Patent Application
20240026463
The present disclosure relates to protein biomarkers carried by circulating extracellular vesicles (EVs) to support screening of asymptomatic women who are at an increased risk of developing ovarian cancer (e.g., BRCA1 and BRCA2 mutation carriers). The proposed biomarkers are based on proteins found in EVs released from fallopian tube epithelium and maintained in the EVs associated with high grade serous ovarian cancer (HGSOC), i.e., lineage specific markers given this deadliest form of ovarian cancer arise in the fallopian tube. The biomarkers can be the proteins or the mRNA that encodes the proteins.
Over two-thirds of all women diagnosed with epithelial ovarian cancer are likely to die from the disease (>14,000 deaths annually). Even though epithelial ovarian cancer therapies have been researched, little progress has been made in the last few decades. Although the five-year survival rates for most other solid tumors have improved steadily, ovarian cancer remains an exception, making it the deadliest of all gynecological cancers and five times deadlier than breast cancer. Ovarian cancer is hard to detect in its early stages due to its vague symptoms. Women may experience constipation, bloating, pelvic/abdominal pain, trouble eating/feeling full quickly, urgency or frequency of urination. While ovarian cancer tends to occur in post-menopausal women, women at younger ages can be at risk due to genetic predisposition.
Treatment is more effective when diagnosed early, with a five-year survival rate of up to 90%. Unfortunately, most cases are not detected until after the cancer has spread, resulting in a dismal five-year survival rate of less than 30%. Current screening methods for ovarian cancer typically use a combination of a pelvic examination, transvaginal ultrasonography, and serum cancer antigen 125 (CA125), but these have minimal impact on improving mortality. Thus, there is a compelling unmet need to develop new molecular tools that can be used to diagnose early-stage endothelial ovarian cancer and/or assist in the clinical management of the disease after a diagnosis, given that over 220,000 women are living with ovarian cancer in the U.S. and are at risk of recurrence.
High grade serous ovarian carcinoma (HGSOC) accounts for ˜70% of ovarian cancer cases. Recent studies have shown that most HGSOCs are not truly ovarian in origin and often arise from the epithelial cells within the fimbriated end of the fallopian tubes. Molecular studies have suggested that the development from serous tubal intraepithelial carcinoma (STIC) to an adenocarcinoma can take between 6 to 7 years, thus providing a window of opportunity for diagnosis and treatment, such as opportunistic salpingectomy to prevent HGSOCs from developing. Early detection while in the fallopian tube could be essential, given that once the tumor cell leaves the fallopian tube the disease spreads rapidly and is hard to cure.
The foregoing and additional information regarding the background of epithelial ovarian cancer, extracellular vesicles and relation to cancer, detection strategies, and therapies can be found in the incorporated references.1-36
In some embodiments, a method of reporting a diagnosis of cancer in a subject is provided. The method can include obtaining a biological sample from the subject and measuring a presence or amount of a combination of biomarkers in the biological sample. The combination of biomarkers includes ITGB3 (CD61), ITGA2 (CD49b), ITGA5 (CD49e), FACL4 (ACSL4), IGSF8 (CD316), and MYOF, and optionally FOLR1 and/or optionally STX4. In some aspects, the presence of the biomarkers in the sample indicates the presence of cancer cells in the subject. In some aspects, an increased amount of the biomarkers in the sample (e.g., compared to a control or sample) indicates the presence of cancer cells in the subject. The method can include determining whether the presence or amount of the combination of biomarkers indicates the presence of cancer cells in the subject and then preparing a report on the presence of cancer cells in the subject. In some aspects, the report includes an association of the combination of biomarkers and the presence of cancer cells. The report is provided to the subject (e.g., including family or caretaker of the subject) or to a medical entity or medical practitioner. In some aspects, the cancer is ovarian cancer or a cancer of fallopian tube origin. In some aspects, the subject is a female human
In some embodiments, a method is provided for detecting a panel of extracellular vesicle-associated protein biomarkers in a female human. The biomarkers can be used for detecting cancer cells, such as those from epithelial ovarian cancer, or any cancer from a fallopian tube tissue origin. The method can include step a) for obtaining extracellular vesicle-associated proteins from a biological sample from a female human. Step b) includes providing a panel of binding agents to the extracellular vesicle-associated proteins, wherein the binding agents are configured to bind with extracellular vesicle-associated proteins of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF and optionally FOLR1, and optionally STX4. Step c) includes assaying for binding a plurality of the binding agents of the panel with the plurality of extracellular vesicle-associated proteins. Step d) includes detecting binding of the plurality of binding agents of the panel with the plurality of extracellular vesicle-associated proteins, the detected plurality of extracellular vesicle-associated proteins being the extracellular vesicle-associated protein biomarkers. Step e) includes preparing a report on the detection of binding of the binding agents to the extracellular vesicle-associated proteins of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF and optionally STX4. Step 0 includes providing the report to the subject or to a medical entity or medical practitioner. These steps can be performed as described herein or otherwise known. In some aspects, the panel of binding agents are designed to be selective for at least ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF based on a higher area under curve (AUC) over a negative control. That is, each binding agent is selective for only one of the biomarkers, wherein the selectivity can be suitable for providing the selectivity in accordance with the data provided herein. In some aspects, the panel of binding agents are selective for at least ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, and STX4 based on higher area under curve (AUC) over a negative control (e.g., no cancer or non-ovarian cancer cases). In some aspects, the panel of binding agents are selective for at least ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, and FOLR1 based on higher area under curve (AUC) over a negative control (e.g., no cancer or non-ovarian cancer cases). In some aspects, the panel of binding agents are selective for at least ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, STX4 and FOLR1 based on higher area under curve (AUC) over a negative control (e.g., no cancer or non-ovarian cancer cases).
In some embodiments, the method can further include selecting the female human by at least one of several factors. For example, the female human subject can be suspected of having ovarian cancer or is at an increased life-time risk of developing ovarian cancer, due to carrying an inherited mutations in BRCA1, BRCA2 or other cancer susceptibility genes. Also, the female human subject can be identified as being labeled as being in a risk group for developing ovarian cancer base on family history of breast and/ovarian cancer. Additionally, the female human subject can be identified as being devoid of symptoms of ovarian cancer and these biomarkers can be used to screen average risk women over the age of 55 (or postmenopausal).
In some embodiments, the method described herein can include obtaining and presenting information in the report. The report can be prepared based on the data of the binding of the binding agents with the biomarkers. Accordingly, the report can be prepared, whether manually or by automation, to include one or more of: an identification of the ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF and optionally STX4 and optionally FOLR1 as biomarkers of ovarian cancer or cancer of fallopian tube origin; a measurement data that indicates a presence or increased amount of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF, and optionally STX4; a measurement data of control for ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF, and optionally STX4; a statement of possible outcomes of ovarian cancer; a statement of treatments for ovarian cancer, wherein the treatments are selected from chemotherapy, radiation therapy, surgical removal of ovarian cancer, or combinations thereof; a statement of possible outcomes of treatments for ovarian cancer; or a listing of medical entities that perform, oversee, or control the treatments for ovarian cancer.
