Invasive Clinical Tests Research Articles

Abstract LB381: Plasma microbiota as novel biomarkers of early epithelial ovarian cancer detection

Abstract Background: Ovarian cancer accounts for 2% of all female cancers in the United States yet it is the 5th leading cancer death among women. Advanced epithelial ovarian cancer (EOC) is associated with an overall survival rate of 30% but can be cured in up to 90% of cases if diagnosed early when the disease is still limited to the ovaries and fallopian tubes. While there is no effective screening method for EOC, developing novel and minimally invasive clinical tests is paramount to identify women with early disease as well as those who are at increased risk. Plasma-based microbiota signatures specific to EOC could become leading biomarkers of early disease in the field that complement existing clinical tools. Methods: We utilized an established institutional biobank to access 180 biobanked plasma samples from: (1) women with EOC; (2) women with non-EOC solid tumors; (3) women undergoing gynecologic-related procedures and non-EOC surgeries; and (4) healthy controls. Batch 1 included 96 plasma samples (n=24 per group) and Batch 2 included 84 samples (n=19 per group and 8 repeat EOC samples). Microbial profiles of plasma specimens were assessed using an amplicon-based sequencing method that targets the 16S rRNA gene in the bacterial genome to study bacterial phylogeny and taxonomy in diseased and healthy women. A stringent bioinformatic pipeline was applied to filter out suspicious bacterial contaminants at the genus level. Bacterial decontamination procedures in the pipeline included evaluating repeat plasma samples of EOC cases and sampling nucleic acid isolation kit reagents to serve as negative controls (only in Batch 2) . Differential abundances of the plasma microbiota among the groups were assessed using analysis of compositions of microbiomes (ANCOM) as implemented in R software package ANCOM-BC. Results: The 16S rRNA gene sequencing identified, classified, and quantified 564 bacterial genera in the circulation of women diagnosed with EOC, non-EOC solid tumors, benign gynecologic conditions, and healthy controls. Bioinformatic decontamination analysis removed bacteria: (1) with differing bacterial abundances between batches; (2) with higher bacteria in negative controls; (3) with differing bacterial abundances in repeat samples; and (4) known as contaminants in the literature that resulted in the removal of 225 high-risk bacterial contaminants. A total of 339 high quality bacteria remained for evaluation. Because we did not collect negative controls in Batch 1, only Batch 2 plasma samples (n=84; 27 in EOC group; 19 in each other group) were included in the final analysis. Women with EOC, which were primarily of the high-grade serous ovarian carcinoma histologic subtype had significantly distinct differential abundances of genera Brevibacterium (p <0.001), Chloronema (p <0.001), Facklamia (p <0.001), Zymomonas (p <0.001), and Sutterella (p <0.001) when compared to women with non-EOC solid tumors, benign gynecologic conditions, and healthy controls. Conclusions: These findings suggest that plasma EOC-associated bacteria could be exploited in the development of a microbial-based blood test for the diagnosis and early detection of EOC in routine practice settings. Citation Format: Diane E. Mahoney, Prabhakar Chalise, Dong Pei, Rachel Griffard, Trisha Home, Harsh Pathak, Shahid Umar, Andrew K. Godwin. Plasma microbiota as novel biomarkers of early epithelial ovarian cancer detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB381.

Diagnosis of Disease Using Whole Blood from a Fingerstick Spotted on Filter Paper: Gene Expression Signature Test for Alzheimer's and Parkinson's Diseases

