successful Management in Early Stage (II) by Surgery and Adjuvant Therapy. Gastrointest Tumors. 2019 Aug;6(1-2):36-42. Mantese G. Gastrointestinal stromal tumor: epidemiology, diagnosis, and treatment. Curr Opin Gastroenterol. 2019 Nov;35(6):555-559. Dermawan JK, Rubin BP. Molecular Pathogenesis of Gastrointestinal Stromal Tumor: A Paradigm for Personalized Medicine. Annu Rev Pathol. 2022 Jan 24;17:323-344. Al-Share B, Alloghbi A, Al Hallak MN, et al. Gastrointestinal stromal tumor: a review of current and emerging therapies. Cancer Metastasis Rev. 2021 Jun;40(2):625-641. Akahoshi K, Oya M, Koga T, et al. Current clinical management of gastrointestinal stromal tumor. World J Gastroenterol. 2018 Jul 14;24(26):2806-2817. Tao Kaixiong, Zhang Peng, Li Jian, et al. Chinese expert consensus on comprehensive management of GIST (2020 edition). Chinese Journal of Practical Surgery, 2020, 40(10):1109-1119. Sbaraglia M, Businello G, Bellan E, et al. Mesenchymal tumours of the gastrointestinal tract. Pathologica. 2021 Jun;113(3):230-251. Feng Y, Yao S, Pu Z, et al. Identification of New Tumor-Related Gene Mutations in Chinese Gastrointestinal Stromal Tumors. Front Cell Dev Biol. 2021 Nov 3;9:764275. Liu M, Etherington MS, Hanna A, et al. Oncogenic KIT Modulates Type I IFN-Mediated Anti-tumor Immunity in GIST. Cancer Immunol Res. 2021 May;9(5):542-553. Farag S, Smith MJ, Fotiadis N, et al. Revolutions in treatment options in gastrointestinal stromal tumours (GISTs): the latest updates. Curr Treat Options Oncol. 2020 May 27;21(7):55. Cohen P, Cross D, Jänne PA. Kinase drug discovery 20 years after imatinib: progress and future directions. Nat Rev Drug Discov. 2021 Jul;20(7):551-569. Rutkowski P, Gronchi A, Hohenberger P, et al．Neoadjuvant imatinib in locally advanced gastrointestinal stmmal tumors(GIST)：the EORTC STBSG experience. Ann Surg Oncol，2013; 20(9): 2937-2943. Joensuu H, Hohenberger P, Corless CL. Gastrointestinal stromal tumour. Lancet. 2013 Sep 14;382(9896):973-983. Fornasarig M, Gasparotto D, Foltran L, et al. A Novel Kindred with Familial Gastrointestinal Stromal Tumors Caused by a Rare KIT Germline Mutation (N655K): Clinico-Pathological Presentation and TKI Sensitivity. J Pers Med. 2020 Nov 17;10(4):234. Takahashi T, Elzawahry A, Mimaki S, et al. Genomic and transcriptomic analysis of imatinib resistance in gastrointestinal stromal tumors. Genes Chromosomes Cancer. 2017 Apr;56(4):303-313. Xu K, He Z, Chen M, et al. HIF-1α regulates cellular metabolism, and Imatinib resistance by targeting phosphogluconate dehydrogenase in gastrointestinal stromal tumors. Cell Death Dis. 2020 Jul 27;11(7):586. Zhang J, Chen K, Tang Y, et al. LncRNA-HOTAIR activates autophagy and promotes the imatinib resistance of gastrointestinal stromal tumor cells through a mechanism involving the miR-130a/ATG2B pathway. Cell Death Dis. 2021 Apr 6;12(4):367. Reichardt P, Kang YK, Rutkowski P, et al. Clinical outcomes of patients with advanced gastrointestinal stromal tumors: safety and efficacy in a worldwide treatment-use trial of sunitinib. Cancer. 2015 May 1;121(9):1405-1413 Patel SR, Reichardt P. An updated review of the treatment landscape for advanced gastrointestinal stromal tumors. Cancer. 2021 Jul 1;127(13):2187-2195. Chang YR, Huang WK, Wang SY, et al. A Nomogram Predicting Progression Free Survival in Patients with Gastrointestinal Stromal Tumor Receiving Sunitinib: Incorporating Pre-Treatment and Post-Treatment Parameters. Cancers (Basel). 2021 May 25;13(11):2587. Kim JJ, Ryu MH, Yoo C, et al. Phase II Trial of Continuous Regorafenib Dosing in Patients with Gastrointestinal Stromal Tumors After Failure of Imatinib and Sunitinib. Oncologist. 2019 Nov;24(11):e1212-e1218. Cao J, Wei J, Yang P, et al. Genome-scale CRISPR-Cas9 knockout screening in gastrointestinal stromal tumor with Imatinib resistance. Mol Cancer. 2018 Aug 13;17(1):121. Yeh WH, Shubina-Oleinik O, Levy JM, et al. In vivo base editing restores sensory transduction and transiently improves auditory function in a mouse model of recessive deafness. Sci Transl Med. 2020 Jun 3;12(546): eaay910130. Anzalone AV, Koblan LW, Liu DR. Genome editing with CRISPR-Cas nucleases, base editors, transposases and prime editors. Nat Biotechnol. 2020 Jul;38(7):824-844. Chen PJ, Hussmann JA, Yan J, et al. Enhanced prime editing systems by manipulating cellular determinants of editing outcomes. Cell. 2021 Oct 28;184(22):5635-5652.e29. Cartier A, Hla T. Sphingosine 1-phosphate: Lipid signaling in pathology and therapy. Science. 2019 Oct 18;366(6463):eaar5551. Zhao P, Tassew GB, Lee JY, et al. Efficacy of AAV9-mediated SGPL1 gene transfer in a mouse model of S1P lyase insufficiency syndrome. JCI Insight. 2021 Apr 22;6(8):e145936. Wang Y, Shen Y, Sun X, et al. Prognostic roles of the expression of sphingosine-1-phosphate metabolism enzymes in non-small cell lung cancer. Transl Lung Cancer Res. 2019 Oct;8(5):674-681. Vishwakarma S, Agarwal R, Goel SK, et al. Altered Expression of Sphingosine-1-Phosphate Metabolizing Enzymes in Oral Cancer Correlate With Clinicopathological Attributes. Cancer Invest. 2017 Feb 7;35(2):139-141. Engel N, Adamus A, Frank M, et al. First evidence of SGPL1 expression in the cell membrane silencing the extracellular S1P siren in mammary epithelial cells. PLoS One. 2018 May 2;13(5):e0196854. Adamus A, Engel N, Seitz G. SGPL1 321 mutation: one main trigger for invasiveness of pediatric alveolar rhabdomyosarcoma. Cancer Gene Ther. 2020 Aug; 27(7-8): 571-584. Faqar-Uz-Zaman WF, Schmidt KG, Thomas D, et al. S1P Lyase siRNA Dampens Malignancy of DLD-1 Colorectal Cancer Cells. Lipids. 2021 Mar;56(2):155-166. Takahashi K, Fujiya M, Konishi H, et al. Heterogenous Nuclear Ribonucleoprotein H1 Promotes Colorectal Cancer Progression through the Stabilization of mRNA of Sphingosine-1-Phosphate Lyase 1. Int J Mol Sci. 2020 Jun 25; 21(12): 4514. Schwiebs A, Herrero San Juan M, Schmidt KG, et al. Cancer-induced inflammation and inflammation-induced cancer in colon: a role for S1P lyase. Oncogene. 2019 Jun;38(24):4788-4803. Hu SL, Huang CC, Tseng TT, et al. S1P facilitates IL-1β production in osteoblasts via the JAK and STAT3 signaling pathways. Environ Toxicol. 2020 Sep;35(9):991-997. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6647302","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":461473677,"identity":"41e2044c-d45c-48b7-b73e-146e41d02e7f","order_by":0,"name":"Jie Wang","email":"","orcid":"","institution":"The Affiliated Suqian First People’s Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Wang","suffix":""},{"id":461473678,"identity":"9e63a495-6e73-4e7c-a34b-41a8ef0dc8be","order_by":1,"name":"Zhen Xu","email":"","orcid":"","institution":"The Affiliated Suqian First People’s Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhen","middleName":"","lastName":"Xu","suffix":""},{"id":461473679,"identity":"9d2147ad-b414-457c-92a1-a3cc4027a0d7","order_by":2,"name":"Yu Wang","email":"","orcid":"","institution":"The Affiliated Suqian First People’s Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Wang","suffix":""},{"id":461473680,"identity":"a48c2dd2-db9e-493a-a614-1600a04b9b91","order_by":3,"name":"Xiaoyan Wang","email":"","orcid":"","institution":"The Affiliated Suqian First People’s Hospital of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyan","middleName":"","lastName":"Wang","suffix":""},{"id":461473681,"identity":"411f0df1-1f00-4c48-bf30-17166c31485d","order_by":4,"name":"Ning Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAp0lEQVRIiWNgGAWjYLACiQoJOXkStZyxMDZsIEkLY1tFIsMBYlXz3Uh+/MFynkQCYwPzw0c3iNEieeaYgYHkNok8dgY2Y+McYrQYHG8wSABqKWZs4GGTJk7LYfYPByTnSCQ2HCBay/EewwbJBlK0SJ45U8wgcUzC2LCZWL/w3Ujf/Fmipk5Onr354WOitICig1kCxGAmSjlUC+MHolWPglEwCkbBiAQAB+AufgusDjEAAAAASUVORK5CYII=","orcid":"","institution":"The