In some embodiments, a panel of binding agents is provided, wherein the binding agents are configured for binding with extracellular vesicle-associated protein biomarkers of ovarian cancer. The binding agent can be any type of binding agent, such as antibodies, antibody fragments, aptamers, binding ligands, combinations thereof, or any molecule that selectively binds with the protein biomarker. In some aspects, the plurality of binding agents are configured to bind to the extracellular vesicle-associated protein biomarkers selectively. In some aspects, the binding agents are configured to selectively bind with a plurality of extracellular vesicle-associated protein biomarkers consisting of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF, and optionally STX4 and optionally FOLR1.
In some aspects, an assay system can include a biochip functionalized for antibody conjugation and at least one composition having a panel of antibody binding agents that bind with the biomarkers.
In some embodiments, a method for treating a female human for ovarian cancer is provided. The method can include a step a) for obtaining extracellular vesicle-associated proteins from a biological sample from the female human. Step b) includes providing a panel of binding agents to the extracellular vesicle-associated proteins. The binding agents are configured to bind with extracellular vesicle-associated proteins of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF, and optionally STX4 and/or optionally FOLR1. Step c) includes assaying for binding a plurality of the binding agents of the panel with the plurality of extracellular vesicle-associated proteins. Step d) includes detecting binding of the plurality of binding agents of the panel with the plurality of extracellular vesicle-associated proteins, where the detected plurality of extracellular vesicle-associated proteins are the extracellular vesicle-associated protein biomarkers. Step e) includes preparing a report on the detection of binding of the binding agents to the extracellular vesicle-associated proteins of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF, and optionally STX4, wherein the report has an identification of the ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF and optionally STX4 as biomarkers of ovarian cancer. Step 0 includes providing the subject with a treatment for ovarian cancer, wherein the subject undergoes the treatment for ovarian cancer.
The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by referencing the drawings and the following detailed description.
The foregoing and following information as well as other features of this disclosure, will become more fully apparent from the following description and appended claims, taken in conjunction with the accompanying drawings. Understanding that these drawings depict only several embodiments in accordance with the disclosure and are, therefore, not to be considered limiting of its scope, the disclosure will be described with additional specificity and detail through the use of the accompanying drawings.
The elements and components in the figures can be arranged in accordance with at least one of the embodiments described herein, and which arrangement may be modified in accordance with the disclosure provided herein by one of ordinary skill in the art.
FIGS. 6A1-6A5 are a heatmap of the relative expression levels of the 7 exo-protein biomarkers in 70 cancer samples (10 ovarian cancer and 60 non-ovarian cancers) and 20 healthy controls.
The elements and components in the figures can be arranged in accordance with at least one of the embodiments described herein, and which arrangement may be modified in accordance with the disclosure provided herein by one of ordinary skill in the art.
In the following detailed description, reference is made to the accompanying drawings, which form a part hereof. In the drawings, similar symbols typically identify similar components unless context dictates otherwise. The illustrative embodiments described in the detailed description, drawings, and claims are not meant to be limiting. Other embodiments may be utilized, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein. It will be readily understood that the aspects of the present disclosure, as generally described herein, and illustrated in the figures, can be arranged, substituted, combined, separated, and designed in a wide variety of different configurations, all of which are explicitly contemplated herein.
Generally, the present technology relates to biomarkers for use in early ovarian cancer detection, where the biomarkers can include a panel of extracellular vesicle-associated proteomic biomarkers. The biomarkers can be liquid biopsy biomarkers that are obtained by a liquid biopsy, such as blood. The biomarkers (EV-based or exo-proteins) described herein can be measured for their presence or amount known measurement techniques. The biomarkers can be measured by measuring the presence or amount of the exo-protein biomarker form.
In some embodiments, the biomarker can be a protein cargo that is carried by EVs. The EVs can be considered to be a family including exosomes, small EVs, shedding microvesicles, ectosomes, apoptotic bodies, autophagic EVs, and nanoparticles. All these types of EVs contain various biological molecules. Exosomes and secreted microvesicles carry proteins, lipids, and nucleic acids. The biomarkers of the present invention can be obtained from any of these EVs.
These different types of EVs can shuttle nucleic acids, lipids, and proteins from their cell of origin to surrounding cells to regulate the function of other cells. EVs are classified according to size (from a few nanometers to a few micrometers) and sub-cellular origin. A subtype of EVs, commonly termed exosomes, are endocytic in origin and include 60-80 nm small exosomes (Exo-S) and 90-120 nm large exosomes (Exo-L). In general, the term “exosomes” is broadly used to refer to a heterogenous mixture of small EVs (sEVs) that are less than 200 nm in size; this is because widely used purification methods (such as differential ultracentrifugation) cannot definitively isolate EV class based on sub-cellular origin.
In some embodiments, exo-proteins can be used as biomarkers to detect ovarian cancers, including high grade serious ovarian carcinomas (HGSOCs). The present exo-protein biomarkers for ovarian cancer detection can be used to screen the blood and other bodily fluids of women to determine whether or not the woman is has the earliest stages of disease, even before the manifestation of symptoms. The biomarkers can be detected in a window for those at increased risk for developing ovarian cancer before the onset of the adenocarcinoma phase. The biological sample can be taken as early as possible and processed for the presence of the biomarkers.
In some embodiments, once the biomarkers are detected, the detection and likely outcomes, with or without treatments, can be provided to the subject patient, such as in the form of a report. Treatments to obtain some of the likely outcomes can be identified, and the protocol of the treatment can be provided to the subject (e.g., in the report). Then, subject patient can then determine the desired outcome and whether or not a particular treatment. In one aspect, a treatment can include surgery to specifically remove the fallopian tubes while maintaining the ovaries (and prevent early menopause) can achieve the desired outcome. In one aspect, the treatment can then be performed on the subject to obtain the desired outcome, which can be removal of the ovarian cancer, and possibly other tissues associated with the ovarian cancer, such as the fallopian tubes.
In some embodiments, the biomarkers can be protein biomarkers positioned on the surface of EVs, which are shared between EVs released by fallopian tube (FT) and HGSOC cells. This is important since the discovery represents lineage associated biomarkers, i.e., present in the progenitor cells of HGSOC which are the fallopian tube epithelium. The exo-protein biomarkers described herein have been identified via a comprehensive proteomic analysis of EVs derived from FT and HGSOC cells (both from human tissue samples and established cell lines). These biomarkers have been clinically validated to show that the transmembrane proteins—ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF, and optionally STX4—are presented on the surface of EVs from human blood samples. These biomarkers can be used in a panel that can diagnose ovarian cancer in women with high sensitivity and specificity. This allows women to be detected earlier so that the choice of therapy has a higher likelihood of achieving the desired outcome, which is to be cancer free.
ACSL4 (e.g., Acyl-CoA Synthetase Long Chain Family Member 4) is a protein encoded by the ACSL4 coding gene. Other diseases associated with ACSL4 include intellectual developmental disorder, X-Linked 63, Stroke, and Ischemia. Among its related pathways are fatty acid metabolism and integration of energy metabolism. The ACSL4 protein is an isozyme of the long-chain fatty-acid-coenzyme A ligase family.
