#METABOLOMICS WORKBENCH Gilles_Perera_Lab_20250320_111111 DATATRACK_ID:5761 STUDY_ID:ST003847 ANALYSIS_ID:AN006322 PROJECT_ID:PR002405 VERSION 1 CREATED_ON April 7, 2025, 7:01 pm #PROJECT PR:PROJECT_TITLE Differential acquisition of extracellular lipid correlates with pancreatic PR:PROJECT_TITLE cancer subtype and metastatic tropism PR:PROJECT_TYPE Metabolomics PR:PROJECT_SUMMARY Pancreatic ductal adenocarcinoma (PDAC) stands as an aggressive disease, ranking PR:PROJECT_SUMMARY at the third leading cause of cancer-related death with a 5-year overall PR:PROJECT_SUMMARY survival rate of less than 5%. Recent studies have identified two major subtypes PR:PROJECT_SUMMARY of pancreatic cancer, basal and classical, which predict patient prognosis, with PR:PROJECT_SUMMARY basal tumors corresponding to more aggressive disease. While transcriptional PR:PROJECT_SUMMARY signatures define basal and classical tumors and cell lines, little is known PR:PROJECT_SUMMARY regarding the metabolic vulnerabilities linked to the basal versus classical PR:PROJECT_SUMMARY state. Using unbiased computational interrogation to uncover metabolic genes PR:PROJECT_SUMMARY correlating with known markers of classical PDAC, we identified high expression PR:PROJECT_SUMMARY of Proprotein Convertase Subtilisin/Kexin type-9 (PCSK9) – a negative PR:PROJECT_SUMMARY regulator of receptor mediated uptake of cholesterol-containing low-density PR:PROJECT_SUMMARY lipoprotein (LDL) – as correlating with several established markers of PR:PROJECT_SUMMARY classical PDAC. In contrast, PCSK9 expression is suppressed in basal PDAC. PR:PROJECT_SUMMARY Accordingly, basal PDAC cells uptake high levels of LDL, are sensitive to LDL PR:PROJECT_SUMMARY depletion and show higher dependence on cholesterol uptake, relative to PR:PROJECT_SUMMARY classical PDAC. As lipoproteins are produced in the liver, we hypothesized that PR:PROJECT_SUMMARY basal PDAC cells might possess a greater propensity to seed and thrive within PR:PROJECT_SUMMARY liver tissues. Conversely, basal cells demonstrated a robust ability to grow PR:PROJECT_SUMMARY within the liver but faced challenges in invading the lungs whereas classical PR:PROJECT_SUMMARY cells harbour the opposite phenotype. Moreover, we observed that patients with PR:PROJECT_SUMMARY liver metastasis alone had weaker PCSK9 staining at the primary tumor site PR:PROJECT_SUMMARY compared to those with lung metastasis only. This observation suggests a PR:PROJECT_SUMMARY potential influence of cholesterol metabolism in the primary tumor on the PR:PROJECT_SUMMARY tropism of metastatic sites. Modulating PCSK9 levels in pancreatic cancer cells PR:PROJECT_SUMMARY with low expression of this protein resulted in reduced LDL uptake and a shift PR:PROJECT_SUMMARY towards the cholesterol biosynthesis pathway. More importantly, overexpressing PR:PROJECT_SUMMARY PCSK9 not only reduced the liver metastasis burden but also increased lung PR:PROJECT_SUMMARY metastasis in liver-tropic cell lines. Lastly, we