Affiliated Suqian First People’s Hospital of Nanjing Medical University","correspondingAuthor":true,"prefix":"","firstName":"Ning","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-05-12 13:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6647302/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6647302/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83544025,"identity":"6f739545-b8e1-44a1-846d-1fb0547c7969","added_by":"auto","created_at":"2025-05-28 08:44:11","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":340204,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDetermination of the optimal imatinib dosage and the amplification of CRISPR-Pool TM KOUT library\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA).The screening roadmap of the study. B). Schematic diagram of the CRISPR-Pool \u003csup\u003eTM\u003c/sup\u003e KOUT library-lentivirus system structure. C). Effect of different concentrations of imatinib on the growth of GIST 882 cells. D). GIST 882 cells developed resistance after the introduction of the sgRNA library. GIST 882 cells treated with imatinib (40 μg/ml) E). RRA scores from the pool of resistance candidates. F). mRNA microarray evealed significant downregulation of SGPL1 gene expression in the mixed library of sgRNAs targeting these 17 genes.\u003c/p\u003e","description":"","filename":"figure1.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6647302/v1/2cc369ab2f3ec4a708ecf9f3.jpg"},{"id":83544331,"identity":"d2b74a5e-7c0f-4b40-ad4e-1fc309e2fea5","added_by":"auto","created_at":"2025-05-28 08:52:11","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":443663,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKnockout of SGPL1 induced drug resistance and promoted proliferation in GIST 882 cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. WB were applied to evaluate the efficiency of SGPL1 gene knockout and overexpression. B. The expression level of SGPL1 in the SGPL1 sgRNA group was markedly lower compared to the WT and overexpression groups. C. The SGPL1 KO exhibited increased cell proliferation with imatinib treatment. D-E. SGPL1 expression was low or absent in the tumor tissues of resistant patients.A. Statistical analysis of SGPL1 expression intensity in tumor tissues of imatinib-resistant and non-resistant GIST patients. Group 1: imatinib-resistant patients; Group 2: non-imatinib-resistant patients, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"figure2.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6647302/v1/fbb5fa0aeb743f72f6f34f78.jpg"},{"id":83544029,"identity":"6e838030-1683-44f1-a04c-09988a43e7f4","added_by":"auto","created_at":"2025-05-28 08:44:11","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":548845,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKnockout of SGPL1 accelerated the proliferation of GIST 882 cells in the transplanted tumor model in nude mice\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) Schematic diagram of groups design. B-D) The cells were injected into the subcutaneous dorsal ventral side of nude mice by 1x10\u003csup\u003e6\u003c/sup\u003e. Tumor growth curves and\u0026nbsp; typical photographs of tumors of different groups. E-F) The expression of SGPL1in tumor tissues of mice in each group was detected.\u003c/p\u003e","description":"","filename":"figure3.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6647302/v1/5de38528b93bf6f7ef5bcfb3.jpg"},{"id":83544030,"identity":"80f8f75a-c785-43d6-9733-f03db5d22292","added_by":"auto","created_at":"2025-05-28 08:44:11","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":788846,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKnockout of SGPL1 induced drug resistance by upregulating Bcl-2 expression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) GO analysis revealed significant enrichment of the pathway based on mRNA microarray of SGPL1 knockout and GIST 882 WT cells. B) The relevant proteins were examined. An upregulation in PI\u003csub\u003e3\u003c/sub\u003eK and AKT expression was observed. Additionally, an increase in Bcl-2 expression and a decrease in P27\u003csup\u003ekip1\u003c/sup\u003e and P15\u003csup\u003eINK4b\u003c/sup\u003e expression were noted. C-D) Immunohistochemical detection the expression of p-AKT and Bcl-2 in different group, E) Protein function enrichment analysis indicated correlations between SGPL1 expression and the MAPK, ErbB, PI3K-Akt, and JAK-STAT signaling pathways. F) The Stringdb database was used to corroborate the gene interactions identified in the Pathway Commons database.\u003c/p\u003e","description":"","filename":"figure4.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6647302/v1/492f0bb322ae0ef24848c335.jpg"},{"id":83544333,"identity":"c1da0372-47f3-4224-aacf-588303247aa6","added_by":"auto","created_at":"2025-05-28 08:52:11","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":510669,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSGPL1 gene mutation site (I191L) in gastric cancer patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA)The cBioPortal (https://www.cbioportal.org/) and TCGA databases were executed to analysis of SGPL1 gene mutations in patients with gastric cancer and leiomyosarcoma. B) Among 434 gastric cancer patients, an A \u0026gt; C mutation in exon 7 of the SGPL1 gene was identified in a chemotherapy-resistant patient, which resulted in an amino acid alteration at position 191 (I191L).\u003c/p\u003e","description":"","filename":"figure5.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6647302/v1/f3abfa76b7a30f6e2a8ea033.jpg"},{"id":105989894,"identity":"706437a3-990d-4694-baa6-54855ea01b0a","added_by":"auto","created_at":"2026-04-02 08:12:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3581924,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6647302/v1/48d659e3-1947-45ff-9b26-59b148f7896a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"SGPL1 Deficiency Get Involved in Imatinib Resistance via PI 3 K-Akt signaling pathway in gastrointestinal stromal tumor","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGastrointestinal stromal tumors (GISTs), originating from Cajal cells in soft tissues, represent the most prevalent mesenchymal tumors within the digestive system. These tumors demonstrate a spectrum of biological behaviors and carry malignant potential \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. The global annual incidence of GIST is estimated to be 10\u0026ndash;15 per million individuals \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. GISTs may develop at any site within the gastrointestinal tract, with the stomach (60\u0026ndash;70%) and small intestine (20\u0026ndash;25%) being the most frequent locations\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. The absence of distinctive clinical manifestations, presenting only symptoms such as gastrointestinal bleeding, abdominal mass, discomfort, and pain, combined with pathological features akin to gastrointestinal spindle cell tumors lacking smooth muscle and neural differentiation, results in GISTs being frequently misdiagnosed or overlooked. Over the past two decades, enhanced understanding of pathogenesis has revealed that GISTs are primarily induced by mutations in the c-KIT gene and the platelet-derived growth factor receptor alpha (PDGFRA) gene\u003csup\u003e[\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Consequently, clinical diagnosis and treatment protocols have become increasingly standardized.