Immunoglobulin superfamily member 8 (IGSF8) is a protein that in humans is encoded by the IGSF8 gene. This protein is known to interact with CD81/CD9 complex.
Integrin alpha-2 (ITGA2 or CD49b (cluster of differentiation 49b)) is a protein that in humans is encoded by the CD49b gene. The CD49b protein is an integrin alpha subunit. It makes up half of the a2(31 integrin duplex. Integrins are heterodimeric integral membrane glycoproteins composed of a distinct alpha chain and a common beta chain. They are found on a wide variety of cell types including T cells (the NKT cells), NK cells, fibroblasts and platelets. Integrins are involved in cell adhesion and also participate in cell-surface-mediate signaling. Expression of CD49b in conjunction with LAG-3 has been used to identify type 1 regulatory (Tr1) cells. The DX5 monoclonal antibody recognizes mouse CD49b.
Integrin alpha-5 (ITGA5) is a protein that in humans is encoded by the ITGA5 gene. The ITGAG protein product of this gene belongs to the integrin alpha chain family. Integrins are heterodimeric integral membrane proteins composed of alpha and beta chains. This gene encodes the integrin alpha 5 chain. Alpha chain 5 undergoes post-translational cleavage in the extracellular domain to yield disulfide-linked light and heavy chains that join with beta 1 to form a fibronectin receptor. In addition to adhesion, integrins are known to participate in cell-surface mediated signalling.
Integrin beta-3 (β3) (ITGB3 or CD61) is a protein that in humans is encoded by the ITGB3 gene. The ITGB3 protein product is the integrin beta chain beta 3. Integrins are integral cell-surface proteins composed of alpha and beta chains. A given chain may combine with multiple partners, resulting in different integrins. Integrin beta 3 is found along with the alpha IIb chain in platelets. Integrins are known to participate in cell adhesion as well as cell-surface-mediated signaling.
Myoferlin (MYOF) is a protein that in humans is encoded by the MYOF gene. The protein encoded by this gene is a type II membrane protein structurally similar to dysferlin. Mutations in dysferlin, a protein associated with the plasma membrane, can cause muscle weakness that affects both proximal and distal muscles. It is a ferlin family member and associates with plasma and nuclear membranes.
Syntaxin-4 (STX4) is a protein that in humans is encoded by the STX4 gene.
Folate receptor 1 (Folate receptor alpha, FOLR1) is a protein that in humans is encoded by the FOLR1 gene. The protein encoded by this gene is a member of the folate receptor (FOLR) family. Members of this family have a high affinity for folic acid and for several reduced folic acid derivatives, and mediate delivery of 5-methyltetrahydrofolate to the interior of cells.
In some embodiments, the present invention can include measuring and determining an amount of the biomarkers by using reverse-transcription polymerase chain reaction (RT-PCR) or reverse-transcription quantitative polymerase chain reaction (RT-qPCR) to determine the presence or amount of the combination of biomarkers.
Reverse transcription polymerase chain reaction (RT-PCR) combines reverse transcription of RNA into DNA (in this context called complementary DNA or cDNA) and amplification of specific DNA targets using polymerase chain reaction (PCR). It is primarily used to measure the amount of a specific RNA, such as mRNA of the biomarkers. This is achieved by monitoring the amplification reaction using fluorescence, a technique called real-time PCR or quantitative PCR (qPCR). Combined RT-PCR and qPCR (RT-qPCR) are used to analyze gene expression and quantify biomarker mRNA for use as described herein. Accordingly, in some aspects, the biomarker can be the mRNA of each identified exo-protein biomarker.
In some embodiments, the present invention can include measuring the biomarkers by proximity ligation. A proximity ligation assay combines antibody-oligo conjugates, enzymatic ligation, and PCR amplification into a sensitive method for quantitative protein detection from small volumes. Proximity ligation extends the capabilities of traditional immunoassays to include direct detection of proteins, protein interactions, extracellular vesicles, and post translational modifications with high specificity and sensitivity. Protein targets, such as the biomarkers, can be readily detected and localized with single molecule resolution and objectively quantified in unmodified cells and tissues. Utilizing only a few cells, sub-cellular events, even transient or weak interactions, are revealed in situ, and subpopulations of cells can be differentiated. Within hours, results from conventional co-immunoprecipitation and co-localization techniques can be confirmed.
In some embodiments, the biomarkers can be used to detect the cancer cells while confined to or fallopian tube or at any stage of cancer progression. It can be beneficial for the biomarkers to be detected at earlier stages when treatments are much more effective. The early detection can be performed from a sample, such as from a liquid sample (e.g., mucus, secretion, blood, etc.) from the vagina or the subject's blood. The sample can be taken at any time and at any age of the female. The sample can be taken before any cancer cells are disseminated from the fallopian tube and spread to the ovary and/or peroneal cavity. Thus, the biomarkers can be used in a non-invasive blood tests or other liquid biopsies for pre-symptomatic screening and early detection of cancer, such as ovarian cancer or cancer of fallopian tube origin.
The biomarkers can be used for the early detection of serous tubal intraepithelial carcinoma (STIC) lesions confined to the fallopian tubes (the earliest stage of disease) and before the tumor cells disseminate into a woman's peritoneal cavity. The biomarkers can also be used to monitor ovarian cancer disease progression, given that they can detect advanced disease with 100% sensitivity and specificity. The biomarkers can be used for detection of minimal residual ovarian cancer calls even after completion of therapies, resulting in clinical “no evidence of disease’ (NED). Thus, these biomarkers provide a robust panel that can be used to screen for ovarian cancer in various stages of progression and treatment.
In some embodiments, the biomarkers can be validated to ensure that they can be used to screen blood samples from asymptomatic women. The biomarkers can be validated by using positive and negative controls. The positive controls may be samples and/or biomarker data and/or biomarker amounts of women who are at an increased risk of developing ovarian cancer due to inherited mutations in BRCA1 or BRCA2 as well as other ovarian cancer related susceptibility genes. Negative controls can be overtly healthy women at an average lifetime risk of ovarian cancer and/or who omit inherited mutations in BRCA1 or BRCA2 or other ovarian cancer related susceptibility genes.
In some embodiments, the biomarkers can be used to screen for ovarian cancer due to the high specificity and sensitivity of these novel biomarkers for ovarian cancer cells. The present method of detection with this set of protein biomarkers can be adapted to a high throughput system, wherein antibodies targeted against these proteins can be applied on microfluidic devices for direct EV capture and/or as secondary probes to assess the relative level of these markers on circulating EVs. Any possible way of measuring the amount of these exo-protein biomarkers can be employed in the present invention.
In some embodiments, the present invention includes a control panel of the biological markers. The control panel includes at least one composition that includes the biomarkers. For example, a synthetic sample can include a defined amount/concentration of each biomarker in the panel, whether protein or mRNA. In another example, each panel biomarker can be in a synthetic sample at a defined amount/concentration. In another example, a plurality of synthetic samples can include the biomarkers in a gradient of the amount/concentration, whether alone or in biomarker combinations. The synthetic samples can be used in the protocols herein as positive controls, where measurements can be done via multiple types of platforms and methodologies. Accordingly, the synthetic samples can be used for positive controls of the biomarkers associated with ovarian cancer disease that has developed in the fallopian tube. In some aspects, the synthetic samples can include the extracellular vesicle associated with the biomarker proteins.
