Lineage specific extracellular vesicle-associated protein biomarkers for the early detection of high grade serous ovarian cancer

High grade serous ovarian carcinoma (HGSOC) accounts for ~ 70% of ovarian cancer cases. Non-invasive, highly specific blood-based tests for pre-symptomatic screening in women are crucial to reducing the mortality associated with this disease. Since most HGSOCs typically arise from the fallopian tubes (FT), our biomarker search focused on proteins found on the surface of extracellular vesicles (EVs) released by both FT and HGSOC tissue explants and representative cell lines. Using mass spectrometry, 985 EV proteins (exo-proteins) were identified that comprised the FT/HGSOC EV core proteome. Transmembrane exo-proteins were prioritized because these could serve as antigens for capture and/or detection. With a nano-engineered microfluidic platform, six newly discovered exo-proteins (ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF) plus a known HGSOC associated protein, FOLR1 exhibited classification performance ranging from 85–98% in a case-control study using plasma samples representative of early (including stage IA/B) and late stage (stage III) HGSOCs. Furthermore, by linear combination of IGSF8 and ITGA5 based on logistic regression analysis, we achieved a sensitivity of 80% (99.8% specificity). These lineage-associated exo-biomarkers have potential to detect cancer while localized to the FT when patient outcomes are more favorable.


Introduction
Epithelial ovarian cancer is associated with an overall mortality of ~ 70% but can be cured in up to 90% of cases if diagnosed early while still restricted to the ovaries and fallopian tubes [1][2][3][4] . Unfortunately, most cases, including the most aggressive and deadly form of ovarian cancer 5 , i.e., high grade serous ovarian cancer (HGSOC), are diagnosed in the late stages, when the ve-year survival rate falls below 30% 4 .
Disappointingly, only about 15% of the cases are localized to the reproductive tissues at the time of diagnosis 6 . Therefore, only a few cases are cured. The lack of precise early warning signs is one of the contributing factors to the small percentage of detection of ovarian tumors in stage I/II [7][8][9] . EOC screening requires surgical methods for a con rmatory diagnosis, in contrast to breast cancer where a biopsy can be used to diagnose the disease 6, 10 . Given the low prevalence of this cancer in the postmenopausal women (~ 1 in 2,500) effective screening strategies are needed to achieve a positive predictive value (PPV) higher than 10% (one positive surgery out of 10) [10][11][12][13] .
The two most used ovarian screening tests in the clinic are transvaginal ultrasound (TVS) and a blood test quantifying the serum level of CA-125, which is often not reliable given elevated CA-125 levels are also caused by non-malignant gynecological conditions 14,15 . When a mass is found with TVS, a more invasive biopsy is required. Ideally, a non-invasive route for diagnosis is preferred, but there is currently no consensus on a blood-based biomarker panel for the early detection of this disease.
The UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) has led the way to determine if population screening can reduce deaths due to the disease with over 200,000 postmenopausal women recruited in this study. When the risk of ovarian cancer algorithm (ROCA) was combined with TVS for women who had elevated CA-125 (a multimodal screening approach), this approach resulted in a combined speci city of 99.8% with a 22% PPV and a modest increase in the detected early stage EOC cases 10,16 . However, after 16.3 years of long-term follow-up this screening trial did not yield promising results because the mortality rates were not signi cantly reduced even with screening 17 . This clinical problem underscores the importance of identifying blood-based biomarkers for detecting cancers early when the disease is more manageable.
To further complicate the screening for ovarian cancer, recent studies continue to support the hypothesis that most HGSOCs arise from the fallopian tube (FT) epithelium, speci cally the secretory cells in the mbriated end [18][19][20] . The development of the earliest steps in the pathogenesis of HGSOC is thought to take decades; however, recent molecular studies have suggested that the transition from a serous tubal intraepithelial carcinoma (STIC) into a metastatic ovarian carcinoma occurs much more rapid; between 6 to 7 years 18, 21 . Once the tumor cell leaves the fallopian tube the disease spreads rapidly and is hard to cure with existing therapies. In fact, one might contemplate renaming this "ovarian cancer" subtype given the tissue of origin. If this biology is indeed correct, we hypothesized that identifying novel FT-associated protein biomarkers during STIC development would provide clinicians a window of opportunity to diagnose the disease at an earlier stage and to surgically remove one or both fallopian tubes (salpingectomy) to reduce the chance of metastasis. There is new evidence that opportunistic salpingectomy in patients already undergoing pelvic surgery for benign disease such as a hysterectomy may signi cantly decrease ovarian cancer risk 22,23 which the Society of Gynecologic Oncology has recommended. Also, the SOROCk (Salpingo-Oophorectomy to Reduce the risk of Ovarian Cancer -NCT04251052) clinical trial is currently recruiting women to determine the e cacy of bilateral salpingectomy with delayed oophorectomy in high risk women for ovarian cancer prevention.