found that PCSK9 expression PR:PROJECT_SUMMARY and protein abundance remained low in liver metastatic lesions and high in lung PR:PROJECT_SUMMARY metastasis lesions. This observation suggests that cancer cells maintain PR:PROJECT_SUMMARY distinct cholesterol metabolism profiles in metastatic lesions. Ongoing studies PR:PROJECT_SUMMARY will interrogate the role of cholesterol uptake and utilization in liver PR:PROJECT_SUMMARY metastasis , and uncover unique features and vulnerabilities of the most PR:PROJECT_SUMMARY aggressive variant of PDAC. PR:INSTITUTE University of California, San Francisco PR:DEPARTMENT Anatomy PR:LABORATORY Perera PR:LAST_NAME Rademaker PR:FIRST_NAME Gilles PR:ADDRESS 513 Parnassus avenue, San Francisco, CA, 94143, USA PR:EMAIL gilles.rademaker@ucsf.edu PR:PHONE 4155024290 #STUDY ST:STUDY_TITLE Differential acquisition of extracellular lipid correlates with pancreatic ST:STUDY_TITLE cancer subtype and metastatic tropism ST:STUDY_TYPE Metabolomics ST:STUDY_SUMMARY Pancreatic ductal adenocarcinoma (PDAC) stands as an aggressive disease, ranking ST:STUDY_SUMMARY at the third leading cause of cancer-related death with a 5-year overall ST:STUDY_SUMMARY survival rate of less than 5%. Recent studies have identified two major subtypes ST:STUDY_SUMMARY of pancreatic cancer, basal and classical, which predict patient prognosis, with ST:STUDY_SUMMARY basal tumors corresponding to more aggressive disease. While transcriptional ST:STUDY_SUMMARY signatures define basal and classical tumors and cell lines, little is known ST:STUDY_SUMMARY regarding the metabolic vulnerabilities linked to the basal versus classical ST:STUDY_SUMMARY state. Using unbiased computational interrogation to uncover metabolic genes ST:STUDY_SUMMARY correlating with known markers of classical PDAC, we identified high expression ST:STUDY_SUMMARY of Proprotein Convertase Subtilisin/Kexin type-9 (PCSK9) – a negative ST:STUDY_SUMMARY regulator of receptor mediated uptake of cholesterol-containing low-density ST:STUDY_SUMMARY lipoprotein (LDL) – as correlating with several established markers of ST:STUDY_SUMMARY classical PDAC. In contrast, PCSK9 expression is suppressed in basal PDAC. ST:STUDY_SUMMARY Accordingly, basal PDAC cells uptake high levels of LDL, are sensitive to LDL ST:STUDY_SUMMARY depletion and show higher dependence on cholesterol uptake, relative to ST:STUDY_SUMMARY classical PDAC. As lipoproteins are produced in the liver, we hypothesized that ST:STUDY_SUMMARY basal PDAC cells might possess a greater propensity to seed and thrive within ST:STUDY_SUMMARY liver tissues. Conversely, basal cells demonstrated a robust ability to grow ST:STUDY_SUMMARY within the liver but faced challenges in invading the lungs whereas classical ST:STUDY_SUMMARY cells harbour the opposite phenotype. Moreover, we observed that patients with ST:STUDY_SUMMARY liver metastasis alone had weaker PCSK9 staining at the primary tumor site ST:STUDY_SUMMARY compared to those with lung metastasis only. This