In some embodiments, EVs for liquid-based testing can be purified from a biological sample, such as blood, plasma, vaginal fluid, fallopian tissue or secretion, or other bodily fluids. The purification can be done by size-exclusion chromatography and immunoaffinity capture. The extracellular vesicle-associated biomarkers co-localized on the EV surface can be detected by any means, such as with binding agents or proximity ligation qPCR. For example, antibody combinations comprising one capture antibody and two oligonucleotide-tagged detection antibodies can be used recognize a plurality of unique biomarkers.
EVs can be isolated in some embodiments using size-exclusion chromatography and immunoaffinity capture. The biomarkers co-localized on individual EVs' surface can be detected with proximity ligation qPCR. Using this approach, antibody combinations recognizing a plurality of biomarkers are employed. Each combination for each biomarker consists of one capture antibody and two oligonucleotide-tagged detection antibodies.
In some embodiments, plasma samples from women with early stage I/II high-grade serous ovarian carcinoma can be tested, and the data thereof can be used as positive controls to determine the absolute sensitivity and specificity of these exo-protein biomarkers for earlier forms of the disease. Samples from healthy women without cancer can be used as negative controls.
In some embodiments, the protocols described herein may be applied to other extracellular proteins, such as those from serum.
In some embodiments, a method is provided for detection of a panel of EV-associated protein biomarkers in a female human. The method can include a step of obtaining EV-associated proteins from a biological sample from the female human. Also, a panel of binding agents are provided, which binding agents bind to biomarkers of a biomarker panel that is associated with ovarian cancer. The binding agents are then provided to the obtained EV-associated proteins. The binding agents are configured to bind with the individual EV-associated proteins ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, FOLR1 and/or STX4. The binding of the plurality of the binding agents with the panel with the plurality of EV-associated proteins can be assayed for so that the binding of the plurality of binding agents with the panel of biomarkers detected. This detection of binding of the binding agents with the biomarkers can show that the biomarkers are present in the obtained EV-associated proteins from the subject. In some aspects, the amount of the biomarkers is determined, which can be compared to a positive control, a negative control, or a threshold standard. The detected plurality of EV-associated proteins biomarkers are the EV-associated protein biomarkers. The presence or amount of the detection of the biomarkers can then be the basis of generating a report to inform the subject of the detection of the biomarkers and the indication of ovarian cancer or cancer of origin from the fallopian tubes. The report may also include prognosis information, such as stage of cancer and possible progression steps, as well as treatments and outcomes thereof.
In some embodiments, the binding agents are selected from antibodies, antibody fragments, aptamers, or combinations thereof. Each binding agent is configured to bind with one of the protein biomarkers of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, FOLR1, and/or STX4. As such, there is a binding agent for each biomarker. However, the type of binding agent can vary for each biomarker. For example, one biomarker may have an antibody binding agent, but another biomarker can have an aptamer binding agent. Thus, a collection of binging agents can include various binding agent types so long as each binging agent binds one of the biomarkers. In some aspects, the binding agents are antibodies or antibody fragments.
In some embodiments, the panel of binding agents are selective for at least six of the plurality of EV-associated proteins. In some aspects, the panel of binding agents are selective for at least ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF, and optionally FOLR1. In some aspects, the panel of binding agents are selective for at least ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, and STX4, and optionally, FOLR1. In some aspects, the panel of binding agents are selective for at least ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, FOLR1, and STX4. In some aspects, the panel of binding agents are selective for at least ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, FOLR1, and optionally STX4.
The methods described herein can include use of tools and protocols for obtaining EVs from the biological sample. The tools and protocols can be configured for measuring the EV-associated proteins from the intact or lysed extracellular vesicles. The methods can include obtaining a biological tissue sample from the female human. The EV-associated proteins can be linked with serous tubal intraepithelial carcinoma (STIC). Any tool or method can be used for obtaining a biological fluid sample from the female human, wherein the biological sample is blood, plasma, urine, and/or a fluid from a vagina of the female human subject.
In some embodiments, the methods can include assaying for binding of a binding agent to the respective biomarker. Such assaying can include a protein binding assay where each binding agent binds with a respective EV-associated protein biomarker from the plurality of EV-associated proteins that are defined as biomarkers for ovarian cancer. The protein binding assay can be configured as an antibody screening assay, wherein each antibody is a binding agent for a respective EV-associated protein biomarker. In some aspects, the antibody screening assay is a simple Western assay. In some aspects, the antibody screening assay can be performed on an assay device that includes a biochip or microfluidic chip configured for receiving the binding agents. However, any type of device and any type of protocol that can be used to detect binding between the binding agents and the biomarkers can be used. For example, the chip can be an ExoProfile chip.
The methods include obtaining EVs from the biological sample, and separating the extracellular vesicle-associated proteins from the extracellular vesicles. The biological sample can be any biological fluid, such as saliva or blood, which can be obtained by any method. The separation can be by any separation technique that can separate the EVs from the biological sample.
In some embodiments, the method of assaying for the biomarkers can include quantifying levels of the EV-associated protein biomarkers by using a reporter. For example, the methods can be performed using fluorescence as a reporter. That is, the fluorescence can be used as a visual indicator of binding between the biomarkers and the binding agents. Various types of fluorescent agents and protocols can be used to track the binding by fluorescence. In some aspects, binding agents (e.g., antibodies) conjugated to biotin are used as a fluorescent reporter, and observing fluorescence of a EV can show the presence of the biomarkers. In some aspects, the assaying is an immunocapture and fluorescent detection assay.
In some embodiments, the biomarker is determined to be present at an elevated level that is greater than a negative control or a threshold. The negative control can be a biomarker panel of no ovarian cancer, or the negative control can be the expression level of the defined biomarkers in one or more non-ovarian cancer patients or an average or mean value thereof, which can be used as a threshold. The levels of the biomarkers are higher than negative controls in subjects that have or are susceptible to ovarian cancer, or at some point of progression of the ovarian cancer.
Also, positive controls can be used, which are biomarker levels in one or more ovarian cancer patients or average or mean thereof. The test values can be compared to the positive control values for correlation of the biomarkers so that the biomarker levels that are similar or about the same as the positive controls are likely to show that the subject has ovarian cancer or some stage of progression thereof.
In some embodiments, the methods can include creating a proteomic profile of EV-associated proteins in the subject, in a negative control, and a positive control. The proteomic profile can include the EV-associated protein biomarkers for the female human that are defined herein as well as others. The profiles can be used for comparison with obtained values to determine if the biomarker is showing as being overexpressed in the subject. This allows for when all the biomarkers being overexpressed the female subject being identified as susceptible or having some stage of progression of ovarian cancer.
In some embodiments, the female human can be selected at random or based on some criteria of related to ovarian cancer. In some aspects, the female human is suspected of having ovarian cancer or is positive for BRCA1 mutation or BRCA2 mutation or other cancer susceptibility genes contributing to an increase lifetime risk of developing this disease. In some aspects, the female is over a certain age, such as over 40, 45, 50, 55, 60, 65, 70, or 75. In some aspects, the female human is in a risk group for developing ovarian cancer. In some aspects, the female human is devoid of symptoms of ovarian cancer.