To detect HGSOCs in its early forms and through non-invasive methods, we focused on novel proteins in extracellular vesicles (EVs) (exo-protein biomarkers). EVs are nanosized particles that are between 30 nm − 1 µm in diameter 24 . EVs are typically formed when vesicles bud off from the plasma membrane of live or dying cells (shedding microvesicles or apoptotic bodies, respectively) or when endosomes (late or recycling) fuse to the plasma membrane which results in the release of multivesicular bodies including small EVs (a.k.a. exosomes) 25 . EVs contain nucleic acids, lipids, and proteins that re ect the cargo of the cell of origin 26 . Many studies have shown that tissue explants are a rich source of these EVs, and that these EVs contain potential biomarkers for various diseases 27 . For the proteomic pro ling studies presented in this manuscript, we use the term EVs to describe vesicles recovered in the 100,000 x g centrifugation step, which are primarily 50-200 nm in size.
Several studies, including ours have used micro uidic devices to capture EVs and quantify levels of proteins such as CD24, CA-125, EpCAM, EGFR, HER2 and/or FOLR1 from ovarian cancer patients' plasma or ascites samples [28][29][30][31][32] . Although these previous studies are promising, there is a still a need to uncover lineage speci c biomarkers for cancers originating in the fallopian tubes to increase the sensitivity and speci city of these tests to support screening studies, especially in women with who are at an increased risk (e.g., BRCA1 and BRCA2 mutation carriers).
To address this clinical need we performed extensive proteomic analyses by mass spectrometry of EVs enriched from healthy FT and HGSOC short-term tissue explants, as well as established fallopian tube secretory epithelial cells (FTSEC)-and HGSOC-derived cell lines. We report the identi cation of EVassociated proteins that have potential to serve as circulating early detection biomarkers of HGSOC that can be detected in a few drops of blood. We hypothesized that EVs from tissue explants could identify relevant biomarkers for human disease and complement those found using cultured cells, which is not exposed to other cell types in the tumor microenvironment 33 as would the tissue explants. From these studies, we identi ed 7 transmembrane candidate protein markers (ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF and STX4) on EVs derived from FT and HGSOC explants. We further evaluated these candidate markers in clinical samples from women diagnosed with HGSOC and healthy age/race matched controls using a novel nano-engineered micro uidic platform (ExoPro le chip 32 ) and showed that these markers exhibit high area under the curve (AUC) values ranging from 0.85-0.98 as calculated using receiver operating characteristic (ROC) analysis. When multi-marker analysis was performed, the combination of IGSF8 and ITGA5 yielded the greatest degree of sensitivity and speci city in this cohort.
Previous studies have focused on other types of cancer such as colorectal cancer, lung cancer, melanoma, and pancreatic cancer 27,34 . To our knowledge, this is the rst study to comprehensively compare the proteomes of EVs from short-term cultures of tissue explants of primary FT and HGSOC with those from established and representative FTSEC and HGSOC cell lines. This study suggests that enrichment and characterization of EVs from short-term cultures of tissue explants maybe a valuable and complementary approach to uncover additional circulating biomarkers not observed with cultured cells.
Our study highlights the importance of tissue derived EVs in biomarker discovery and may have biological implications on the disease pathogenesis of HGSOC.