\u003c/p\u003e \u003cp\u003eGuidelines for the diagnosis and treatment of GIST have been developed and updated by the National Comprehensive Cancer Network and the European Society for Medical Oncology. Similarly, the Chinese Society of Clinical Oncology has issued an expert consensus on GIST, noting that targeted therapy remains the sole effective treatment for patients with advanced primary tumors ineligible for surgery, as well as those experiencing postoperative recurrence, metastasis, or facing recurrence risk\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. \u003cem\u003eTyrosine kinase inhibitors\u003c/em\u003e, recognized as the initial targeted drugs utilized in GIST treatment, competitively bind to the intracellular domain of tyrosine kinase by vying with adenosine triphosphate, thereby obstructing downstream signal transduction pathways such as JAK-STAT3 and RAS-MEK-ERK. This mechanism effectively suppresses tumor cell growth, proliferation, and metastasi \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e \u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eImatinib, a tyrosine kinase inhibitor, is recognized as a first-line targeted drug that has shown considerable efficacy in early clinical applications. Patients have achieved complete or partial remission, with a median progression-free survival (PFS) of 20\u0026ndash;24 months and a median overall survival of five years \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. However, with the progression of treatment, drug resistance has become increasingly prominent, emerging as a significant bottleneck limiting the efficacy of targeted therapy for GIST. Clinical data suggest that 10\u0026ndash;20% of patients develop primary resistance within the first six months of imatinib treatment. Additionally, within 1\u0026ndash;3 years of treatment, 40\u0026ndash;50% of patients experience secondary resistance, with the incidence of secondary resistant cases rising by 10% annually \u003csup\u003e[\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Primary resistance mechanisms are mainly attributed to the wild-type (WT) c-KIT gene and the PDGFRA D842V mutation, whereas the mechanisms underlying secondary resistance remain unclear. Some studies have indicated that resistance in certain patients is due to secondary mutations in exons 13, 14, 17, or 18 of the c-KIT gene during treatment, resulting in structural changes in the intracellular segment of tyrosine kinase, which prevent imatinib from binding and exerting its therapeutic effect \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Other research proposes that in some resistant patients, the c-KIT gene does not undergo secondary mutations; instead, prolonged stimulation by imatinib leads to upregulation of hypoxia-inducible factor HIF1α expression, which promotes tumor cell proliferation and inhibits apoptosis by regulating the activity of phosphogluconate dehydrogenase\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Furthermore, additional studies have identified that imatinib resistance is associated with non-coding RNAs, such as LncRNA HOTAIR, which induces resistance by modulating the miR-130a/ATG2B signaling pathway \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFollowing the onset of imatinib resistance, the standard strategy involves increasing the drug dosage to sustain its efficacy. Upon reaching the maximum daily dose of 800 mg, if symptoms persist or the dose is not well-tolerated, patients are generally transitioned to second-line sunitinib or third-line regorafenib. Although sunitinib can mitigate the condition to a degree, its PFS remains relatively short, with a median of 5.6 months, and its objective response rate is comparatively low (6.8%). Additionally, the side effects of sunitinib are more severe than those of imatinib, commonly manifesting as fatigue, diarrhea, nausea, hand-foot syndrome, hypertension, neutropenia, thrombocytopenia, and anemia \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Regorafenib is also associated with significant toxic side effects \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. The limited overall survival benefit and adverse reactions linked to second- and third-line drugs constrain their long-term clinical application \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. In light of this scenario, identifying key genes responsible for imatinib resistance and delving into their resistance mechanisms, along with exploring methods to reverse the resistance, is of considerable clinical significance for enhancing the efficacy of imatinib treatment and improving the prognosis of GIST patients.\u003c/p\u003e \u003cp\u003eTraditional approaches to investigating drug resistance genes mainly encompass the drug concentration gradient doubling method and the patient-derived tumor xenograft model. The former entails the creation of a gene mutation cell model via drug induction. Despite its simplicity, this method requires a prolonged modeling period of approximately 6\u0026ndash;12 months, leading to low efficiency and limited genetic data acquisition. Conversely, the latter method, although it preserves the genetic characteristics of primary tumors more effectively, fails to accurately represent the comprehensive drug-resistance gene profile due to tumor heterogeneity and individual genetic variations among patients.\u003c/p\u003e \u003cp\u003eTherefore, the research objectives of this project are as follows: Firstly, a CRISPR/Cas9 whole-genome library will be employed to screen the entire genome of GIST 882 cells. This library comprises 123,411 sgRNAs targeting 19,050 coding genes and 1,864 miRNAs within the GIST 882 cell genome. Post-imatinib treatment, the surviving cells, presumed to be enriched with drug-resistant genes, will be harvested for high-throughput sequencing and bioinformatics analysis to identify differentially expressed drug-resistant candidate genes. Secondly, the functions of these drug-resistant candidate genes will be validated both in vitro and in vivo, and their resistance mechanisms will be further investigated. These findings, in conjunction with The Cancer Genome Atlas Program (TCGA) database, will be used to identify mutation sites of the drug-resistant genes.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAmplification of the CRISPR-Pool \u003csup\u003eTM\u003c/sup\u003e KOUT library plasmid\u003c/h2\u003e \u003cp\u003e(1) Preparation of \u003cem\u003eEscherichia coli\u003c/em\u003e DH5α competent cells\u003c/p\u003e \u003cp\u003eA single \u003cem\u003eEscherichia coli\u003c/em\u003e DH5α colony was selected and inoculated into 4 mL of antibiotic-free LB medium. The culture was incubated overnight at 37\u0026deg;C with shaking. The following day, the bacterial suspension was transferred to 3 mL of fresh antibiotic-free LB medium and cultured for an additional 12\u0026ndash;14 h. Once the OD\u003csub\u003e600\u003c/sub\u003e reached around 0.5, the cultivation was halted. The bacterial suspension was subsequently placed in an ice-water bath for 30 min, followed by centrifugation at 4\u0026deg;C. After discarding the supernatant, the pellet was resuspended in 20 mL of pre-chilled ddH\u003csub\u003e2\u003c/sub\u003eO. This process was repeated, and the final pellet was resuspended in 20 \u0026micro;L of ddH\u003csub\u003e2\u003c/sub\u003eO, forming the competent cells.