observation suggests a ST:STUDY_SUMMARY potential influence of cholesterol metabolism in the primary tumor on the ST:STUDY_SUMMARY tropism of metastatic sites. Modulating PCSK9 levels in pancreatic cancer cells ST:STUDY_SUMMARY with low expression of this protein resulted in reduced LDL uptake and a shift ST:STUDY_SUMMARY towards the cholesterol biosynthesis pathway. More importantly, overexpressing ST:STUDY_SUMMARY PCSK9 not only reduced the liver metastasis burden but also increased lung ST:STUDY_SUMMARY metastasis in liver-tropic cell lines. Lastly, we found that PCSK9 expression ST:STUDY_SUMMARY and protein abundance remained low in liver metastatic lesions and high in lung ST:STUDY_SUMMARY metastasis lesions. This observation suggests that cancer cells maintain ST:STUDY_SUMMARY distinct cholesterol metabolism profiles in metastatic lesions. Ongoing studies ST:STUDY_SUMMARY will interrogate the role of cholesterol uptake and utilization in liver ST:STUDY_SUMMARY metastasis , and uncover unique features and vulnerabilities of the most ST:STUDY_SUMMARY aggressive variant of PDAC. ST:INSTITUTE University of California, San Francisco ST:DEPARTMENT Anatomy ST:LABORATORY Perera ST:LAST_NAME Rademaker ST:FIRST_NAME Gilles ST:ADDRESS 513 Parnassus avenue, San Francisco, CA, 94143, USA ST:EMAIL gilles.rademaker@ucsf.edu ST:PHONE 4155024290 #SUBJECT SU:SUBJECT_TYPE Cultured cells SU:SUBJECT_SPECIES Homo sapiens SU:TAXONOMY_ID 9606 #SUBJECT_SAMPLE_FACTORS: SUBJECT(optional)[tab]SAMPLE[tab]FACTORS(NAME:VALUE pairs separated by |)[tab]Raw file names and additional sample data SUBJECT_SAMPLE_FACTORS - 1 Variant:KP4_Control | Sample source:Pancreatic cancer cells Replicate=1; RAW_FILE_NAME(Raw File name)=Cell_UCSF_01 SUBJECT_SAMPLE_FACTORS - 2 Variant:KP4_Control | Sample source:Pancreatic cancer cells Replicate=2; RAW_FILE_NAME(Raw File name)=Cell_UCSF_02 SUBJECT_SAMPLE_FACTORS - 3 Variant:KP4_Control | Sample source:Pancreatic cancer cells Replicate=3; RAW_FILE_NAME(Raw File name)=Cell_UCSF_03 SUBJECT_SAMPLE_FACTORS - 4 Variant:KP4_Control | Sample source:Pancreatic cancer cells Replicate=4; RAW_FILE_NAME(Raw File name)=Cell_UCSF_04 SUBJECT_SAMPLE_FACTORS - 5 Variant:KP4_Control | Sample source:Pancreatic cancer cells Replicate=5; RAW_FILE_NAME(Raw File name)=Cell_UCSF_05 SUBJECT_SAMPLE_FACTORS - 6 Variant:KP4_D374Y | Sample source:Pancreatic cancer cells Replicate=1; RAW_FILE_NAME(Raw File name)=Cell_UCSF_06 SUBJECT_SAMPLE_FACTORS - 7 Variant:KP4_D374Y | Sample source:Pancreatic cancer cells Replicate=2; RAW_FILE_NAME(Raw File name)=Cell_UCSF_07 SUBJECT_SAMPLE_FACTORS - 8 Variant:KP4_D374Y | Sample source:Pancreatic cancer cells Replicate=3; RAW_FILE_NAME(Raw File name)=Cell_UCSF_08 SUBJECT_SAMPLE_FACTORS - 9 Variant:KP4_D374Y | Sample source:Pancreatic cancer cells Replicate=4; RAW_FILE_NAME(Raw File name)=Cell_UCSF_09 SUBJECT_SAMPLE_FACTORS - 10 Variant:KP4_D374Y | Sample source:Pancreatic cancer cells Replicate=5; RAW_FILE_NAME(Raw File name)=Cell_UCSF_10 SUBJECT_SAMPLE_FACTORS - 11 Variant:KP4_WT | Sample source:Pancreatic cancer cells Replicate=1; RAW_FILE_NAME(Raw File name)=Cell_UCSF_11 SUBJECT_SAMPLE_FACTORS - 12 Variant:KP4_WT | Sample source:Pancreatic cancer cells Replicate=2; RAW_FILE_NAME(Raw File name)=Cell_UCSF_12 SUBJECT_SAMPLE_FACTORS - 13 Variant:KP4_WT | Sample source:Pancreatic cancer cells Replicate=3; RAW_FILE_NAME(Raw File name)=Cell_UCSF_13 SUBJECT_SAMPLE_FACTORS - 14 Variant:KP4_WT | Sample source:Pancreatic cancer cells Replicate=4; RAW_FILE_NAME(Raw File name)=Cell_UCSF_14 SUBJECT_SAMPLE_FACTORS - 15 Variant:KP4_WT | Sample source:Pancreatic cancer cells Replicate=5; RAW_FILE_NAME(Raw File name)=Cell_UCSF_15 SUBJECT_SAMPLE_FACTORS - 16 Variant:KP4_R46L | Sample source:Pancreatic cancer cells Replicate=1; RAW_FILE_NAME(Raw File name)=Cell_UCSF_16 SUBJECT_SAMPLE_FACTORS - 17 Variant:KP4_R46L | Sample source:Pancreatic cancer cells Replicate=2; RAW_FILE_NAME(Raw File name)=Cell_UCSF_17 SUBJECT_SAMPLE_FACTORS - 18 Variant:KP4_R46L | Sample source:Pancreatic cancer cells Replicate=3; RAW_FILE_NAME(Raw File name)=Cell_UCSF_18 SUBJECT_SAMPLE_FACTORS - 19 Variant:KP4_R46L | Sample source:Pancreatic cancer cells Replicate=4; RAW_FILE_NAME(Raw File name)=Cell_UCSF_19 SUBJECT_SAMPLE_FACTORS - 20 Variant:KP4_R46L | Sample source:Pancreatic cancer cells Replicate=5; RAW_FILE_NAME(Raw File name)=Cell_UCSF_20 SUBJECT_SAMPLE_FACTORS - 39 Variant:KP4 | Sample source:Pancreatic cancer cells Replicate=1; RAW_FILE_NAME(Raw File name)=Cell_UCSF_39 SUBJECT_SAMPLE_FACTORS - 40 Variant:KP4 | Sample source:Pancreatic cancer cells Replicate=2; RAW_FILE_NAME(Raw File name)=Cell_UCSF_40 SUBJECT_SAMPLE_FACTORS - 41 Variant:KP4 | Sample source:Pancreatic cancer cells Replicate=3; RAW_FILE_NAME(Raw File name)=Cell_UCSF_41 SUBJECT_SAMPLE_FACTORS - 48 Variant:HPAC | Sample source:Pancreatic cancer cells Replicate=1; RAW_FILE_NAME(Raw File name)=Cell_UCSF_48 SUBJECT_SAMPLE_FACTORS - 49 Variant:HPAC | Sample source:Pancreatic cancer cells Replicate=2; RAW_FILE_NAME(Raw File name)=Cell_UCSF_49 SUBJECT_SAMPLE_FACTORS - 50 Variant:HPAC | Sample source:Pancreatic cancer cells Replicate=3; RAW_FILE_NAME(Raw File name)=Cell_UCSF_50 SUBJECT_SAMPLE_FACTORS - 51 Variant:STD_1 | Sample source:STANDARD Replicate=1; RAW_FILE_NAME(Raw File name)=00_STD_2x7DHC8t5_7DHDes4t5_S02 SUBJECT_SAMPLE_FACTORS - 52 Variant:STD_2 | Sample source:STANDARD Replicate=1; RAW_FILE_NAME(Raw File name)=00_STD_2x7DHC8t5_7DHDes4t5_S03 SUBJECT_SAMPLE_FACTORS - 53 Variant:STD_3 | Sample source:STANDARD Replicate=1; RAW_FILE_NAME(Raw File name)=00_STD_2x7DHC8t5_7DHDes4t5_S04 SUBJECT_SAMPLE_FACTORS - 54 Variant:STD_4 | Sample source:STANDARD Replicate=1; RAW_FILE_NAME(Raw File name)=00_STD_2x7DHC8t5_7DHDes4t5_S05 SUBJECT_SAMPLE_FACTORS - 55 Variant:STD_5 | Sample source:STANDARD Replicate=1; RAW_FILE_NAME(Raw File name)=00_STD_2x7DHC8t5_7DHDes4t5_S06 SUBJECT_SAMPLE_FACTORS - 56 Variant:STD_6 | Sample source:STANDARD Replicate=1; RAW_FILE_NAME(Raw File name)=00_STD_2x7DHC8t5_7DHDes4t5_S07 