Results
Enrichment and characterization of EVs derived from patient HGSOC and healthy fallopian tube tissue explants and cell lines Conditioned media was collected from 3 FT cell lines (FT240, FT246 and FT282), 6 HGSOC cell lines (OVCAR2, OVCAR3, OVCAR4, OVCAR8, PEO1 and PEO4) and 21 fresh tissue explants (HGSOC primary tumor tissues, n = 9, HGSOC omental metastases, n = 6, and healthy FT tissue specimens, n = 6) ( Fig. 1a & Supplementary File 1). For these studies, we chose the 24 h time point for tissue media collection since the number of total particles decreased by at least 55% within 48 h ( Supplementary Fig. 1). This observation might be attributed to the decrease in growth factors once the media is replaced at 24 h. The collected media was then processed by differential ultracentrifugation 27 to enrich for the EVs. We characterized representative EVs puri ed from either cell lines or tissue explants by nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), single particle interferometric re ectance imaging sensing (SP-IRIS) and uorescence following the Minimum Information for Studies of Extracellular Vesicles 2018 guidelines 35 (Fig. 1b-d & Supplementary Fig. 2-3). By NTA, most particles were between 120-160 nm in size ( Fig. 1b & Supplementary Fig. 3a). Using negative staining followed by TEM, we observed EVs to have the typical cup shaped morphology with a size range between 32-128 nm ( Fig. 1c & Supplementary Fig. 3b). By SP-IRIS, the mode size for the EVs is 50 nm ( Supplementary   Fig. 3c). The variation in EV particle size as detected by NTA, TEM, and SP-IRIS and uorescence is likely due to the differences in instrument sensitivities and their limitations (Fig. 1b-c & Supplementary Fig. 3ac). With SP-IRIS and uorescence, we found that both cell line and tissue explant EVs either from FT or HGSOC expressed common tetraspanin markers, e.g., CD9, CD63 and CD81 (Fig. 1d & Supplementary  Fig. 3d). We also observed that tissue explant derived EVs had a higher percentage of CD63 single positive EVs compared to cell line derived EVs (Fig. 1d) whereas FT cell lines and HGSOC cell lines displayed a higher CD9 + population, as well as double positive CD9 + CD81 + EV populations compared to the tissue explant derived EVs (Fig. 1d, Supplementary Fig. 3d & Supplementary Fig. 4). This nding could be due to the presence of additional cell populations (e.g., tumor stroma) present in the tissue explants releasing EVs or the overall differences in the biogenesis of tissue derived EVs compared to that of cell line EVs, similar to how 2D culture and 3D culture derived EVs differ in EV populations 36 .

Identi cation of FT and HGSOC core proteome
After EV characterization, we performed proteomic pro ling and an analysis pipeline (Fig. 2a) to establish the EV proteome of FT and HGSOC (for both tissue and cell lines) via liquid chromatography tandem mass spectrometry (LC-MS/MS) 27,34 , with the goal of identifying putative transmembrane exo-proteins that can ultimately be used to perform immunocapture and detection of intact EVs from clinical samples.
To determine which exo-proteins were to be included in subsequent analyses, a criteria was set such that a protein was included only if it was detected in at least two out of the three biological replicates for the HGSOC or in both biological replicates for the FT cell lines. For the tissue explants, the criteria required that the proteins were detected in all the biological replicates within their respective set. Using this approach, approximately 2,200 to 3,200 exo-proteins were identi ed in each sample (Fig. 2b). Then, we calculated the relative abundance of the common EV markers using our proteomic data and found that most of these markers were identi ed at similar levels in both the cell line and tissue explant derived EVs (Fig. 2c). However, a common EV marker, CD63, was detected at relatively low levels or was undetectable in EVs, as observed in previous studies 27 . Lack of representation in the mass spectrometry data is likely due to the CD63 being heavily glycosylated 37 . As mentioned earlier, we found that CD63 + EVs was predominately present in tissue explants derived EVs using SP-IRIS and uorescence. Our ndings also support a recent study that proposed syntenin-1 (SDCBP) to be a putative universal EV marker 38 as this protein was detected at relatively similar levels across all the EV samples (both tissue and cell linederived). In addition, we examined the relative quantitation of serum-based proteins that are reported in literature or included in biomarker-based algorithms for ovarian cancer, i.e., CA-125 39 ; ROCA multimodal screening 10,17 ; the multivariate ROMA 40 test; and the FDA approved OVA1 41 test. Importantly, these serum markers were also found in the EVs used in our study ( Supplementary Fig. 5).