\u003c/p\u003e \u003cp\u003e(2) Transformation of \u003cem\u003eEscherichia coli\u003c/em\u003e DH5α competent cells\u003c/p\u003e \u003cp\u003eTo 30 \u0026micro;L of freshly prepared competent cells, 1 \u0026micro;L each of CRISPR library plasmids A and B (hGeCKOa and hGeCKOb) were added, and the mixture was placed in an ice-cold water bath for 10 min. The competent cells were then transferred to pre-chilled electroporation cuvettes for electroporation transformation. Post-transformation, incubation of the cells was carried out at room temperature with shaking for 1 h. Following this, 10 \u0026micro;L of the transformed cells was plated and incubated for 14 h. The next day, the resultant colonies were harvested and cultured with shaking at 37\u0026deg;C for another 14 h.\u003c/p\u003e \u003cp\u003e(3) Extraction of library plasmids\u003c/p\u003e \u003cp\u003eUsing the PureLink Hipure Plasmid Miniprep Kit, the library plasmids hGeCKOa and hGeCKOb were extracted. Agarose gel electrophoresis was employed to observe the target bands, which were subsequently excised from the gel and recovered for sequencing. After this, 1 ml of bacterial culture was inoculated into 250 ml of LB liquid medium and incubated at 37\u0026deg;C with shaking for 14 h. The bacterial cells were then harvested. Extraction of plasmids was performed using the PureLink Hipure Plasmid Maxiprep Kit, followed by determination of plasmid concentration.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eVirus packaging\u003c/h3\u003e\n\u003cp\u003eHEK293 cells in the logarithmic growth phase were seeded at a density of 5 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells per 10 cm culture dish. Upon reaching a cell density of 80\u0026ndash;90%, preparations for transfection were initiated. The complete culture medium was replaced 2 h before transfection. In tube A, 35 \u0026micro;L of transfection reagent was mixed with 1.25 mL of Opti-MEM\u0026trade; Medium and incubated for 5 min. In tube B, hGeCKOa and packaging plasmids were combined in a 4:3 ratio with 1.25 mL of Opti-MEM\u0026trade; Medium and incubated for 5 min. The contents of the two tubes were then gently mixed and incubated for 25 min before being added to the HEK293 culture dish. Eight hours later, the culture medium was replaced. After 48 h, the culture supernatant was collected, and the viral titer was determined. The packaging of the library plasmid hGeCKOb followed the same procedure.\u003c/p\u003e\n\u003ch3\u003eTransfected GIST 882 cells\u003c/h3\u003e\n\u003cp\u003eGIST 882 cells were seeded into culture dishes at a density of 5 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells per dish, across a total of 20 dishes. Two dishes were designated as the control group, receiving no viral addition. The following day, upon reaching a cell density of 50%, the culture medium was replaced with 5 ml of DMEM complete medium containing 10 \u0026micro;g/ml polybrene. After a 30-minute incubation period, 4 ml of culture medium and 1 ml of virus solution were added. The medium was replaced 24 h later. On the third day, puromycin selection was initiated. The surviving cells in the treatment group were deemed to have successfully integrated the sgRNA, and the multiplicity of infection (MOI\u0026thinsp;\u0026lt;\u0026thinsp;0.3) was calculated.\u003c/p\u003e\n\u003ch3\u003eDetermination of imatinib IC50\u003c/h3\u003e\n\u003cp\u003eGIST 882 cells in the logarithmic growth phase were seeded into 96-well plates at a density of 6 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e cells per well. Following a 24-hour incubation, the medium was replaced with DMEM containing varying concentrations of imatinib (0, 20, 40, 60, 80, and 100 \u0026micro;g/ml). Each concentration was tested in triplicate wells. After a 48-hour exposure, the culture medium was removed, and 10 \u0026micro;l of CCK8 reagent in fresh medium was added to each well. The plates were then incubated in the dark for 4 h. Absorbance at 450 nm was measured, and the IC50 was calculated to establish the optimal imatinib concentration for treatment.\u003c/p\u003e\n\u003ch3\u003eImatinib treatment\u003c/h3\u003e\n\u003cp\u003eGIST 882 WT cells and GIST 882 cells transduced with the sgRNA library were separately seeded at a density of 5 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells per dish. Imatinib was administered to both cell groups at a concentration of 40 \u0026micro;g/ml and maintained for a duration of 4 days. A control dish of GIST 882 cells transduced with the sgRNA library was left untreated. Upon complete apoptosis or death of GIST 882 WT cells, the surviving GIST 882 cells transduced with the sgRNA library were deemed to be a population enriched for imatinib-resistant genes. Cells from each group, along with the library plasmids, were subsequently collected for high-throughput sequencing.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHigh-throughput sequencing analysis\u003c/h2\u003e \u003cp\u003eClustering analysis and positive/negative gene screening were utilized to calculate RRA scores for the candidate drug resistance genes. From the top 50 ranked genes, ten genes associated with cell growth, proliferation, apoptosis, and drug resistance were selected for further screening. The sgRNA sequencing was conducted by Genewiz (Suzhou) Company.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEstablishment of stable GIST 882 cell lines with SGPL1 knockout/overexpression\u003c/h3\u003e\n\u003cp\u003esgRNA sequences targeting SGPL1 were designed and inserted into the CRISPRlentiV2 vector to create the knockout plasmid for the drug resistance target gene. The overexpression sequence of SGPL1 was designed and inserted into the pCDH-CMV-EF1-mcherry vector to generate the overexpression plasmid. Both constructs were verified by sequencing. Lentiviruses were packaged, and the SGPL1 knockout and overexpression plasmids were transduced separately into GIST 882 cells to establish stable cell lines with SGPL1 knockout or overexpression.\u003c/p\u003e\n\u003ch3\u003eObservation of imatinib sensitivity in GIST 882 cells after SGPL1 gene knockout\u003c/h3\u003e\n\u003cp\u003eCulturing and passaging were performed for SGPL1 knockout, overexpression, and WT GIST 882 cell lines. Cells in the logarithmic growth phase were seeded into 96-well plates at a density of 6 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e cells per well. After 24 h of incubation, the medium was replaced with culture medium containing 40 \u0026micro;g/ml imatinib, and the treatment was maintained for four days. Daily observations of cell growth were conducted, and survival rate curves were generated to evaluate the sensitivity of cells to the drug.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eWestern Blot (Wb)\u003c/h2\u003e \u003cp\u003eProteins were isolated from cultured GIST 882 cells treatment with different virus. Equal amounts of proteins were subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis. The resolved proteins were electrotransferred to a nitrocellulose membrane (Bio-Rad, Hercules, CA). The membrane was blocked with 5% skim dry milk in Tris-HCl buffered saline and incubated with anti-SGPL1 (CST), p-AKT(CST), AKT(CST), PI\u003csub\u003e3\u003c/sub\u003eK (CST), JNK(CST), P53(CST), CDK2(CST), P27\u003csup\u003eKip1\u003c/sup\u003e(CST), Bcl-2 (Abcam), P15\u003csup\u003eInk4b\u003c/sup\u003e (CST) and anti-β-actin (Abcam) primary antibodies. Next, the membrane was incubated with enzyme-labeled species-specific secondary antibodies. Immunoreactive signals were developed using enhanced chemiluminescence (Pierce Chemical Company, Rockford, IL).