SUBJECT_SAMPLE_FACTORS - 57 Variant:STD_7 | Sample source:STANDARD Replicate=1; RAW_FILE_NAME(Raw File name)=00_STD_2x7DHC8t5_7DHDes4t5_S08 #COLLECTION CO:COLLECTION_SUMMARY HPAC and KP4 pancreatic cancer cell lines were obtained from the American Type CO:COLLECTION_SUMMARY Culture Collection (ATCC) or DSMZ. All cell lines were cultured in DMEM media CO:COLLECTION_SUMMARY (Gibco) supplemented with 10% FBS (Atlanta biologicals), 1% CO:COLLECTION_SUMMARY Pencillin/Streptomycin (Gibco) and 15mM HEPES (Gibco) and grown in a humidified CO:COLLECTION_SUMMARY chamber at 37°C, 5% CO2. Cells were trypsinized using TrypLE (Gibco). Routine CO:COLLECTION_SUMMARY mycoplasma testing was performed using the Mycoplasma PCR detection kit (Abm; CO:COLLECTION_SUMMARY Cat. Number G238) at least once a month and the cell lines were authenticated by CO:COLLECTION_SUMMARY STR fingerprinting. Cell lines are passaged for a maximum of 15 passages upon CO:COLLECTION_SUMMARY thawing prior to replacement. To perform the experiments cells were washed with CO:COLLECTION_SUMMARY PBS, detached and washed again two times with PBS before pellet freezing. KP4 CO:COLLECTION_SUMMARY WT, D374Y and R46L are expressing different human PCSK9 variants: WT, D374Y CO:COLLECTION_SUMMARY (active variant), and R46L (inactive variant). KP4 control cells express a CO:COLLECTION_SUMMARY control vector and KP4 WT express WT PCSK9. KP4 and HPAC are parental cells. CO:SAMPLE_TYPE Pancreatic cancer cells #TREATMENT TR:TREATMENT_SUMMARY Cell pellets were collected and suspended in 500 μL of TR:TREATMENT_SUMMARY water-methanol-chloroform (1 :5 :2) in Eppendorf tubes. The samples were TR:TREATMENT_SUMMARY homogenized on a MM 400 mill mixer with the aid of two 3-mm metal balls and at a TR:TREATMENT_SUMMARY shaking frequency of 30Hz for 3min.The homogenization step was repeated two more TR:TREATMENT_SUMMARY times. The samples were then ultra-sonicated in an ice-water bath for 2 min and TR:TREATMENT_SUMMARY subsequently centrifuged at 21,000 g and 5°C for 10 min. The clear supernatants TR:TREATMENT_SUMMARY were collected for the following LC-MS analysis and the precipitated pellets TR:TREATMENT_SUMMARY were used for protein assay by UV-VIS spectroscopy using a standardized Bradford TR:TREATMENT_SUMMARY procedure. No specific treatment was performed before the speficic mass TR:TREATMENT_SUMMARY spectrometry processing protocol. #SAMPLEPREP SP:SAMPLEPREP_SUMMARY Cell pellets were collected and suspended in 500 μL of SP:SAMPLEPREP_SUMMARY water-methanol-chloroform (1 :5 :2) in Eppendorf tubes. The samples were SP:SAMPLEPREP_SUMMARY homogenized on a MM 400 mill mixer with the aid of two 3-mm metal balls and at a SP:SAMPLEPREP_SUMMARY shaking frequency of 30Hz for 3min.The homogenization step was repeated two more SP:SAMPLEPREP_SUMMARY times. The samples were then ultra-sonicated in an ice-water bath for 2 min and SP:SAMPLEPREP_SUMMARY subsequently centrifuged at 21,000 g and 5°C for 10 min. The clear supernatants