Biomarkers In Clinical Studies Research Articles

Serum CD133-Associated Proteins Identified by Machine Learning Are Connected to Neural Development, Cancer Pathways, and 12-Month Survival in Glioblastoma.

Glioma is the most prevalent type of primary central nervous system cancer, while glioblastoma (GBM) is its most aggressive variant, with a median survival of only 15 months when treated with maximal surgical resection followed by chemoradiation therapy (CRT). CD133 is a potentially significant GBM biomarker. However, current clinical biomarker studies rely on invasive tissue samples. These make prolonged data acquisition impossible, resulting in increased interest in the use of liquid biopsies. Our study, analyzed 7289 serum proteins from 109 patients with pathology-proven GBM obtained prior to CRT using the aptamer-based SOMAScan® proteomic assay technology. We developed a novel methodology that identified 24 proteins linked to both serum CD133 and 12-month overall survival (OS) through a multi-step machine learning (ML) analysis. These identified proteins were subsequently subjected to survival and clustering evaluations, categorizing patients into five risk groups that accurately predicted 12-month OS based on their protein profiles. Most of these proteins are involved in brain function, neural development, and/or cancer biology signaling, highlighting their significance and potential predictive value. Identifying these proteins provides a valuable foundation for future serum investigations as validation of clinically applicable GBM biomarkers can unlock immense potential for diagnostics and treatment monitoring.

Extracellular vesicles secreted by 3D tumor organoids are enriched for immune regulatory signaling biomolecules compared to conventional 2D glioblastoma cell systems.

Newer 3D culturing approaches are a promising way to better mimic the in vivo tumor microenvironment and to study the interactions between the heterogeneous cell populations of glioblastoma multiforme. Like many other tumors, glioblastoma uses extracellular vesicles as an intercellular communication system to prepare surrounding tissue for invasive tumor growth. However, little is known about the effects of 3D culture on extracellular vesicles. The aim of this study was to comprehensively characterize extracellular vesicles in 3D organoid models and compare them to conventional 2D cell culture systems. Primary glioblastoma cells were cultured as 2D and 3D organoid models. Extracellular vesicles were obtained by precipitation and immunoaffinity, with the latter allowing targeted isolation of the CD9/CD63/CD81 vesicle subpopulation. Comprehensive vesicle characterization was performed and miRNA expression profiles were generated by smallRNA-sequencing. In silico analysis of differentially regulated miRNAs was performed to identify mRNA targets and corresponding signaling pathways. The tumor cell media and extracellular vesicle proteome were analyzed by high-resolution mass spectrometry. We observed an increased concentration of extracellular vesicles in 3D organoid cultures. Differential gene expression analysis further revealed the regulation of twelve miRNAs in 3D tumor organoid cultures (with nine miRNAs down and three miRNAs upregulated). MiR-23a-3p, known to be involved in glioblastoma invasion, was significantly increased in 3D. MiR-7-5p, which counteracts glioblastoma malignancy, was significantly decreased. Moreover, we identified four miRNAs (miR-323a-3p, miR-382-5p, miR-370-3p, miR-134-5p) located within the DLK1-DIO3 domain, a cancer-associated genomic region, suggesting a possible importance of this region in glioblastoma progression. Overrepresentation analysis identified alterations of extracellular vesicle cargo in 3D organoids, including representation of several miRNA targets and proteins primarily implicated in the immune response. Our results show that 3D glioblastoma organoid models secrete extracellular vesicles with an altered cargo compared to corresponding conventional 2D cultures. Extracellular vesicles from 3D cultures were found to contain signaling molecules associated with the immune regulatory signaling pathways and as such could potentially change the surrounding microenvironment towards tumor progression and immunosuppressive conditions. These findings suggest the use of 3D glioblastoma models for further clinical biomarker studies as well as investigation of new therapeutic options.

Implications of the new nomenclature of steatotic liver disease and definition of metabolic dysfunction-associated steatotic liver disease.