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003eCCK-8 analysis\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eGIST 882 cells were inoculated into 96-well plates at a concentration of 2\u0026times;10\u003csup\u003e4\u003c/sup\u003e/ well, and cultured for 4d with a concentration of 40 \u0026micro;g/ml imatinib. After 96 h of drug treatment, 20 \u0026micro;l CCK-8 (Dojindo, Japan) solution was added to each well and incubated at 37℃ for 4 h, following the manufacturer's instructions. The absorbance at 450 nm was measured by the Bio-Tek automatic enzyme-labeler. The cell survival rate was calculated as a percentage of CCK-8 absorbance, calculated as follows: [(absorbance of drug treated sample - blank)/ (absorbance of control sample - blank) ]\u0026times;100%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemical staining\u003c/h2\u003e \u003cp\u003eTumor tissues were fixed in 4% paraformaldehyde (PFA) for overnight and then were sliced into 10-\u0026micro;m thick sections on adhesive slides. The tissue sections were permeabilized with 0.3% Triton X-100 (Sigma, St. Louis, USA) in 1\u0026times;phosphate-buffered saline (PBS) for 10 min, and blocked with immunofluorescence blocking solution (Beyotime, Shanghai, China) for 30 min at room temperature. The neurons were then washed and probed with anti-SGPL1 primary antibodies (1:500) overnight at 4℃. After washing with 1\u0026times;PBS, the neurons were incubated with Alexa Fluor 488-conjugated donkey anti-rat secondary antibodies (Jackson, USA) (1:400) for 2 h at room temperature. The neurons were washed again with 1\u0026times;PBS and stained with 4\u0026prime;,6-diamidino-2-phenylindole (DAPI) (Cell Signaling Technology, USA). The fluorescence signals were observed under an orthogonal fluorescence microscope (Leica, Germany). Axon regeneration was quantified based on the axon length using Leica QWin V3 image analysis software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEstablishment of SGPL1 knockout/overexpression BALB/c-nu nude mouse xenograft models\u003c/h2\u003e \u003cp\u003eThe SGPL1 knockout/overexpression GIST 882 stable cell lines were combined with Matrigel (thawed overnight at 4\u0026deg;C) in a 1:1 volume ratio. This mixture, at a concentration of 1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells/100 \u0026micro;L per mouse, was subcutaneously injected into the left dorsal area near the axilla of 6-week-old nude mice. The injections for each group were as follows: Group 1: Phosphate-buffered saline (PBS); Groups 2 and 3: GIST 882 stable cells with SGPL1 knockout; Group 4: GIST 882 cells transfected with an empty knockout plasmid; Groups 5 and 6: GIST 882 stable cells overexpressing SGPL1; Group 7: GIST 882 cells transfected with an empty overexpression plasmid. Each group included 10 mice, totaling 70 mice. Body weight and tumor volume were recorded daily. Commencing on the 7th day post-tumor cell inoculation, imatinib was delivered via intratumoral injection at a dose of 0.1 mg/g/day, administered once daily for a duration of 21 days. Imatinib was injected into mice in groups 2, 4, 5, and 7, while the remaining groups received an equivalent volume of PBS. Following the treatment period, euthanasia was performed on the mice, and tumor tissues were collected. Tumor weight and volume were subsequently measured. Growth curves were generated to evaluate the sensitivity of mouse tumor cells to imatinib following SGPL1 knockout. The expression levels of SGPL1 in mouse tumor tissues were assessed via Wb and immunostaining. Immunohistochemistry was employed to evaluate cell proliferation and apoptosis, and flow cytometry was used to analyze cell cycle distribution.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eScreening for candidate genes of imatinib resistance using CRISPR-Pool \u003csup\u003eTM\u003c/sup\u003e KOUT library\u003c/h2\u003e \u003cp\u003eThe screening roadmap was showed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA. The CRISPR-Pool TM KOUT library-lentivirus system, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, was successfully packaged. An average titer of 2.57 TU/ml was achieved. Post-infection of GIST 882 cells, the MOI value was maintained below 0.3, thereby ensuring comprehensive coverage of the CRISPR library within the cells. The IC50 of imatinib for GIST 882 cells has been established at 40 \u0026micro;g/ml. Through preliminary experiments assessing various drug concentrations, 40 \u0026micro;g/ml emerged as the optimal dosage. Concentrations below 40 \u0026micro;g/ml proved inadequate for effective screening, whereas those surpassing 40 \u0026micro;g/ml, particularly at 60 \u0026micro;g/ml or higher, resulted in significant cell death (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). This dosage aligns with the findings presented by Jie Cao et al. in their research\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Imatinib at a concentration of 40 \u0026micro;g/ml was administered to both the sgRNA screening group and the control group (WT) of GIST 882 cells, and the treatment was continued for 4 days. Upon cessation of the drug, starting from day 4, nearly all cells in the control group (WT) perished, whereas a portion of cells in the sgRNA screening group remained viable (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003eCells from both the sgRNA\u003csup\u003e+\u003c/sup\u003eimatinib group and the sgRNA group were harvested on the 6th day post-imatinib treatment for high-throughput sequencing. Cluster analysis along with positive and negative screening analyses were employed to identify the top 50 drug resistance candidate genes based on RRA scores from the pool of resistance candidates (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). Out of these 50 genes, 17 genes associated with cell proliferation, apoptosis, and the cell cycle, including FLI1, ZNF, SGPL1, and hsa-mir-4461, were selected for a second screening round. To enhance screening efficiency in this round, a mixed library of sgRNAs targeting these 17 genes was generated and introduced into GIST 882 cells. Following imatinib treatment, resistant cells and control group cells were collected for sgRNA sequencing, with SGPL1 sgRNA showing the highest degree of enrichment. Moreover, mRNA microarray differential gene analysis revealed significant downregulation of SGPL1 gene expression in resistant cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Integrating the results from the second round of sgRNA sequencing, microarray bioinformatics analysis, and prediction, SGPL1 might be the drug resistance target gene.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eKnockout of SGPL1 induced drug resistance and promoted proliferation in GIST 882 cells\u003c/h2\u003e \u003cp\u003eThe lentiV2-SGPL1 sgRNA for SGPL1 knockout and lenti\u0026ndash;SGPL1 for overexpression infected GIST 882 cells. WB were applied to evaluate the efficiency of SGPL1 gene knockout and overexpression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Imatinib was administered to GIST 882, SGPL1 sgRNA group, and SGPL1 PLV group cells. The expression level of SGPL1 in the SGPL1 sgRNA group was markedly lower compared to the WT and overexpression groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). On the first day post-imatinib treatment, the survival rate of GIST 882 cells was 75%, which declined markedly on the second and third days, culminating in the near-total death of cells by the fourth day. Conversely, GIST 882 cells in the SGPL1 sgRNA group demonstrated a survival rate of approximately 90% on the first day after imatinib treatment. These cells remained quiescent on the second and third days, initiated proliferation on the fourth day, and proliferated extensively by the fifth and sixth days. The SGPL1 sgRNA control group cells, without imatinib treatment, exhibited increased cell proliferation following SGPL1 gene knockout (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). In addition, we found that the downregulation of SGPL1 in tumor tissues of imatinib-resistant GIST patients. Detection of SGPL1 protein in tumor tissues from both imatinib-resistant and non-resistant GIST patients indicated that SGPL1 expression was low or absent in the tumor tissues of resistant patients. Conversely, high expression levels were observed in the tumor tissues of non-resistant patients as well as in normal gastric mucosal epithelium (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD-E).