SP:SAMPLEPREP_SUMMARY were collected for the following LC-MS analysis and the precipitated pellets SP:SAMPLEPREP_SUMMARY were used for protein assay by UV-VIS spectroscopy using a standardized Bradford SP:SAMPLEPREP_SUMMARY procedure.Specifically, Serially diluted standard solutions of SP:SAMPLEPREP_SUMMARY 7-dehydrocholesterol and 7-dehydrodesmosterol were prepared in acetonitrile. SP:SAMPLEPREP_SUMMARY The concentration range of each compound ranged from 0.00001µM to 1 µM with SP:SAMPLEPREP_SUMMARY STD1 being the highest concentration and STD7 the lowest. Next, 100 μL of SP:SAMPLEPREP_SUMMARY the clear supernatant extractant from each sample was mixed with 300 μL of 50% SP:SAMPLEPREP_SUMMARY methanol and 150 μL of chloroform. After vortex-mixing for 30 s and centrifugal SP:SAMPLEPREP_SUMMARY clarification at 10,000 g for 2 min, the lower organic phase was collected and SP:SAMPLEPREP_SUMMARY dried under a gentle nitrogen gas flow. The residue was dissolved in 100 µL of SP:SAMPLEPREP_SUMMARY acetonitrile. To 50 µL of the sample solution or each standard solution, 450 SP:SAMPLEPREP_SUMMARY µL of 10-mM 4-phenyl-1,2,4-triazoline-3,5-dione solution in acetonitrile was SP:SAMPLEPREP_SUMMARY added. The mixtures were incubated at room temperature for 2 h on a Thermomixer SP:SAMPLEPREP_SUMMARY at a shaking frequency of 600 rpm. 10 µL aliquots of the resultant solutions SP:SAMPLEPREP_SUMMARY were injected into an Agilent Eclipse C18 (2.1*50 mm, 1.8 µm) column to run SP:SAMPLEPREP_SUMMARY LC-MRM/MS on an Agilent 1290 UHPLC system coupled to a Sciex 7500 QQQ mass SP:SAMPLEPREP_SUMMARY spectrometer operated in the positive-ion detection mode, using 0.1% formic acid SP:SAMPLEPREP_SUMMARY in water (A) and 0.1% formic acid in acetonitrile (B) as the mobile phase for SP:SAMPLEPREP_SUMMARY binary-solvent gradient elution under optimized LC separation and MRM/MS SP:SAMPLEPREP_SUMMARY detection conditions SP:SAMPLE_DERIVATIZATION Dansyl chloride #CHROMATOGRAPHY CH:CHROMATOGRAPHY_SUMMARY Agilent Eclipse C18 (2.1*50 mm, 1.8 µm) column The gradient began at 65% B at 0 CH:CHROMATOGRAPHY_SUMMARY min, shifted to 50% B over 9 min, 100% B from 9 min to 9.1 min, then stayed at CH:CHROMATOGRAPHY_SUMMARY 100% B for 0.9 min before ramping down to 65% B in 0.1 min and stayed at 65% B CH:CHROMATOGRAPHY_SUMMARY for 3.9 min, at 0.26 mL/min and 50 C. CH:CHROMATOGRAPHY_TYPE Reversed phase CH:INSTRUMENT_NAME Agilent 1290 CH:COLUMN_NAME Agilent ZORBAX Eclipse Plus C18 (50 x 2.1mm,1.8um) CH:SOLVENT_A 100% water; 0.1% formic acid CH:SOLVENT_B 66.67% isopropanol/33.33% acetonitrile; 0.1% formic acid CH:FLOW_GRADIENT The gradient began at 65% B at 0 min, shifted to 50% B over 9 min, 100% B from 9 CH:FLOW_GRADIENT min to 9.1 min, then stayed at 100% B for 0.9 min before ramping down to 65% B CH:FLOW_GRADIENT in 0.1 min and stayed at 65% B for 3.9 min CH:FLOW_RATE 0.26 mL/min CH:COLUMN_TEMPERATURE 50°C #ANALYSIS AN:ANALYSIS_TYPE MS #MS MS:INSTRUMENT_NAME ABI Sciex 7500 QQQ MS:INSTRUMENT_TYPE Triple quadrupole MS:MS_TYPE