After this initial assessment of the data quality by comparing levels of the canonical EV markers as well as presence of existing serum markers from the tests mentioned above, we ltered the data furthered by comparing the EV proteins from tissue explants with their respective cell lines (e.g., HGSOC or FT) to increase the speci city of the EV proteins to their site of origin ( Fig. 2d-e). We then compared the 1,309 proteins found in the HGSOC group with the 1,193 proteins found in the FT group to identify 985 EV proteins that are common between the two groups which we termed as FT/HGSOC core proteome (

Identi cation of transmembrane proteins
The above ROC analysis is useful for identifying differences between FT and HGSOC samples. However, for this study, we are interested in 1) lineage-associated markers, i.e., exo-protein biomarkers present in FT epithelium that are preserved in HGSOC, and 2) exo-protein biomarkers that would be suitable for both immunocapture and on chip detection using our micro uidic ExoPro le chip. Therefore, we focused on prioritizing exo-proteins within the 985 FT/HGSOC core proteome which are more likely to be displayed on the surface of EVs, thus making them suitable biomarker for screening and early detection.  Table 1). We then subtracted common EV proteins by comparing to the list of top 100 EV-associated proteins found in ExoCarta and Vesiclepedia databases. This narrowed the list to 66 transmembrane exo-proteins not commonly observed in EVs (Fig. 2h). We calculated the fold differences for these 66 proteins in the FTand HGSOC-derived EVs and selected those that showed a log 2 fold-change ≥ -0.58 to identify proteins present in the FT samples and which increase in expression as the disease progresses to HGSOC (Supplementary Table 1). This approach resulted in a ranked list of 47 exo-proteins. Several of these proteins are integrins which have been implicated in cancer cell proliferation, migration and invasion 43 . Integrins have also been shown to be essential for EV homing and act as seeds that condition the favorable formation of tumor niches 24,44 . In addition, two of these proteins, IGHM and ADAM10, were found to be common EV proteins reported in literature 34,35,45 , which were not previously in listed in the ExoCarta and Vesiclepedia databases so they were manually removed from further analysis.  Table 1) to con rm their presence within cell line derived EVs to support the LC-MS/MS data. Of the proteins detected by Wes, we found that ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF and STX4 were present in the FT and HGSOC cell line EVs tested (Fig. 3& Supplementary Fig. 6). These exo-protein biomarkers were prioritized for further analysis. The other exo-proteins failed to be detected due to challenges with available commercial antibodies or they did not meet our strict criteria requiring that the exo-proteins be present in EVs derived from all the FT and HGSOC cell line samples. These were excluded from additional analysis.

Evaluation of candidate biomarker transmembrane proteins in clinical samples
Since these seven transmembrane exo-proteins (ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF and STX4) are present in FT and HGSOC cell lines, we next measured the expression of these proteins via immunohistochemistry (IHC) to con rm the tissues of origin. We created a tissue microarray (TMA) using samples from 100 patients with most of the samples having matching primary tumor, metastatic tumor, and a healthy region of fallopian tube tissue (Supplementary File 1). Following staining, a pathologist reviewed and scored each core ( Fig. 4a & Supplementary Fig. 7). We found that all transmembrane proteins were expressed to varying degrees in healthy FT tissue, and in both primary and metastatic tumors. We included FOLR1 as a positive control since it has been shown to be highly expressed in ovarian tumors compared to healthy tissue but is decreased in platinum-resistant ovarian tumors compared to drug-sensitive tumors 46,47 . ITGA2 showed lower expression in all tissues compared to all the other proteins. Furthermore, we stained FT tissues with STIC lesions, based on being the precursors for most HGSOCs, obtained from risk-reducing salpingo-oopherectomy (RRSO) specimens. We found that in both p53-overexpressed and p53-null STICs, most of the candidate biomarker proteins were expressed in these regions. Interestingly, ITGA2 was found to be only expressed in the p53-null STIC, while ITGB3 and ITGA5 demonstrated patches of staining within STIC lesions (Fig. 4b). The IHC protein expression results continued to support our hypothesis that these transmembrane proteins are present in the fallopian tube tissue and maintained during disease progression.