The American and European liver associations have endorsed new nomenclature of steatotic liver disease (SLD) and definition of metabolic dysfunction-associated steatotic liver disease (MASLD). To review the historical development leading to the changes and to discuss the implications of the changes on research and clinical practice METHODS: We performed a literature search using keywords related to MASLD and non-alcoholic fatty liver disease (NAFLD). The SLD umbrella allows classification of patients under the key categories of MASLD, alcohol-associated liver disease and a new entity termed MetALD, which represents MASLD with increased alcohol intake. The diagnosis of MASLD requires the demonstration of hepatic steatosis and at least one metabolic risk factor, whereas MASLD can co-exist with other liver diseases such as chronic viral hepatitis. Despite the change in definition, over 95% of patients previously known as having NAFLD fulfil diagnostic criteria for MASLD. It is conceivable that future clinical trials and biomarker studies will continue to exclude concomitant liver diseases. As most patients with MASLD are seen at primary care and non-hepatology settings, communication with other stakeholders is essential to ensure disease awareness and smooth adoption of the changes. The new nomenclature is both a challenge, given the need for dissemination and education across the spectrum of stakeholders, and an opportunity to bring everyone together and spark new research to better understand epidemiology, natural history, diagnosis, biomarkers and management strategies across the spectrum of SLD.

The role of miR-143/miR-145 in the development, diagnosis, and treatment of diabetes.

Diabetes mellitus [DM], is a multifaceted metabolic disease, which has become a worldwide threat to human wellness. Over the past decades, an enormous amount of attention has been devoted to understanding how microRNAs [miRNAs], a class of small non-coding RNA regulators of gene expression at the post-transcriptional level, are tied to DM pathology. It has been demonstrated that miRNAs control insulin synthesis, secretion, and activity. This review aims to provide an evaluation of the use of miR-143 and miR-145 as biomarkers for the diagnosis and prognosis of diabetes. The use of miR-143 and miR-145 as biomarkers for the diagnosis and prognosis of diabetes has been studied, and research that examined this link was sought after in the literature. In addition, we will discuss the cellular and molecular pathways of insulin secretion regulation by miR-143/145 expression and finally their role in diabetes. In the current review, we emphasize recent findings on the miR-143/145 expression profiles as novel DM biomarkers in clinical studies and animal models and highlight recent discoveries on the complex regulatory effect and functional role of miR-143/145 expression in DM. A novel clinical treatment that alters the expression and activity of miR-143/miR-145 may be able to return cells to their natural state of glucose homeostasis, demonstrating the value of using comprehensive miRNA profiles to predict the beginning of diabetes. The online version contains supplementary material available at 10.1007/s40200-023-01317-y.

Mitochondrial-Derived Vesicles: The Good, the Bad, and the Ugly.

Mitophagy is crucial for maintaining mitochondrial quality. However, its assessment in vivo is challenging. The endosomal-lysosomal system is a more accessible pathway through which subtypes of extracellular vesicles (EVs), which also contain mitochondrial constituents, are released for disposal. The inclusion of mitochondrial components into EVs occurs in the setting of mild mitochondrial damage and during impairment of lysosomal function. By releasing mitochondrial-derived vesicles (MDVs), cells limit the unload of mitochondrial damage-associated molecular patterns with proinflammatory activity. Both positive and negative effects of EVs on recipient cells have been described. Whether this is due to the production of EVs other than those containing mitochondria, such as MDVs, holding specific biological functions is currently unknown. Evidence on the existence of different MDV subtypes has been produced. However, their characterization is not always pursued, which would be relevant to exploring the dynamics of mitochondrial quality control in health and disease. Furthermore, MDV classification may be instrumental in understanding their biological roles and promoting their implementation as biomarkers in clinical studies.

Characterizing telomerase reverse transcriptase (TERT) promoter mutations (mut) across sex, race, and cancer types.