ESI MS:ION_MODE POSITIVE MS:MS_COMMENTS Concentrations of the compounds detected in the samples were calculated by MS:MS_COMMENTS interpolating their constructed linear-regression calibration curves with MS:MS_COMMENTS internal standard calibration or external standard calibration. #MS_METABOLITE_DATA MS_METABOLITE_DATA:UNITS pmol/mg protein MS_METABOLITE_DATA_START Samples 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 39 40 41 48 49 50 51 52 53 54 55 56 57 Factors Variant:KP4_Control | Sample source:Pancreatic cancer cells Variant:KP4_Control | Sample source:Pancreatic cancer cells Variant:KP4_Control | Sample source:Pancreatic cancer cells Variant:KP4_Control | Sample source:Pancreatic cancer cells Variant:KP4_Control | Sample source:Pancreatic cancer cells Variant:KP4_D374Y | Sample source:Pancreatic cancer cells Variant:KP4_D374Y | Sample source:Pancreatic cancer cells Variant:KP4_D374Y | Sample source:Pancreatic cancer cells Variant:KP4_D374Y | Sample source:Pancreatic cancer cells Variant:KP4_D374Y | Sample source:Pancreatic cancer cells Variant:KP4_WT | Sample source:Pancreatic cancer cells Variant:KP4_WT | Sample source:Pancreatic cancer cells Variant:KP4_WT | Sample source:Pancreatic cancer cells Variant:KP4_WT | Sample source:Pancreatic cancer cells Variant:KP4_WT | Sample source:Pancreatic cancer cells Variant:KP4_R46L | Sample source:Pancreatic cancer cells Variant:KP4_R46L | Sample source:Pancreatic cancer cells Variant:KP4_R46L | Sample source:Pancreatic cancer cells Variant:KP4_R46L | Sample source:Pancreatic cancer cells Variant:KP4_R46L | Sample source:Pancreatic cancer cells Variant:KP4 | Sample source:Pancreatic cancer cells Variant:KP4 | Sample source:Pancreatic cancer cells Variant:KP4 | Sample source:Pancreatic cancer cells Variant:HPAC | Sample source:Pancreatic cancer cells Variant:HPAC | Sample source:Pancreatic cancer cells Variant:HPAC | Sample source:Pancreatic cancer cells Variant:STD_1 | Sample source:STANDARD Variant:STD_2 | Sample source:STANDARD Variant:STD_3 | Sample source:STANDARD Variant:STD_4 | Sample source:STANDARD Variant:STD_5 | Sample source:STANDARD Variant:STD_6 | Sample source:STANDARD Variant:STD_7 | Sample source:STANDARD 7-Dehydrocholesterol 747.095569 571.024077 902.953631 1197.426395 1125.49759 7168.896312 9283.805793 3761.739927 2479.290345 2249.193819 375.41794 416.126907 4345.776136 4228.97696 5224.654874 579.850009 526.599358 3631.630486 2466.525991 2089.367108 63.552209 62.835299 51.540777 121.064303 92.550982 86.145937 N/A N/A N/A N/A N/A N/A N/A 7-Dehydrodesmosterol 34.254777 32.470984 6.215894 7.068508 7.068773 580.078633 682.3994 610.10392 28.091375 23.494704 78.009412 96.524283 254.327081 248.822096 332.314958 54.470758 54.373473 106.012093 35.495666 24.725216 8.551942 12.085504 9.968921 14.827474 14.613551 13.66286 N/A N/A N/A N/A N/A N/A N/A MS_METABOLITE_DATA_END #METABOLITES METABOLITES_START metabolite_name Kegg_ID 7-Dehydrocholesterol C04831 7-Dehydrodesmosterol C15631 METABOLITES_END #END