After con rming that these transmembrane proteins are present in tissues via IHC, we then tested these exo-proteins in patient plasma samples using a modi ed ExoPro le (Fig. 5a) micro uidic chip capable of EV immunocapture and uorescence detection 32 . We used this functionalized nano-engineered micro uidic platform to evaluate the diagnostic power of the FT/HGSOC exo-protein biomarkers. Based on our previous publications, exo-FOLR1 was able to differentiate ovarian patients (late and early stage) from benign and healthy controls with high speci city and sensitivity 32,48 . Therefore, we used FOLR1 as the positive control to assess the speci city and sensitivity of the current lineage speci c biomarkers being evaluated. Using the ExoPro le chip, speci cally developed to simultaneously measure multiple EVassociated analytes, we captured CD81 + EVs from plasma (n = 10 cases and n = 20 age/race matched controls -Supplementary File 1) and quanti ed the relative levels of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, and FOLR1 (Fig. 5b, unfortunately we were not able to test STX4 since an antibody compatible with the ExoPro le chip was not available). The clinical samples represented HGSOC patients with both early (FIGO Stage I-II; n = 5) or advanced stage (FIGO Stage III-IV, n = 5) disease. Importantly, all seven FT/HGSOC exo-protein biomarkers were detected at signi cantly higher levels in the HGSOC plasma (regardless of stages) relative to healthy plasma. We performed ROC analysis for each marker and found that four markers (ACSL4, ITGB3, ITGA5 and FOLR1) had an area under the curve (AUC) that is higher for early stage compared to healthy plasma versus late stage compared to healthy plasma (Supplementary Table 2). Since this sample set of diseased patients is relatively small, we proceeded with calculating all the ovarian cancer patients (n = 10) together instead of in separate groups (early or late stage) against the healthy controls (n = 20). We found that these markers had AUCs ranging from 0.85-0.98 (Fig. 5c & Table 1), which indicates a signi cant separation between diseased and healthy controls. In fact, exo-ITGA5 and exo-ITGB3 (AUC of 0.95 and 0.98, respectively) performed better than exo-FOLR1 (AUC of 0.925) which was a robust ovarian cancer biomarker based on our previous work 32 . We also performed various marker combinations of two or more markers and found that the linear combination of IGSF8 and ITGA5 based on logistic regression analysis yielded an AUC of 0.990 with a sensitivity of 0.80 at 99.8% speci city (Table 1& data not shown). Based on multivariable logistic regression analysis, the equation we derived for the best marker combination is as follows: Linear combination of IGSF8 & ITGA5 = 11.299 x log(IGSF8) + 14.935 x log(ITGA5). These results con rm that the lineage associated exo-protein biomarkers detected from proteomic pro ling of FT/HGSOC tissue-derived EVs can be incorporated onto the ExoPro le chip to develop a clinically relevant liquid biopsy test focused on the early detection of this disease, and potentially while con ned to the fallopian tubes.

Discussion
Developing non-invasive and highly speci c blood-based test for pre-symptomatic screening and early detection of ovarian cancer is crucial since no clinical trials have been successful in reducing the mortality rates of women with EOC 17 , and the currently available blood-based biomarkers have low speci city. Ultimately, our goal is to develop a highly speci c test that can detect HGSOC, the deadliest form of ovarian cancer, at its earlier stages, especially in women who are at increased risk of developing ovarian cancer (e.g., BRCA1 and BRCA2 mutation carriers). When translated into the clinic, these types of liquid-based assays can help identify at risk women in need of risk reducing salpingectomy (surgical removal of the fallopian tubes) without oophorectomy (removal of the ovaries). Not only would this approach reduce the their change of developing a deadly cancer, but could do so while retaining hormone production 7 . As reported, we have for the rst time identi ed candidate exo-biomarkers focused on lineage speci c proteins shared between fallopian tube epithelium and HGSOC. We demonstrated that these new ovarian cancer biomarkers could discriminate ovarian cancer cases from healthy controls. In fact, when we performed a separate analysis of the early stage compared to late stage versus healthy, four markers (ACSL4, ITGB3, ITGA5 and FOLR1) demonstrated higher AUC values (Supplementary  Table 2).
Several studies on various diseases have performed proteomic pro ling on EVs since these contain valuable information which can be translated into noninvasive diagnostic platforms 27 . In HGSOC, initial proteomic studies on EVs were performed on a few cell lines 49 . A study by Selvendiran and colleagues performed proteomic pro ling on CD63 + and EpCAM + EVs enriched using a micro uidic device from HGSOC, FTSEC and ovarian surface epithelial (OSE) cell lines but these studies were dependent on a single cell line per each type (OVCAR8, FT33 and OSE). From this study, IL-6, HGF and STAT3 were identi ed to be highly expressed in EVs from ovarian cancer patient serum 50 . EVs circulating in the blood can originate from any cell type either healthy or diseased. Thus, there is a growing need to de ne which subpopulations are signi cant to study. We hypothesized that evaluating protein expression on EVs found in FT tissue and shared with HGSOC cells has the capability to develop a clinically relevant assay to detect HGSOC at its earliest stages, i.e., while still con ned to the fallopian tube.