Background: There is an unmet need for a minimally invasive clinical test using samples collected by medical staff or by self-collection to screen persons for Alzheimer's disease (AD), Parkinson's Disease (PD) and other dementias and diseases. AD is underdiagnosed today, particularly in underserved populations where it is high incidence (non-Hispanic black and Hispanic) and in rural populations. Even in populations with access to health care, diagnosis is often delayed by years, even though the most recently approved therapies are most efficacious when given early in the progression of disease. While dementias are diseases of the brain, many publications link the underpinning inflammatory aspects to circulating neutrophils, macrophages, and lymphocytes. Thus, there is an opportunity to exploit the hematologic aspects of AD and PD in its diagnosis and potentially, therapeutically. AD gene expression signatures using RNA extracted from venipuncture whole blood have been reported. FDA-cleared tests based on circulating biomarkers are in use today but are not definitive tests for AD. We developed a direct, extraction-free TempO-Seq® assay of gene expression using blood from a finger prick spotted on filter paper, providing a simple and minimally invasive method of obtaining a blood sample and performing a test that can potentially be used to identify a host of diseases and disease risk. We then implemented a test that classified patients as having AD or PD. Method: The commercial targeted sequencing whole transcriptome TempO-Seq® gene expression assay (Yeakley, PLosOne doi.org/10.1371/journal.pone.0178302) was adapted to utilize blood from a simple fingerstick spotted on filter paper and dried (not a biohazard, simplifying transport and testing). Three independent patient cohorts of samples (~50:50 male:female) were obtained from normal volunteers and patients clinically diagnosed with AD or PD based on cognitive testing. AD, PD, and used for training/retraining and testing/retesting AD and PD classification signatures. To account for the presence of subtypes in our dataset, we contrasted AD and control samples by testing hundreds of random subsets and performing differential gene expression analyses (DESeq2). We used machine learning approaches (k-nearest neighbors, random forest, support vector machine with either linear, polynomial or rgb kernel and extreme gradient boosting) to build algorithms differentiating control, AD and PD. Randomly sampled subsets accounting for 80% of each cohort were used to train these classifiers. The accuracy of calling AD and PD samples was determined using the remaining 20% of samples as a test set. For each classifier an area under ROC curve (AUC-ROC) was calculated. Gene set enrichment was performed using the Gene Ontology database for biological processes (p value threshold 0.05) to identify expressed pathways. Result: A protocol that eliminated interference by components of whole blood with enzymes used in molecular biology assays (including PCR) was successfully implemented. This permitted a TempO-Seq assay to be carried out without extraction of RNA from the filter paper blood spots. Highly expressed genes were attenuated to increase the sensitivity with which AD biomarker genes could be measured. Within-spot reproducibility (r>0.96) and day-to-day reproducibility of blood collected from the same donor (r>0.94) was excellent. The AUC-ROC for the AD classifier was 0.86, and for the PD classifier was 0.87. Predominate pathways were immune response pathways, with the three most significantly differentially expressed pathways related to the involvement of neutrophils in the immune and inflammatory response. Conclusion: Patients with AD and PD, and potentially other dementias and diseases, can be classifiedusing a TempO-Seq gene expression signature obtained from fingerstick blood spotted on filter paper. Such samples are easily collected by medical staff or by self-collection, potentially transforming the diagnosis of AD and PD, reducing health disparities, and by speeding up diagnosis, enabling therapy for many to begin earlier. The data support that neutrophils and immune cells either impact disease and/or are impacted by disease, consequently resulting in expression of disease signatures capable of classifying patients.

A gene expression signature for Alzheimer’s from finger prick blood spotted on a filter paper card

AbstractBackgroundThere is an unmet need for a minimally invasive clinical test using samples collected by medical staff or by self‐collection to screen persons at risk for Alzheimer’s disease (AD) for initial diagnosis as well as for monitoring progression. Addressing this need is even more challenging for underserved and rural populations. Currently, use of whole blood has required venipuncture and RNA extraction. None‐the‐less, AD gene expression signatures using RNA extracted from whole blood have been reported by a number of groups. We have developed a direct, extraction‐free TempO‐Seq® assay of gene expression using blood from a finger prick spotted on filter paper. This novel method is perhaps the simplest and least invasive method of obtaining a blood sample and performing a test that can be used to identify a diagnostic Alzheimer’s signature.MethodThe targeted sequencing of the whole transcriptome via the TempO‐Seq® gene expression assay (Yeakley, PLosOne doi.org/10.1371/journal.pone.0178302) was adapted to utilize blood spotted on filter paper. Samples were obtained under an IRB‐approved protocol from normal volunteers and patients clinically diagnosed with AD or Parkinson’s disease (PD).ResultA protocol that eliminated interference by components of whole blood with enzymes used in molecular biology assays was successfully implemented. This permitted a TempO‐Seq assay to be carried out without extraction of RNA from the filter paper blood spots. Highly expressed genes were attenuated to increase the sensitivity with which AD biomarker genes could be measured. The shelf‐life of blood spotted filter paper stored at room temperature was greater than 6 months. AD, PD, and normal control blood samples were assayed and a proposed gene expression signature for AD was identified.ConclusionUse of a simple gene expression‐based assay of blood from a finger prick spotted on filter paper to diagnose AD is feasible. The spotted blood sample is stable for months at room temperature, permitting self‐collection or assisted collection and mailing of samples for testing.

Computational biomarker pipeline from discovery to clinical implementation: plasma proteomic biomarkers for cardiac transplantation.

Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac rejection may offer a relevant post-transplant monitoring tool to effectively guide clinical care. The proposed computational pipeline is highly applicable to a wide range of biomarker proteomic studies.