In some embodiments, a panel of binding agents for EV-associated protein biomarkers of ovarian cancer is provided. In one example, the panel includes binding agents to the EV-associated protein biomarkers, wherein the binding agents are configured to bind with a plurality to biomarkers selected from ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, FOLR1, and/or STX4. In one example, the panel includes binding agents to the EV-associated protein biomarkers, wherein the binding agents are configured to bind with a plurality of biomarkers selected from ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, FOLR1, and MYOF. The binding agents can be complementary nucleic acids that bind with mRNA of these biomarkers. In one example, the panel includes binding agents to the EV-associated protein biomarkers, wherein the binding agents are configured to bind with a plurality to biomarkers selected from ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, FOLR1, and STX4.
In some embodiments, an assay system is provided. The assay system can include a biochip functionalized for capturing a binding agent that binds with one of the biomarkers. For example, the binding agent can be an antibody, and the biochip is functionalized for antibody conjugation. The system can also include at least one composition having a plurality of binding agents that are configured to bind with a plurality of extracellular protein biomarkers are selected from ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, FOLR1, and/or STX4. In some aspects, the biochip includes an anti-CD81 antibody or related tetraspanins, including CD9 and CD63. In some aspects, the plurality of extracellular protein biomarkers are selected from ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF. In some aspects, the plurality of extracellular protein biomarkers are selected from ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, FOLR1, and MYOF. In some aspects, the plurality of extracellular protein biomarkers are selected from ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, FOLR1, MYOF, and STX4.
In some embodiments, an assay system can include a PCR or qPCR machine and the required compositions for performing RT-PCR or RT-qPCR.
In some embodiments, the methods can include proteomic analyses by mass spectrometry of EVs.
In some embodiments, the biomarkers exhibit high area under the curve (AUC) values ranging from about 0.85 to about 0.98 as calculated using receiver operating characteristic (ROC) analysis. The AUC range of about 0.85 to about 0.98 can be used as a positive control value, where patient samples in this range likely have ovarian cancer. The biomarkers can have a biomarker AUC threshold of at least 0.85, where an AUC of at least 0.85 indicates the biomarker is present and can indicate cancer. When each panel of the combination of biomarkers has an AUC value greater than the AUC threshold value of there is evidence that the subject has an onset of cancer, such as ovarian cancer or cancer of fallopian tube origin. When multi-marker analysis was performed, the combination of IGSF8 and ITGA5 yielded most significant degree of sensitivity and specificity in this cohort. In some aspects, the threshold can be 0.7 or 0.75 for the AUC, and an AUC above the threshold for the biomarker indicates the presence of the biomarker that indicates the ovarian cancer.
The comparison of the AUC of a female subject with the positive control AUC can provide information about whether or not the female subject, when lower than the positive control the female is likely does not have ovarian cancer, but when about the same value as the positive control the female is likely to have ovarian cancer.
The AUC for a negative control non-ovarian cancer patient is about 0.4-0.6 (0.5 is a random classifier as compared to 1.0 which is a biomarker with perfect performance). The comparison of the AUC of a female subject with the negative control AUC can provide information about whether or not the female subject, when higher than the negative control the female is likely to have ovarian cancer, but when about the same value as the negative control the female is unlikely to have ovarian cancer.
Once the biomarkers have been identified, quantified, and/or compared to controls or standards, the report identifying whether or not the subject has cancer can be prepared. The report can be prepared as any standard report as a paper or electronic file. The report can have information or other indicia that identifies the subject and the presence or absence of cancer. The report can be prepared by typing or writing on paper, or by inputting and word processing on a computing system. As a result, the report provides the information about the subject and cancer and may include information about the biomarkers and their relationship to cancer. In some aspects, the AUCs of the biomarkers of the subject can be provided, which can be shown by comparison to AUC values for the positive controls, negative controls, or threshold values. The report is prepared by an action that takes the information of the determination of the presence of the biomarkers and/or the indication of a potential ovarian cancer and puts the information of the determination into indicia (e.g., text, charts, tables, graphs, images, etc.) that can be read by a human visually or by a computer electronically.
In some embodiments, the report includes one or more of: an identification of the ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF and optionally STX4 and/or FOLR1 as biomarkers of cancer of ovaries or fallopian tube origin; a measurement data that indicates the presence or increased amount of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF and optionally STX4 and/or FOLR1; a measurement data of positive or negative control for ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF and optionally STX4 and/or FOLR1, or a threshold thereof; a statement of possible outcomes of cancer of ovaries or fallopian tube origin; a statement of treatments for the identified cancer, wherein the treatments are selected from chemotherapy, radiation therapy, surgical removal of the cancer cells or tumor, or combinations thereof; a statement of possible outcomes of treatments for the identified cancer; or a listing of medical entities that perform, oversee, or control the treatments for the identified cancer.
In some embodiments, a method for treating a female human for ovarian cancer is provided. The method can include determining the presence of the combination of biomarkers described herein in the subject, preparing a report that the female human has cancer, and then treating the cancer. The determination of the presence of the biomarkers can be by any method, such as follows. Once the biomarkers that indicate cancer are detected, such as having a AUC over the threshold value or over the negative control value or about the positive control value, the report is prepared. The method can include preparing a report on the detection of binding of the binding agents to the extracellular vesicle-associated proteins of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF and optionally STX4, and optionally FOLR1. The report has an identification of the ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF and optionally STX4 and optionally FOLR1 as biomarkers of ovarian cancer. The method includes providing the subject to get a treatment for the ovarian cancer, wherein the subject undergoes the treatment, e.g., surveillance or surgery for early stage ovarian cancer.
In some embodiments, the biomarkers described herein can be used for monitoring the patient during the performance of the treatment for ovarian cancer (e.g., measure minimal residual disease after completion of treatment which is an essential measure of early recurrence and subsequent death). That is, the subject can be treated for cancer, and the biomarkers can be measured. An indication that the subject still has cancer can cause further treatments for cancer therapy to be provided to the subject. An indication that the subject is free of cancer can terminate any ongoing cancer therapy treatment and then monitor the patient. The treatments for ovarian cancer can be selected from chemotherapy, radiation therapy, surgical removal of the fallopian tubes (if the cancer is detected while confined) or the ovarian cancer (if tumor cells have spread to the ovaries and peritoneum), or combinations thereof. In some aspects, the method includes the subject undergoing the treatment of ovarian cancer. In some aspects, the subject can be provided a statement of possible outcomes of treatments for ovarian cancer, or provided a listing of medical entities that perform, oversee, or control the treatments for ovarian cancer.
In some embodiments, the subject is selected by selecting the female human by at least one of: to be suspected of having ovarian cancer or is positive for BRCA1, BRCA2 mutation or other cancer susceptibility genes; is in a risk group for developing ovarian cancer; or is devoid of symptoms of ovarian cancer. Any of these types of subjects can be identified as a subject of the present invention.