One study has published an in silico approach to identify membrane proteins by combining several databases namely, the Cancer Genome Atlas Research Network (TCGA), Genotype-Tissue Expression Project (GTEx) and the Human Protein Atlas 51 . Their study focused on predicted transmembrane proteins that have higher expression in HGSOC tissues compared to healthy tissues, while our study was more focused on shared exo-proteins between FT and HGSOC. When we compared their list of 1,451 transmembrane proteins identi ed via in silico approach 51 with our list of the 45 transmembrane exoproteins (Supplementary Table 1), we found that more than 50% of the EV transmembrane proteins (n = 27) were in common between the two data sets. More importantly, we identi ed 18 unique exo-proteins that were solely found in our EV data not previously discovered (Supplementary Table 1). Previously, this comparison was not possible because our study is the rst to generate a comprehensive analysis of FT/HGSOC EV proteome from tissues and cell lines. ACSL4 and ITGB3 were part of these 18 unique exoproteins, both of which were able to discriminate healthy from diseased patients using the ExoPro le assay.
Based on the exo-protein markers identi ed with the work ow we employed, we were able to narrow down the markers to seven proteins namely, ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF and STX4. Previous studies on protein levels of these markers have shown that ACSL4, ITGA5 and STX4 are highly upregulated in ovarian cancer tissues 52-54 , while ITGA2 was upregulated in omental tumors 55 . High protein expression levels of ACSL4, ITGA2 and ITGA5 have been implicated in poor prognosis 52,53,56 ; however, the low expression of ITGB3 in HGSOC has been associated with favorable prognosis 57 .
Moreover, ITGA2 has been shown to impart paclitaxel resistance 56 , while ITGA5 from ascitic tumor cells is essential for cancer associated broblasts to initiate peritoneal metastasis 58 . Interestingly, neither IGSF8 nor MYOF have been previously implicated in HGSOC or fallopian tube biology but MYOF in EVs from breast and pancreatic cancer cell lines has been shown to contribute to cancer progression via metastasis 59 . Although most of these markers appear to have been studied in ovarian cancer biology, our study results are the rst to report these as EV-associated biomarkers in this disease.
A caveat of this study is that most of the ovarian cancer patients' tissue samples obtained as short-term explants had been collected after neoadjuvant chemotherapy since this is the standard of care before performing a debulking surgery. The ideal situation would be to obtain tumor tissues from untreated patients, which could yield a slightly modi ed EV-associated proteomic pro le. We are aware of the possibility that systemic host responses from immune cell activation could in uence EV cargo, as well as tumor cellularity since these tissues would have varying amounts of tumor present in the tissues that we processed. This is speci cally why we used well characterized FT and HGSOC cell lines to con rm the epithelial origin of the biomarkers. Also, these studies did not assess post-translational modi cations such as glycosylation which typically occur in cancers. Collaborative efforts will be needed to expand the clinical samples, focusing on blood samples from women prior to risk reducing surgery who were diagnosed upon pathological examination with STIC lesions. Despite these limitations, our study is the rst to establish the protein content of tissue derived EVs from healthy fallopian tube, primary HGSOC and omental metastatic cancer tissues. Our focus was to identify lineage associated exo-proteins predicted to be transmembrane for immunocapture and detection which can advance clinical diagnostic applications. We have identi ed transmembrane proteins associated uniquely with FT and HGSOC EVs.
When these protein markers are used with our functionalized ExoPro le chip, we were able to distinguish the HGSOC patients (both early and late stage equally) from matched healthy individuals with high AUC values. Furthermore, when we combined IGSF8 and ITGA5 we achieved a sensitivity of 0.80 at 99.8% speci city. These results exceed the performance of clinically adopted serum multimarker panels, i.e., CA-125 (gold standard) and HE4 60,61 . Although this study was performed on a small set of cases and control, future studies will need to validate the sensitivity and speci city of these exo-biomarkers in clinical samples from other gynecological and non-gynecological malignancies, and ultimately asymptomatic-high risk women who subsequently are diagnosis of HGSOC.