Automated Software Analysis of Corneal Micrographs for Peripheral Neuropathy

A relationship has been reported between the presence of peripheral neuropathy and the density and shape of corneal nerve fibers. Peripheral neuropathy is a debilitating condition that arises from many common health problems, and its presence is often confirmed with an invasive clinical test called intramuscular electromyography (EMG). In this study, the possibility of developing an alternative or adjunct test to EMG based on the appearance of nerve fibers in corneal micrographs was explored. Since corneal imaging is virtually noninvasive compared with EMG, such a test may be administered more liberally and frequently, before neuropathy symptoms occur. A software program that automatically traces nerve fibers in corneal micrographs and generates measures based on these traces was implemented. This software was applied to a database of images collected by confocal laser scanning corneal microscopy from diabetic subjects whose levels of neuropathy were measured with EMG and from healthy subjects. Trends in the nerve fiber density and various measures of shape were calculated and observed, to explore the possibility of using these measures as a clinical tool for corroborating symptoms, confirming an evaluation, or evaluating risk factors for developing neuropathy. Preliminary statistical trends show a potential for measuring and observing neuropathy severity or for providing an objective risk measure for a patient's ensuing condition. More work is needed in the development of the measures and in their testing to prove that the measures can be made repeatable in a clinical environment.

Time-reversal focusing through the skull : application to High Intensity Focused Ultrasound brain therapy.

Bursts of focused ultrasound energy a billion times more intense than diagnostic ultrasound have become available commercially recently for clinical ablation of various biological soft tissues from prostate cancer to uterine fibroids. However, although that the use of High Intensity Focused Ultrasound (HIFU) for brain therapeutic applications was already envisioned in the early 5O’s, the targeting of brain with High Intensity Focused Ultrasound (HIFU) remains today a technological challenge. Due to the large discrepancy between the speed of sound in the bone and in the soft tissues associated with a high absorption of the bone. the ultrasonic wavefront is strongly distorted by the skull bone. resulting in a destruction of the focus. During the last decade, novel adaptive focusing techniques have been developed in order to correct the skull aberrations. The potential of time reversal focusing associated with the development of high power multi-element therapeutic transducers allow now the accurate focusing of high power ultrasound in the brain. Minimally invasive clinical tests on sheep will be presented as well as fully non-invasive tests on monkeys.

Arrhythmogenic right ventricular cardiomyopathy: diagnostic and prognostic value of the cardiac MRI in relation to arrhythmia-free survival

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a potentially fatal disease, which is often difficult to diagnose. As a non-invasive test cardiac magnetic resonance imaging (CMR) has become an important tool in establishing the diagnosis. The aim of this study was to evaluate the diagnostic and prognostic value of CMR in patients with suspected ARVC and to assess the long-term outcome of patients with CMR-diagnosed ARVC. Thirty-six patients with suspected ARVC (26 male, 10 female, median age 41 years) underwent non-invasive and invasive clinical tests as gold standard for ARVC diagnosis. ARVC was clinically diagnosed in 19 patients and excluded in 17 patients. Both groups underwent CMR, and diagnosis was confirmed by CMR in 16/18 patients with clinically diagnosed ARVC (sensitivity 89%), and correctly excluded in 14/17 of patients with clinically excluded ARVC (specificity 82%). This result indicates a positive predictive value of the CMR of 84%, and a negative predictive value of 88%, respectively (p < 0.0001). Using a scoring system, multiple CMR parameters were compared in the two groups in regard of the clinical diagnosis. By univariate analysis, right ventricular fatty tissue infiltration (p = 0.0003) was predictive for diagnosis. Compared by outcome, 37% of patients with clinically and by CMR-diagnosed ARVC had an arrhythmic event during a mean follow-up of 16 +/- 11 months. These data suggest that CMR is a highly sensitive and specific method to diagnose or exclude ARVC, and thus, has an important prognostic impact on predicting arrhythmia free survival.

The use of SELDI ProteinChip array technology in renal disease research.

Proteomics approaches can be useful in identifying biomarkers of renal disease as well as in understanding biological processes specific to renal function. When combined with laser-capture microdissection (LCM), proteomics techniques can identify biomarkers that are specific to structures of the renal parenchyma such sas glomeruli, proximal tubules, or distal tubules, thus increasing the specificity of markers. In addition, since proteomics can be applied to urine as well as cells of the renal parenchyma, proteomics has the potential to identify biomarkers that could be useful in non invasive clinical tests.