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eKnockout of SGPL1 accelerated the proliferation of GIST 882 cells in the transplanted tumor model in nude mice\u003c/b\u003e \u003c/p\u003e \u003cp\u003eForty 6-week-old female BALB/C-nude mice were divided into 3 groups with GIST 882 WT cells, GIST 882 cells with SGPL1 sgRNA and GIST 882 cells with Nontarget sgRNA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The cells were injected into the subcutaneous dorsal ventral side of nude mice by 1x10\u003csup\u003e6\u003c/sup\u003e. The weight of mice was measured before inoculation, and the weight of mice was measured the day after inoculation, and the tumor length and short diameter were measured, and the tumor volume was calculated to establish the transplanted tumor model (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTwo weeks after inoculation of nude mice with tumor cells, mice inoculated with GIST 882 WT cells were divided into two groups. One group served as the control group, and the other group received imatinib treatment together with the SGPL1 sgRNA group or the Nontarget sgRNA group. Imatinib was intraperitoneally injected at 150 mg/kg and the mice were killed after continuous administration for 7 days. Knockout of SGPL1 accelerated the growth of GIST 882 cells in the transplanted tumor model in nude mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D). In addition, the expression of SGPL1 gene in tumor tissues of mice in each group was detected. SGPL1 showed strong positive expression in transplanted tumors of Nontarget group, control group and GIST 882 WT\u0026thinsp;+\u0026thinsp;IM group, and negative expression in transplanted tumors of SGPL1 knockout group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE-F), with significant difference (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eKnockout of SGPL1 inhibited apoptosis and promoted drug resistance by upregulating Bcl-2 expression\u003c/h2\u003e \u003cp\u003emRNA microarray analysis was conducted on SGPL1 knockout and GIST 882 WT cells. Integration with differential gene screening and GO database analysis revealed significant enrichment of the PI\u003csub\u003e3\u003c/sub\u003eK-Akt pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Following the sequencing results, relevant proteins were examined. Post SGPL1 gene knockout, an upregulation in PI\u003csub\u003e3\u003c/sub\u003eK and AKT expression was observed. Additionally, an increase in Bcl-2 expression and a decrease in P27\u003csup\u003ekip1\u003c/sup\u003e and P15\u003csup\u003eINK4b\u003c/sup\u003e expression were noted (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Immunohistochemical detection of transplanted tumor tissues of nude mice showed negative or low expression of p-AKT and Bcl-2 in the control group, control treatment group and Nontarget treatment group, and strong positive expression in the treatment group with knockout SGPL1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D). To further elucidate the potential interactions between SGPL1 and these genes, information from the Pathway Commons database was utilized. Protein function enrichment analysis indicated correlations between SGPL1 expression and the MAPK, ErbB, PI3K-Akt, and JAK-STAT signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). Subsequently, the Stringdb database was used to corroborate the gene interactions identified in the Pathway Commons database. It was revealed that SGPL1 could indirectly affect AKT1 and influence Bcl-2 through Akt or other genes. Furthermore, interactions with genes such as MAPK8, EGFR, and MYC were also identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eSGPL1 gene mutations\u003c/h2\u003e \u003cp\u003eA preliminary bioinformatics analysis of SGPL1 gene mutations in patients with gastric cancer and leiomyosarcoma was executed utilizing the cBioPortal (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cbioportal.org/\u003c/span\u003e\u003cspan address=\"https://www.cbioportal.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and TCGA databases. The analysis demonstrated that among 434 gastric cancer patients, an A\u0026thinsp;\u0026gt;\u0026thinsp;C mutation in exon 7 of the SGPL1 gene was identified in a chemotherapy-resistant patient, which resulted in an amino acid alteration at position 191 (I191L, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Among 253 leiomyosarcoma patients, three instances exhibited abnormal SGPL1 gene fragment copy numbers, and one instance displayed a base mutation. However, it remains indeterminate if these mutations induce functional alterations in the gene. Furthermore, a study identified an A\u0026thinsp;\u0026gt;\u0026thinsp;G mutation in the SGPL1 gene within a pediatric alveolar rhabdomyosarcoma patient, resulting in an amino acid alteration at position 321 in the coding region.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the preliminary study, a genome-wide CRISPR/Cas9 library was utilized to screen for imatinib resistance genes in GIST 882 cells through two rounds of selection. The top 50 resistance candidate genes were ranked by robust rank aggregation (RRA) scores in the first round of screening (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Among these, ten genes or microRNAs, including FLI1, ZNF, SGPL1, and hsa-mir-4461, which are associated with tumor cell growth, proliferation, apoptosis, and drug resistance, were chosen for the second round of screening. Following the second round of sgRNA screening, sequencing, and microarray bioinformatics analysis, SGPL1 was identified as the resistance target gene. SGPL1 encodes sphingosine-1-phosphate lyase, an enzyme that irreversibly degrades sphingosine 1-phosphate (S1P)\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eUnder physiological conditions, SGPL1, along with sphingosine kinase (SphK), maintains the dynamic balance of S1P metabolism and is involved in regulating cell growth, proliferation, metastasis, and angiogenesis\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Studies have shown that SGPL1 is expressed at low levels in oral squamous cell carcinoma \u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e and breast cancer\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e tissues, and is associated with promoting tumor cell proliferation, migration, and invasion. When the SGPL1 gene is mutated\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e or its expression is dysregulated\u003csup\u003e[\u003cspan additionalcitationids=\"CR37 CR38\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e, S1P accumulates, activating multiple signaling pathways, including STAT3, ERK, and NF-κB, by binding to cell surface receptors, thereby promoting tumor cell proliferation and metastasis, and inhibiting apoptosis. The current study found that knocking out the SGPL1 gene in GIST 882 cells led to drug resistance and enhanced proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Clinical research results indicated that SGPL1 protein was expressed at low levels in tumor tissues of imatinib-resistant GIST patients, while it was highly expressed in tumor tissues of non-resistant patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD-E).