Material and Methods
Human samples Primary HGSOCs tumors or metastatic tissue from the omentum were obtained from women with Stage II-IV HGSOCs who were undergoing tumor debulking surgery. Healthy FT tissues were obtained from patients undergoing salpingo-oophorectomy for various medical conditions, including hysterectomies for non-cancerous conditions. Archival formalin-xed para n-embedded (FFPE) FT tissue samples with STIC lesions were obtained from women undergoing RRSO after pathological review. Informed consent was obtained from all participants included in the study. The de-identi ed tissues obtained were minced into small pieces and placed in 6-well plates containing 3 mL of cell media. Cell media without supplements and without serum was added and placed in a humidi ed incubator at 37 °C with 5% CO 2 for 24 h. The conditioned media was collected and EVs were enriched from the media using differential ultracentrifugation as described below. Ovarian cancer cell lines (OVCAR2, OVCAR3, OVCAR4, OVCAR8, PEO1 and PEO4) were cultured in RPMI1640 media (Hyclone, Cytiva Life Sciences) supplemented with 10% (v/v) EV-depleted FBS (spun at 100,000 x g at 4 °C for at least 18 h and ltered using a 0.2 µm lter), 2.5% mg/mL insulin and 100 units/mL penicillin-streptomycin at 37 °C with 5% CO 2 . Conditioned media was collected when cells were at least 60% con uent. Conditioned media from each cell line was collected from either two separate passages (FT cells) or three separate passages (for HGSOC cells). Each collection was processed and maintained as an independent biological replicate even throughout the LC-MS/MS procedure and analysis.
Enrichment of EVs from conditioned media by differential ultracentrifugation Conditioned media from cell cultures and tissue explants was collected and centrifuged at 300 x g for 10 min to remove cell debris. The supernatant fraction was then centrifuged at 2,000 x g for 20 min to remove apoptotic bodies. This was followed with supernatant centrifugation at 10,000 x g to remove large microvesicles for 1 h followed by 100,000 x g spin to collect EVs. The EV pellets were washed and resuspended in PBS and spun for 1 h at 100,000 x g. The EV pellets were resuspended in PBS and stored at -80 °C.

Transmission electron microscopy
Glow-discharged carbon-coated copper grids were oated on the surface of a drop of 30 µL of EVs for 20 min. The grids were then rinsed with water followed by negative staining with 1% uranyl acetate for 5 s. Once the grids were dry, TEM images were taken using a JEM-1400 Transmission Electron Microscope (JEOL USA, Inc.) equipped with a Lab6 gun.
Nanoparticle tracking analysis (NTA) The concentration and size of the enriched EVs were analyzed using the NanoSight LM10 instrument (Malvern Panalytical Ltd). NTA was performed using a monochromatic 404 nm laser on EVs diluted in 0.2 µm ltered PBS. Three recordings of 60 s videos were taken per sample at camera level 13 using the NTA software version 2.3. Data was compiled using a custom MATLAB code.
Single particle interferometric re ectance imaging sensing and uorescence Enriched EV samples (17.5 µL each) were mixed with an equal volume of Solution A. The sample was then place on an ExoView chip and incubated overnight. 1 mL of Solution A was added, and this was shaken at 500 rpm for 3 min at room temperature. The chip was then washed three-times with incubation solution before adding the blocking solution containing tetraspanin antibodies (CD9, CD63 and CD81).
The chips were incubated for 1 h at room temperature. Incubation solution was added and shaking at 500 rpm for 3 min at room temperature was repeated. The ExoView chip was washed 3 times before adding rinse solution and was scanned using the ExoView R100 instrument (NanoView Biosciences). nScan 2.8.10 software was used for data acquisition and NanoViewer software was used for data analysis (both from NanoView Biosciences). The threshold used for cut-off was 500 arbitrary units of Simple Western assay (Wes) The concentration of EV proteins was established using the Bradford assay (Bio-Rad) according to manufacturer's instructions. Simple Western assay (Wes, ProteinSimple) was used for the detection of EV markers (CD81 and Flotillin-1) and proteins that were selected for further evaluation, namely ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF and STX4 (for additional details please see Supplementary Table 3).
EVs at a concentration of 0.4 µg/µL were used in these assays. The 12-230 kDa or 66-440 kDa Wes separation module and the secondary anti-mouse, anti-rabbit, and anti-goat detection modules were used following manufacturer's instructions. Chemiluminescent detection pro le was set at High Dynamic Range 4.0 and contrast was manually adjusted for each sample. Data were analyzed using the Compass software version 6.0.0. (ProteinSimple).