In some embodiments, after the subject undergoes the treatment for ovarian cancer, the method can include performing another biomarker detection assay (e.g., measuring CA-125 concentration in serum), and preparing a second report on the detection of binding of the binding agents to the extracellular vesicle-associated proteins of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF and optionally STX4 and/or FOLR1. This new report can be to the subject or to a medical entity or medical practitioner. The method can include performing a subsequent treatment if the second report provides an indication of ovarian cancer in the subject based on the extracellular vesicle-associated proteins of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, and MYOF and optionally STX4 and/or FOLR1.
Enrichment and characterization of EVs derived from patient HGSOC and healthy fallopian tube tissue explants and cell lines was performed. 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). For these studies, the 24 h time point was used for tissue media collection since the number of total particles decreased by at least 55% within 48 h. This observation may 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 to enrich for the EVs.27 Representative EVs purified from either cell lines or tissue explants were characterized by nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), single particle interferometric reflectance imaging sensing (SP-IRIS) and fluorescence following the Minimum Information for Studies of Extracellular Vesicles 2018 guidelines (
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.
Identification of FT and HGSOC core proteome biomarkers was performed. After EV characterization, we performed proteomic profiling and an analysis pipeline to establish the EV proteome of FT and HGSOC (for both tissue and cell lines) via liquid chromatography tandem mass spectrometry (LC-MS/MS), 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.
Approximately 2,200 to 3,200 exo-proteins were identified in each sample (
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, the data was filtered furthered by comparing the EV proteins from tissue explants with their respective cell lines (e.g., HGSOC or FT) to increase the specificity of the EV proteins to their site of origin (
The ROC analysis is useful for identifying differences between FT and HGSOC samples. However, this study can identify 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 microfluidic ExoProfile chip. For this analysis, the 985 FT/HGSOC core proteome with known or predicted transmembrane proteins curated in the protein sequence database of UniProtKB (Swiss-Prot, July 2021), which resulted in a truncated list of 75 exo-proteins (
Capillary western blotting (Simple Western—using the Wes platform) was performed on the 45 transmembrane proteins using one antibody per protein to confirm their presence within cell line derived EVs to support the LC-MS/MS data. Among the proteins analyzed using Wes, ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF and STX4 were consistently detected in all the tested FT and HGSOC cell line EVs (
The expression of these proteins was measured via immunohistochemistry (IHC) to confirm 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. Following staining, a pathologist reviewed and scored each core (
After confirming that these transmembrane proteins are present in tissues via IHC, the exo-proteins in patient plasma samples were tested using a modified ExoProfile microfluidic chip capable of EV immunocapture and fluorescence detection32. To further improve the capacity of this device for molecular profiling of circulating EVs, a platform can integrate an ultrasensitive gold nanorod (AuNR) plasmonic fluor-linked immunosorbent assay (P-FLISA) with the ExoProfile chip. In contrast to conventional ELISA that uses reporter enzymes for signal amplification, which limits the multiplicity, our assay uses gold nanorods coated with fluorophore molecules as the ultrabright fluorescent tag for the sandwich immunoassay. Due to the localized surface plasmon resonance of AuNRs, fluorescence signal can be enhanced by more than 1000-fold with immensely improved stability. Furthermore, this new platform enables sensitive capture and detection of EVs without the additional steps needed for in-solution enzymatic reaction and thus greatly simplifies the assay workflow and expedites the chip operation and analysis speed.
The biomarker exo-FOLR1 was able to differentiate ovarian patients (late and early stage) from benign and healthy controls with high specificity and sensitivity32,48. Therefore, FOLR1 was used as the positive control to assess the specificity and sensitivity of the current lineage specific biomarkers being evaluated. Using the ExoProfile chip specifically developed to simultaneously measure multiple EV-associated analytes, the protocol captured CD81+ EVs from plasma (n=10 cases and n=20 age/race matched controls) and quantified the relative levels of ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, and FOLR1 (
When the protein biomarkers are used with the functionalized ExoProfile chip, the protocol can distinguish the HGSOC patients (both early and late stage equally) from matched healthy individuals with high AUC values. Furthermore, when combined IGSF8 and ITGA5 the protocol achieved a sensitivity of 0.80 at 99.8% specificity. These results exceed the performance of clinically adopted serum multimarker panels, i.e., CA-125 (gold standard) and HE461,62. Although this study was performed on a small set of cases and control, future studies will need to validate the sensitivity and specificity 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.
De-identified plasma samples from healthy and untreated HGSOC patients with early (FIGO Stage I-II) or advanced stage (FIGO Stage III-IV) disease were obtained from the University of Kansas Medical Center Biospecimen Repository Core Facility (KUMC BRCF).
Primary HGSOCs tumors or metastatic tissue 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-fixed paraffin-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-identified 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 humidified incubator at 37° C. with 5% CO2 for 24 h. The conditioned media was collected and EVs were enriched from the media using differential ultracentrifugation as described below.
FT cell lines, FT240, FT246 and FT28263 were a kind gift from Dr. Ronny Drapkin (University of Pennsylvania). All cell lines were validated by short tandem repeat fingerprinting. FT cell lines were cultured in a 50/50 mixture of DMEM/F-12 without L-glutamine (Corning) supplemented with 2% (v/v) Ultroser G (Pall Biosciences) and 1% (v/v) penicillin-streptomycin at 37° C. with 5% CO2. Ultroser G was ultracentrifuged for a minimum of 18 h at 100,000×g followed by filtration through a 0.2 μm filter. 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×g at 4° C. for at least 18 h and filtered using a μm filter), 2.5% mg/mL insulin and 100 units/mL penicillin-streptomycin at 37° C. with 5% CO2. Conditioned media was collected when cells were at least 60% confluent. 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×g for 10 min to remove cell debris. The supernatant fraction was then centrifuged at 2,000×g for 20 min to remove apoptotic bodies. This was followed with supernatant centrifugation at 10,000×g to remove large microvesicles for 1 h followed by 100,000×g spin to collect EVs. The EV pellets were washed and resuspended in PBS and spun for 1 h at 100,000×g. The EV pellets were resuspended in PBS and stored at −80° C.
Glow-discharged carbon-coated copper grids were floated 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.
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 filtered 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.
Enriched EV samples (17.5 μL each) were mixed with an equal volume of Solution A. The sample was then placed 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 an 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 fluorescence for the red, green, and blue channels in all experiments.
Enriched EV samples were submitted to the Proteomics and Mass Spectrometry Facility at the Donald Danforth Plant Science Center (St. Louis, MO) for LC-MS/MS analysis. Twenty micrograms of EVs per sample were denatured using 8 M urea, reduced with 10 mM TCEP, and alkylated with 25 mM iodoacetamide followed by digestion with trypsin/Lys-C mix at 37° C. overnight. The digested sample was acidified with 1% TFA and then cleaned up using a Pierce C18 tip (Thermo Fisher Scientific). The extracted peptides were dried down and each sample was resuspended in 30 μL 1% acetonitrile/1% formic acid. Approximately 1 μg of each sample was injected for LC-MS/MS analysis.