\u003c/p\u003e \u003cp\u003eTo further elucidate the pathways and mechanisms by which SGPL1 promotes GIST 882 cell proliferation and drug resistance, microarray differential gene expression results (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), Western blot results (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), and SGPL1 interaction information from the Pathway Commons database (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE) were analyzed. It was found that SGPL1 expression correlated with the PI\u003csub\u003e3\u003c/sub\u003eK-Akt, MAPK, and JAK-STAT signaling pathways. The PI\u003csub\u003e3\u003c/sub\u003eK and Akt genes are crucial nodes in the PI\u003csub\u003e3\u003c/sub\u003eK/Akt/mTOR signaling pathway, which is essential for promoting tumor cell proliferation, inhibiting apoptosis, and developing chemotherapy drug resistance. Gene interaction relationships identified in the Pathway Commons database were further validated using the Stringdb database, revealing that SGPL1 could indirectly influence Bcl-2 through AKT1 or other genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). Experiments confirmed that after knocking out the SGPL1 gene, PI3K and Akt gene expression was upregulated, along with Bcl-2 expression. Additionally, the expression of inhibitory factors P27\u003csup\u003ekip1\u003c/sup\u003e and P15\u003csup\u003eINK4b\u003c/sup\u003e, involved in cell cycle regulation, was downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). These findings suggest that SGPL1 may regulate the expression of Bcl-2, P27\u003csup\u003ekip1\u003c/sup\u003e, and P15\u003csup\u003eINK4b\u003c/sup\u003e genes through the PI3K-Akt signaling pathway. The absence of SGPL1 inhibits GIST 882 cell apoptosis, accelerates the G1/S cell cycle transition, and ultimately leads to imatinib resistance. The implementation of this project will further investigate the molecular mechanisms of drug resistance based on the functional identification of resistance genes.\u003c/p\u003e \u003cp\u003eFinally, bioinformatics analysis utilizing cBioPortal and TCGA databases has identified an A\u0026thinsp;\u0026gt;\u0026thinsp;C mutation in exon 7 of the SGPL1 gene in a chemotherapy-resistant gastric cancer patient, leading to an amino acid substitution from isoleucine to leucine at position 191 (I191L) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Furthermore, among 253 leiomyosarcoma patients, 3 cases displayed SGPL1 gene fragment copy number abnormalities, and 1 case exhibited a mutation, although its impact on gene function remains unclear. This project aims to sequence the SGPL1 gene in imatinib-resistant patients. If gene mutations are discovered, efforts will be made to repair the A\u0026thinsp;\u0026gt;\u0026thinsp;C mutation site at the cellular level using PE technology to potentially reverse imatinib resistance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn conclusion, the limitations inherent in traditional drug resistance research methods, marked by low efficiency and poor representativeness, were successfully addressed in this project. Through the integration of gene function and phenotype, the CRISPR/Cas9 whole-genome library was utilized to efficiently screen and identify critical genes and mechanisms underlying imatinib resistance. Subsequent efforts were made to repair these identified genes, thereby establishing a comprehensive theoretical basis for the development of novel imatinib treatment strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was supported by the Suqian Sci\u0026amp;Tech Program (No. M202110), the Research Project of Jiangsu Provincial Health Commission (No. M2021098) and the Scientific Research Project (Key Project) of the Jiading District Health Commission in Shanghai (No. 2024-KY-ZD-11).\u003c/p\u003e \u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eXW, NZ; Experiment conductance and data analyses: JW, ZX, YW, XW, NZ; Contributed reagents/materials/analysis tools: YW, XW; Wrote the manuscript:JW, ZX, XW, NZ.\u003c/p\u003e\u003ch2\u003eAcknowledgment\u003c/h2\u003e \u003cp\u003eWe thank GENEWIZ (Suzhou) for bioinformatics analysis.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKelly CM, Gutierrez Sainz L, Chi P. The management of metastatic GIST: current standard and investigational therapeutics. J Hematol Oncol. 2021 Jan 5;14(1):2. \u003c/li\u003e\n\u003cli\u003eBlay JY, Kang YK, Nishida T, et al. Gastrointestinal stromal tumors. Nat Rev Dis Primers. 2021 Mar 18;7(1):22.\u003c/li\u003e\n\u003cli\u003eSvatoň R, Kala Z, Kysela P, et al. Gastrointestinal Stromal Tumours of the Rectum-Evaluating the National Registry Data with Respect to its Use in Clinical Practice. Klin Onkol. 2019 Spring;32(2):117-123.\u003c/li\u003e\n\u003cli\u003eLi J, Shen L. The current status of and prospects in research regarding gastrointestinal stromal tumors in China. Cancer. 2020 May 1;126 Suppl 9:2048-2053.\u003c/li\u003e\n\u003cli\u003eBegum FA, Rahman MA, Rabbi H, et al. Primary Jejunal Gastrointestinal Stromal Tumor: Diagnosis Delay of 3 Years but Successful Management in Early Stage (II) by Surgery and Adjuvant Therapy. Gastrointest Tumors. 2019 Aug;6(1-2):36-42. \u003c/li\u003e\n\u003cli\u003eMantese G. Gastrointestinal stromal tumor: epidemiology, diagnosis, and treatment. Curr Opin Gastroenterol. 2019 Nov;35(6):555-559.\u003c/li\u003e\n\u003cli\u003eDermawan JK, Rubin BP. Molecular Pathogenesis of Gastrointestinal Stromal Tumor: A Paradigm for Personalized Medicine. Annu Rev Pathol. 2022 Jan 24;17:323-344.\u003c/li\u003e\n\u003cli\u003eAl-Share B, Alloghbi A, Al Hallak MN, et al. Gastrointestinal stromal tumor: a review of current and emerging therapies. Cancer Metastasis Rev. 2021 Jun;40(2):625-641.\u003c/li\u003e\n\u003cli\u003eAkahoshi K, Oya M, Koga T, et al. Current clinical management of gastrointestinal stromal tumor. World J Gastroenterol. 2018 Jul 14;24(26):2806-2817.\u003c/li\u003e\n\u003cli\u003eTao Kaixiong, Zhang Peng, Li Jian, et al. Chinese expert consensus on comprehensive management of GIST (2020 edition). Chinese Journal of Practical Surgery, 2020, 40(10):1109-1119.\u003c/li\u003e\n\u003cli\u003eSbaraglia M, Businello G, Bellan E, et al. Mesenchymal tumours of the gastrointestinal tract. Pathologica. 2021 Jun;113(3):230-251.\u003c/li\u003e\n\u003cli\u003eFeng Y, Yao S, Pu Z, et al. Identification of New Tumor-Related Gene Mutations in Chinese Gastrointestinal Stromal Tumors. Front Cell Dev Biol. 2021 Nov 3;9:764275.\u003c/li\u003e\n\u003cli\u003eLiu M, Etherington MS, Hanna A, et al. Oncogenic KIT Modulates Type I IFN-Mediated Anti-tumor Immunity in GIST. Cancer Immunol Res. 2021 May;9(5):542-553.\u003c/li\u003e\n\u003cli\u003eFarag S, Smith MJ, Fotiadis N, et al. Revolutions in treatment options in gastrointestinal stromal tumours (GISTs): the latest updates. Curr Treat Options Oncol. 2020 May 27;21(7):55.\u003c/li\u003e\n\u003cli\u003eCohen P, Cross D, J\u0026auml;nne PA. Kinase drug discovery 20 years after imatinib: progress and future directions. Nat Rev Drug Discov. 2021 Jul;20(7):551-569.\u003c/li\u003e\n\u003cli\u003eRutkowski P, Gronchi A, Hohenberger P, et al．Neoadjuvant imatinib in locally advanced gastrointestinal stmmal tumors(GIST)：the EORTC STBSG experience. Ann Surg Oncol，2013; 20(9): 2937-2943. \u003c/li\u003e\n\u003cli\u003eJoensuu H, Hohenberger P, Corless CL. Gastrointestinal stromal tumour. Lancet. 