Immunohistochemistry staining of TMA and STICs
Unstained tissue slide sections of ve TMA blocks containing representative tissue cores of benign fallopian tube, primary and metastatic ovarian tumor tissues (n = 100) were provided by the KUMC BRCF.
Tissue microarrays were previously constructed by the BRCF staff using archival FFPE tissue blocks and were provided as a kind gift by Dr. Dineo Khabele (Washington University, St. Louis). Tissue sections were placed in xylene and rehydrated in ethanol baths of decreasing concentration. Antigen retrieval was performed by heating with citrate buffer in a pressure cooker for 15 min. Once at room temperature, endogenous peroxidase activity was blocked using BLOXALL blocking solution (Vector Laboratories) for 20 min, slides were washed followed by another blocking step using 2.5% normal horse serum for 30 min.
FT tissue sections containing STIC lesions were stained for p53 using an automated protocol optimized for the Dako Autostainer Link (Agilent) or for the candidate protein biomarkers using the manual IHC staining protocol described above.
EV immunoassay using the ExoPro le chip The ExoPro le chip was functionalized for antibody conjugation and anti-CD81 antibody was owed through the chip to coat the surface similar to previous methods 32 . De-identi ed plasma samples, rst processed to remove platelets (2,500 x g for 15 minutes), were centrifuged at 10,000 x g for 30 min at 4°C to remove large microvesicles. 10 µL of plasma was diluted to 100 µL and used to detect seven exoprotein biomarkers (ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, FOLR1 and MYOF) simultaneously. One channel was designated as the negative control (PBS) to measure any background uorescence. Assays were performed on the ExoPro le chip similar to those described previously 32 . Fluorescence images were captured using a Nikon Ti2 inverted uorescence microscope equipped with a LED excitation light source (Lumencor). Fluorescence intensity was quanti ed by processing and analyzing the images using ImageJ.

Bioinformatics analysis
Qualitative analysis (GO identi cation and network analysis) of the FT/HGSOC core proteome was analyzed using DAVID version 6.8. The protein-protein interaction network was obtained using STRING version 11.5. p-values were calculated using EdgeR analysis 64 . The log 2 fold change values and the adjusted p-values were used to de ne signi cant differential expression proteins. Qprot 65 v1.3.5 was used to calculate Z-statistics, log 2 (fold change) and FDR values. Qprot analysis was performed with a burn-in value of 2,000 and 10,000 iterations.
To identify monotone and non-monotone markers, we used the length of the ROC curve 42   Enrichment and characterization of cell line and tissue explant EVs. a) Surgical resections of healthy FT or tumor tissues were minced and used to initiate short-term tissue explants (cultured for 24 h) followed by collection of the conditioned media and processed by differential ultracentrifugation to enrich for EVs.
Likewise, conditioned media from the FT and ovarian cancer cell lines shown was collected and processed. Created with BioRender.com b) Representative NTA data. c) Sixty (60) EV particles were imaged, and their size was measured for representative samples by TEM at x30K magni cation. d) Shown are representative SP-IRIS and uorescence (ExoView) data of FT tissue explant derived EVs displaying the common tetraspanins observed with cell-line derived EVs: CD9 (blue), CD63 (pink) and CD81 (green).  Detection of predicted transmembrane proteins in FT and HGSOC cell line EVs using capillary western blotting. A total of 45 markers were evaluated by capillary western blotting. Only the exo-biomarkers that were detected and showed to be present in EVs derived from both HGSOC and FT cell lines are shown.
Those exo-biomarkers that were not detected due to limitations with antibodies for Wes or were weakly expressed, were not prioritized. In addition, CD81 and FLOT1 were evaluated as these are common EV markers. Full length unprocessed blots can be found in Supplementary Fig. 6.  Evaluation of transmembrane exo-proteins in plasma samples using ExoPro le chips. a) Image of an ExoPro le chip consisting of 8 nanopatterned parallel channels for EV capture. b) Quanti cation of transmembrane exo-protein biomarkers on captured CD81+ EVs for HGSOC (n=10) and healthy control (n=20) (dotted line signi es background uorescence from a negative control channel labeled as BKG).
FOLR1 was included as a previous positive control for HGSOC 32 . c) Area under the curve plot of receiver operating characteristic analyses for all the six markers and FOLR1 are shown.

Supplementary Files
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