LC-MS/MS was carried out on an Orbitrap Fusion Lumos (Thermo Fisher Scientific) mass spectrometer coupled with a U3000 RSLCnano HPLC (Thermo Fisher Scientific). The peptide separation was carried out on a C18 column (Acclaim PepMap RSLC, 50 cm×75 μm nanoViper™, C18, 2 μm, 100 Å, Thermo Fisher Scientific) at a flow rate of 0.3 μL/min and the following gradient: Time=0-4 min, 2% B isocratic; 4-8 min, 2-10% B; 8-83 min, 10-25% B; 83-97 min, 25-50% B; 97-105 min, 50-98%. Mobile phase A consisted of 0.1% formic acid and mobile phase B consisted of 0.1% formic acid in acetonitrile. The instrument was operated in the data-dependent acquisition mode in which each MS1 scan was followed by higher-energy collisional dissociation (HCD) of as many precursor ions in a 2-second cycle (Top Speed method). The mass range for the MS1 done using the FTMS was 365 to 1800 m/z with resolving power set to 60,000 @ 400 m/z and the automatic gain control (AGC) target set to 1,000,000 ions with a maximum fill time of 100 ms. The selected precursors were fragmented in the ion trap using an isolation window of 1.5 m/z, an AGC target value of 10,000 ions, a maximum fill time of 100 ms, a normalized collision energy of 35 and activation time of 30 ms. Dynamic exclusion was performed with a repeat count of 1, exclusion duration of 30 s, and a minimum MS ion count for triggering MS/MS set to 5000 counts.
Sequence mapping and label-free quantification were done using Proteome
Discoverer (PD) version 2.4 (Thermo Fisher Scientific). Database searches with Sequest search engine were launched in PD and queried against Human reference proteome (Uniprot.org, April 2021). The digestion enzyme was set as trypsin. The MS/MS spectra were searched with a precursor mass tolerance of 10 ppm and a fragment ion mass tolerance of 0.6 Da. Carbamidomethylation of cysteine was set as a fixed modification. Oxidation of methionine and acetylation of the N-terminal of protein were specified as variable modifications. Matched peptides were filtered using a Percolator-based 1% false discovery rate (FDR). Protein quantification was achieved by using the total intensities of all precursors.
The concentration of EV proteins was established using the Bradford assay (Bio-Rad) according to the 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. 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. The chemiluminescent detection profile 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).
Unstained tissue slide sections of five 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 minutes. Once at room temperature, endogenous peroxidase activity was blocked using a 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. Primary antibody incubation using ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF, STX4 and FOLR1 was performed overnight. Anti-mouse, anti-rabbit, or anti-goat secondary ImmPRESS horse IgG polymer reagent (Vector Laboratories) was added and incubated for 30 min. The ImmPACT DAB EqV reagent was then incubated for 1-5 min. A light hematoxylin counterstain was performed followed by dehydration, clearing, and mounting using a permanent mounting medium (Vector Laboratories). These stained slides were then visualized under a bright field microscope and scored by a board-certified pathologist using the following formula: H-score=(0×area of cells with absent staining)+(1×area of “1+” cells %)+(2×area “2+” cells %)+(3×area “3+” cells %)64.
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.
The ExoProfile chip was functionalized for antibody conjugation and an anti-CD81 antibody was flowed through the chip to coat the surface similar to previous methods32. De-identified plasma samples, first processed to remove platelets (2,500×g for 15 min), were centrifuged at 10,000×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 exo-protein biomarkers (ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, FOLR1 and MYOF) simultaneously. One channel was designated as the negative control (PBS) to measure any background fluorescence. 10 μL of diluted plasma flowed through the chip with a constant flow rate of 5 μL/h. The chip was washed with Superblock buffer and primary detection antibodies against the target exo-proteins were added using the optimized concentrations. Biotin-conjugated secondary antibodies (donkey anti-goat IgG or donkey anti-rabbit IgG) were flowed through followed by the plasmonic fluorophores to serve as the fluorescence reporter65,66. Fluorescence images were captured using a Nikon Ti2 inverted fluorescence microscope equipped with a LED excitation light source (Lumencor). Fluorescence intensity was quantified by processing and analyzing the images using ImageJ.
Qualitative analysis (GO identification 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 analysis67. The log2 fold change values and the adjusted p-values were used to define significant differential expression proteins. Qprot68 v1.3.5 was used to calculate Z-statistics, log2 (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 curve42. The length of the ROC curve for each protein was estimated non-parametrically using a Gaussian kernel density estimator for the scores of each group (FT and HGSOC), so that a smooth ROC curve estimate is available. Monotone markers are proteins which have an ROC curve length of 2 and exhibit AUC>0.8 and AUC<0.2, while non-monotone markers are proteins that have an ROC curve length of >1.6 and exhibit AUC≥0.35 but ≤0.65.
For NTA data and IHC expression score analysis, GraphPad Prism version 8 was used for performing Mann-Whitney U tests in calculating p-values to compare between the samples. Data were expressed as means±s.e.m. (standard error of the mean). For the ExoProfile chip, one-way ANOVA was performed on the fluorescent intensities measured per each sample per biomarker. ROC/AUC for single marker analysis was performed using GraphPad Prism version 8. For combination marker analysis, we explored all possible combinations of markers which involved scrutinizing all possible models with 2 markers, with 3 markers etc., along with a model that included all markers. The Akaike Information Criterion (AIC) was used to identify the best marker combination69. The linear term of this logistic regression model is then extracted to be utilized as the combined marker score. We then maximized the Youden index70 to derive the sensitivity and specificity at the optimized cutoff.
Data has been obtained that show that lineage specific (FT/HGSOC shared) biomarkers (e.g., biomarkers identified herein) are able to discriminate ovarian cancers from other type of cancers. This shows that the biomarkers are selective for ovarian cancers, or cancer of fallopian tube origin. The data shows that the biomarkers have the ability to discriminate ovarian cancer from 12 different types of other common types of cancers, such as leukemia, breast—invasive and DCIS, cervical, renal, colon, endometrial, brain, lung, lymphoma, pancreatic, and thyroid. The differentiation can be with these other cancer calls having AUCs comparable to healthy subjects versus the identified biomarkers recited herein for ovarian cancer that have much higher AUCs. The data shows that the ovarian cancer biomarkers described herein can be successful by being specific for ovarian cancer over other cancers.
FIGS. 6A1-6A5 include heatmaps of the relative expression levels of the 7 exo-protein biomarkers in 70 cancer samples (10 ovarian cancer and 60 non-ovarian cancers) and 20 healthy controls.
A report can be prepared that identifies the treatment for the subject, and the report can be provided to the subject, or a medical professional, or a medical clinic, or a hospital or other treatment facility. Once the treatment is identified, the method can include an entity coordinating the performance of the treatment on the subject. Then, the subject can be treated as determined and reported. The report can be provided to the subject for consideration, whether in verbal or written or electronic form. The report can also include the recommendation for a treatment, and optionally treatment providers. Also, the report can include information about the outcomes of the treatments, including positive outcomes and/or negative outcomes. The patient can then be put on the waitlist, and can undergo further examinations.