2013 Sep 14;382(9896):973-983.\u003c/li\u003e\n\u003cli\u003eFornasarig M, Gasparotto D, Foltran L, et al. A Novel Kindred with Familial Gastrointestinal Stromal Tumors Caused by a Rare KIT Germline Mutation (N655K): Clinico-Pathological Presentation and TKI Sensitivity. J Pers Med. 2020 Nov 17;10(4):234.\u003c/li\u003e\n\u003cli\u003eTakahashi T, Elzawahry A, Mimaki S, et al. Genomic and transcriptomic analysis of imatinib resistance in gastrointestinal stromal tumors. Genes Chromosomes Cancer. 2017 Apr;56(4):303-313.\u003c/li\u003e\n\u003cli\u003eXu K, He Z, Chen M, et al. HIF-1\u0026alpha; regulates cellular metabolism, and Imatinib resistance by targeting phosphogluconate dehydrogenase in gastrointestinal stromal tumors. Cell Death Dis. 2020 Jul 27;11(7):586.\u003c/li\u003e\n\u003cli\u003eZhang J, Chen K, Tang Y, et al. LncRNA-HOTAIR activates autophagy and promotes the imatinib resistance of gastrointestinal stromal tumor cells through a mechanism involving the miR-130a/ATG2B pathway. Cell Death Dis. 2021 Apr 6;12(4):367.\u003c/li\u003e\n\u003cli\u003eReichardt P, Kang YK, Rutkowski P, et al. Clinical outcomes of patients with advanced gastrointestinal stromal tumors: safety and efficacy in a worldwide treatment-use trial of sunitinib. Cancer. 2015 May 1;121(9):1405-1413\u003c/li\u003e\n\u003cli\u003ePatel SR, Reichardt P. An updated review of the treatment landscape for advanced gastrointestinal stromal tumors. Cancer. 2021 Jul 1;127(13):2187-2195. \u003c/li\u003e\n\u003cli\u003eChang YR, Huang WK, Wang SY, et al. A Nomogram Predicting Progression Free Survival in Patients with Gastrointestinal Stromal Tumor Receiving Sunitinib: Incorporating Pre-Treatment and Post-Treatment Parameters. Cancers (Basel). 2021 May 25;13(11):2587. \u003c/li\u003e\n\u003cli\u003eKim JJ, Ryu MH, Yoo C, et al. Phase II Trial of Continuous Regorafenib Dosing in Patients with Gastrointestinal Stromal Tumors After Failure of Imatinib and Sunitinib. Oncologist. 2019 Nov;24(11):e1212-e1218. \u003c/li\u003e\n\u003cli\u003eCao J, Wei J, Yang P, et al. Genome-scale CRISPR-Cas9 knockout screening in gastrointestinal stromal tumor with Imatinib resistance. Mol Cancer. 2018 Aug 13;17(1):121.\u003c/li\u003e\n\u003cli\u003eYeh WH, Shubina-Oleinik O, Levy JM, et al. In vivo base editing restores sensory transduction and transiently improves auditory function in a mouse model of recessive deafness. Sci Transl Med. 2020 Jun 3;12(546): eaay910130. \u003c/li\u003e\n\u003cli\u003eAnzalone AV, Koblan LW, Liu DR. Genome editing with CRISPR-Cas nucleases, base editors, transposases and prime editors. Nat Biotechnol. 2020 Jul;38(7):824-844.\u003c/li\u003e\n\u003cli\u003eChen PJ, Hussmann JA, Yan J, et al. Enhanced prime editing systems by manipulating cellular determinants of editing outcomes. Cell. 2021 Oct 28;184(22):5635-5652.e29.\u003c/li\u003e\n\u003cli\u003eCartier A, Hla T. Sphingosine 1-phosphate: Lipid signaling in pathology and therapy. Science. 2019 Oct 18;366(6463):eaar5551.\u003c/li\u003e\n\u003cli\u003eZhao P, Tassew GB, Lee JY, et al. Efficacy of AAV9-mediated SGPL1 gene transfer in a mouse model of S1P lyase insufficiency syndrome. JCI Insight. 2021 Apr 22;6(8):e145936.\u003c/li\u003e\n\u003cli\u003eWang Y, Shen Y, Sun X, et al. Prognostic roles of the expression of sphingosine-1-phosphate metabolism enzymes in non-small cell lung cancer. Transl Lung Cancer Res. 2019 Oct;8(5):674-681.\u003c/li\u003e\n\u003cli\u003eVishwakarma S, Agarwal R, Goel SK, et al. Altered Expression of Sphingosine-1-Phosphate Metabolizing Enzymes in Oral Cancer Correlate With Clinicopathological Attributes. Cancer Invest. 2017 Feb 7;35(2):139-141.\u003c/li\u003e\n\u003cli\u003eEngel N, Adamus A, Frank M, et al. First evidence of SGPL1 expression in the cell membrane silencing the extracellular S1P siren in mammary epithelial cells. PLoS One. 2018 May 2;13(5):e0196854.\u003c/li\u003e\n\u003cli\u003eAdamus A, Engel N, Seitz G. SGPL1\u003csub\u003e321\u003c/sub\u003e mutation: one main trigger for invasiveness of pediatric alveolar rhabdomyosarcoma. Cancer Gene Ther. 2020 Aug; 27(7-8): 571-584.\u003c/li\u003e\n\u003cli\u003eFaqar-Uz-Zaman WF, Schmidt KG, Thomas D, et al. S1P Lyase siRNA Dampens Malignancy of DLD-1 Colorectal Cancer Cells. Lipids. 2021 Mar;56(2):155-166.\u003c/li\u003e\n\u003cli\u003eTakahashi K, Fujiya M, Konishi H, et al. Heterogenous Nuclear Ribonucleoprotein H1 Promotes Colorectal Cancer Progression through the Stabilization of mRNA of Sphingosine-1-Phosphate Lyase 1. Int J Mol Sci. 2020 Jun 25; 21(12): 4514.\u003c/li\u003e\n\u003cli\u003eSchwiebs A, Herrero San Juan M, Schmidt KG, et al. Cancer-induced inflammation and inflammation-induced cancer in colon: a role for S1P lyase. Oncogene. 2019 Jun;38(24):4788-4803.\u003c/li\u003e\n\u003cli\u003eHu SL, Huang CC, Tseng TT, et al. S1P facilitates IL-1\u0026beta; production in osteoblasts via the JAK and STAT3 signaling pathways. Environ Toxicol. 2020 Sep;35(9):991-997.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Imatinib Resistance, Gastrointestinal stromal tumor, The genome-scale CRISPR/Cas9 Knockout Screening, SGPL1, Bcl-2","lastPublishedDoi":"10.21203/rs.3.rs-6647302/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6647302/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGastrointestinal stromal tumor (GIST) is the most common mesenchymal tumor in the gastrointestinal tract. In recent years, secondary resistance to the first-line drug imatinib has become its bottleneck of targeted therapy due to the unclear mechanism. It has important clinical significance for breaking through the bottleneck by screening and identifying the critical gene of imatinib resistance. Unbiased in vivo genome-wide genetic screening is a powerful approach to elucidate new molecular mechanisms. Here the genome-scale CRISPR/Cas9 Knockout Screening was applied to investigate imatinib resistance genes in GIST 882 cell line for two rounds, and it was found that deficiency of sphingosine 1-phosphate lyase coding gene SGPL1 can inhibit tumor cell apoptosis and accelerate cell cycle G1/S, finally leading to imatinib resistance in vitro and in vivo, by regulating the expression of Bcl-2, p27kip1 and p15INK4B via PI\u003csub\u003e3\u003c/sub\u003eK-Akt signaling pathway. In additionally, non-synonymous mutation in the exon of SGPL1 gene has been found by comparing the TCGA clinical drug resistance patient database. It was revealed that SPGL1 gene may be the critical gene of imatinib resistance. Taken together, our study provides a resource for achieving a deep understanding of the molecular basis of imatinib resistance.\u003c/p\u003e","manuscriptTitle":"SGPL1 Deficiency Get Involved in Imatinib Resistance via PI 3 K-Akt signaling pathway in gastrointestinal stromal tumor","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-28 08:44:06","doi":"10.21203/rs.3.rs-6647302/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"642b0690-4b20-4cc8-9773-2a81c505276f","owner":[],"postedDate":"May 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":49010739,"name":"Biological sciences/Cell biology"},{"id":49010740,"name":"Biological sciences/Molecular biology"},{"id":49010741,"name":"Biological sciences/Cancer"},{"id":49010742,"name":"Biological sciences/Cancer/Cancer screening"},{"id":49010743,"name":"Biological sciences/Cancer/Cancer therapy"}],"tags":[],"updatedAt":"2026-04-02T08:10:43+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-28 08:44:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6647302","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6647302","identity":"rs-6647302","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}