To realize the above-mentioned report, a diagnosis results assessment system of the present invention includes: a diagnosis unit to perform a diagnosis of a subject to determine the presence of biomarkers, for generating diagnosis record information; a report storage unit to store a report describing a diagnosis result on the sample; a report analysis unit to analyze the diagnosis result described in the report stored in the report storage unit; and a report verification unit to compare the diagnosis result analyzed by the report analysis unit to the diagnosis record information, and determine a degree of matching on the diagnosis degree of the comparison result.
A diagnosis results assessment method of the present invention includes: a diagnosing step of performing a diagnosis of a sample to determine the presence or amount of biomarkers for generating diagnosis record information; a report storing step of storing a report describing the biomarkers and diagnosis result for the subject in a report storage unit; a report analyzing step of analyzing the diagnosis result described in the report stored in the report storage unit: and a report verifying step of comparing the diagnosis result analyzed in the report analyzing step to the diagnosis record information, and determining a degree of matching on the diagnosis degree of the comparison result.
A diagnosis results assessment device of the present invention includes: a diagnosis unit (e.g., computing system) to perform a pathological diagnosis of a sample from a subject for generating diagnosis record information; a report storage unit to store a report describing a pathological diagnosis result on the tissue specimen image: a report analysis unit to analyze the diagnosis result described in the report stored in the report storage unit; and a report verification unit to compare the diagnosis result analyzed by the report analysis unit to the diagnosis record information, and determine a degree of matching on the diagnosis degree of the comparison result.
Embodiments of the disclosure provide a computing system for generating a diagnosis report based on data from a panel of biological markers of a patient. The system includes a communication interface configured to receive the data acquired by a diagnostic data acquisition device. The system further includes at least one processor. The at least one processor is configured to detect a medical condition of the patient and parameters associated with the medical condition based on the diagnostic data. At least one processor is further configured to construct the diagnosis report based on the diagnostic data, wherein the diagnosis report includes at least information related to the biomarkers and the disease indication, and a description of the medical condition using the parameters. The system also includes a display configured to display the diagnosis report.
Embodiments of the disclosure also provide a method for generating a diagnosis report based on diagnostic data. The method includes receiving, by a communication interface, the diagnostic data that is acquired by performing the biomarker detection/quantification assay. The method further includes detecting, by at least one processor, a medical condition of the patient and parameters associated with the medical condition based on the diagnostic data. The method also includes constructing, by at least one processor, the diagnosis report based on the diagnostic data. The method additionally includes displaying the diagnosis report on a display, transmitting the report, printing the report on paper, or otherwise providing the report to the patient or medical entity.
Embodiments of the disclosure further provide a non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more processors, causes one or more processors to perform a method for generating a diagnosis report based on diagnostic data of a patient. The method includes receiving the diagnostic data acquired by the performance of the diagnostic assays. The method further includes detecting a medical condition of the patient and parameters associated with the medical condition based on the diagnostic data. The method also includes constructing the diagnosis report based on the diagnostic data. The diagnosis report includes at least one data linking the patient to the diagnosed medical condition, and a description of the medical condition using the parameters. The method additionally includes displaying the diagnosis report.
One skilled in the art will appreciate that, for this and other processes and methods disclosed herein, the functions performed in the processes and methods may be implemented in differing order. Furthermore, the outlined steps and operations are only provided as examples, and some of the steps and operations may be optional, combined into fewer steps and operations, or expanded into additional steps and operations without detracting from the essence of the disclosed embodiments.
The present disclosure is not to be limited in terms of the particular embodiments described in this application, which are intended as illustrations of various aspects. Many modifications and variations can be made without departing from its spirit and scope, as will be apparent to those skilled in the art. Functionally equivalent methods and apparatuses within the scope of the disclosure, in addition to those enumerated herein, will be apparent to those skilled in the art from the foregoing descriptions. Such modifications and variations are intended to fall within the scope of the appended claims. The present disclosure is to be limited only by the terms of the appended claims, along with the full scope of equivalents to which such claims are entitled. It is to be understood that this disclosure is not limited to particular methods, reagents, compounds, compositions or biological systems, which can, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.
With respect to the use of substantially any plural and/or singular terms herein, those having skill in the art can translate from the plural to the singular and/or from the singular to the plural as is appropriate to the context and/or application. The various singular/plural permutations may be expressly set forth herein for sake of clarity.
It will be understood by those within the art that, in general, terms used herein, and especially in the appended claims (e.g., bodies of the appended claims) are generally intended as “open” terms (e.g., the term “including” should be interpreted as “including but not limited to,” the term “having” should be interpreted as “having at least,” the term “includes” should be interpreted as “includes but is not limited to,” etc.). It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation no such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases “at least one” and “one or more” to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles “a” or “an” limits any particular claim containing such introduced claim recitation to embodiments containing only one such recitation, even when the same claim includes the introductory phrases “one or more” or “at least one” and indefinite articles such as “a” or “an” (e.g., “a” and/or “an” should be interpreted to mean “at least one” or “one or more”); the same holds true for the use of definite articles used to introduce claim recitations. In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should be interpreted to mean at least the recited number (e.g., the bare recitation of “two recitations,” without other modifiers, means at least two recitations, or two or more recitations). Furthermore, in those instances where a convention analogous to “at least one of A, B, and C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., “a system having at least one of A, B, and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). In those instances where a convention analogous to “at least one of A, B, or C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., “a system having at least one of A, B, or C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). It will be further understood by those within the art that virtually any disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase “A or B” will be understood to include the possibilities of “A” or “B” or “A and B.”
In addition, where features or aspects of the disclosure are described in terms of Markush groups, those skilled in the art will recognize that the disclosure is also thereby described in terms of any individual member or subgroup of members of the Markush group.
As will be understood by one skilled in the art, for any and all purposes, such as in terms of providing a written description, all ranges disclosed herein also encompass any and all possible subranges and combinations of subranges thereof. Any listed range can be easily recognized as sufficiently describing and enabling the same range being broken down into at least equal halves, thirds, quarters, fifths, tenths, etc. As a non-limiting example, each range discussed herein can be readily broken down into a lower third, middle third and upper third, etc. As will also be understood by one skilled in the art all language such as “up to,” “at least,” and the like include the number recited and refer to ranges which can be subsequently broken down into subranges as discussed above. Finally, as will be understood by one skilled in the art, a range includes each individual member. Thus, for example, a group having 1-3 cells refers to groups having 1, 2, or 3 cells. Similarly, a group having 1-5 cells refers to groups having 1, 2, 3, 4, or 5 cells, and so forth.
From the foregoing, it will be appreciated that various embodiments of the present disclosure have been described herein for purposes of illustration, and that various modifications may be made without departing from the scope and spirit of the present disclosure. Accordingly, the various embodiments disclosed herein are not intended to be limiting, with the true scope and spirit being indicated by the following claims.
All references recited herein are incorporated herein by specific reference in their entirety.
This patent application claims priority to U.S. Provisional Application No. 63/391,657 filed Jul. 22, 2022, which provisional is incorporated herein by specific reference in its entirety.
This invention was made with government support under GM130423 and CA260132 awarded by the National Institutes of Health. The government has certain rights in the invention.
| Number | Date | Country | |
|---|---|---|---|
| 63391657 | Jul 2022 | US |