3122 Background: TERT promoter mut. have been evaluated as a predictive biomarker for patients (pts) receiving immune checkpoint inhibitors. Understanding the prevalence of TERT promoter mut. by sex, race, and cancer type is essential for optimizing its use. Methods: Pts who underwent next-generation sequencing at Dana-Farber Cancer Institute and Memorial Sloan Kettering Cancer Center were identified from the AACR Genomics Evidence Neoplasia Information Exchange (GENIE) registry v11.0. Self-reported race and sex data were extracted for ten cancer types with the highest prevalence of TERT promoter mut. The strength of associations with TERT promoter mut. was quantified by Odds ratios (ORs) and two-sided Fisher’s exact tests, along with FDR-adjusted q-values using the Benjamini-Hochberg method. Results: We identified 31,925 pts – 87.6% (27,970) self-identified as White, 7.1% (2,273) Asian, and 5.3% (1,682) Black. TERT promoter mut. were present in 17% (5,470) tumors, including 56% (1,346/2,411) bladder cancers, 43% (966/2,243) melanomas, 41% (395/959) thyroid cancers, and 23% (183/782) head and neck cancers (HNC). TERT promoter mut. were significantly higher in males vs. females in melanoma, cancer of unknown primary (CUP), hepatobiliary (HPB), and thyroid cancers. In contrast, males harbored fewer mut. vs. females with HNC. Interestingly, TERT promoter mut. varied by race. Mut. frequency was significantly higher in White pts with melanoma (44%, n=964/2176) compared to Asian and Black pts (2.9%, n= 2/67) (OR=25.8; 95% CI = 6.9 - 217, p<0.0001). Asian males with HNC (37%, n= 22/60) were enriched for TERT promoter mut. vs. White males (19%, n= 93/489) (OR = 2.5; 95% CI = 1.4 - 4.4; q=0.03). Within HNC tumors, oral cavity (OC) tumors (44.3%, n= 85/192) were associated with higher TERT promoter mut. vs. other HNC subtypes (16.6%, n= 98/590) (OR = 4.4; 95% CI = 3.03 - 6.26; p<0.0001). Asian pts with OC (70%, n=14/20) harbored more mut. vs. White pts with OC (41.4%, n=70/169) (OR = 3.3; 95% CI = 1.2 - 9; p<0.05). Conclusions: Our study demonstrates differences in the distribution of TERT promoter mut. by sex, race, and cancer type. Considering these variations is crucial for future clinical trial design and biomarker studies. [Table: see text]

Abstract 6639: Preclinical characterization and clinical biomarker studies with RP3, a novel oncolytic immunotherapy expressing a fusogenic protein, a human anti-CTLA-4 antibody, hCD40L and h4-1BBL

Abstract Introduction: RP3, a tumor-directed oncolytic immunotherapy (TDOI), is a selectively replication-competent HSV-1 that contains the codon-optimized sequence for the fusogenic GALV-GP-R- protein, an anti-CTLA-4 antibody-like molecule, CD40L, and 4-1BBL. The expression of GALV-GP-R- potentiates immunogenic tumor cell death through the induction of cell-to-cell fusion. CD40L enhances dendritic cell and macrophage activation and 4-1BBL promotes CD8+ T-cell activation and co-stimulation. The anti-CTLA-4 antibody-like molecule blocks the interaction of CTLA-4 with its ligands B7.1 and B7.2, further enhancing T cell activation. RP3 is currently being assessed in a Phase 1 clinical trial with or without nivolumab in patients with advanced solid tumors (NCT04735978). Methods: CD1 nude mice with A375 melanoma xenograft tumors (Group 1) were treated with a single intratumoral injection of 1 × 107 PFU/mL of RP3. Tumors and blood samples were collected 3 days later, and immunohistochemistry (IHC) was performed to detect CD40L, 4-1BBL and HSV-1. For anti-CTLA-4 detection, two doses of 107 PFU/mL of RP3 were injected intratumorally into C57BL/6 mice bearing 4434 murine BRAFV600E mutant melanoma tumors (Group 2). Tumors and blood samples were collected at 3, 6, 9, 12 and 15-days post-dosing and anti-CTLA-4 ELISA was performed. For clinical biomarker studies, tumor biopsies were collected pre- and post-RP3 treatment. CD8 and PD-L1 were characterized by IHC, and gene expression analysis (GEA) was performed. TCR analysis was also performed using PBMCs. Results: IHC analysis from Group 1 confirmed abundant and widespread expression of CD40-L and 4-1BBL, which were detected alongside with HSV-1 antigen. In the blood samples collected from Group 2, robust levels of anti-CTLA-4 antibody were detected, which stayed in detectable range up to 15 days after the 2nd RP3 injection. IHC analysis of patient tumor samples demonstrated a marked increase in CD8 T cells and PD-L1 expression. GEA of patient tumor biopsies demonstrated increased levels of genes associated with innate and adaptive immune activation and genes previously reported to be associated with responsiveness to anti-PD1 therapy. TCR sequencing of PBMCs and multiplex IHC analysis are ongoing and updated results will be presented. Conclusion: Preclinical experiments from mice models confirmed the robust expression of CD40-L, 4-1BBL and anti-CTLA-4 in RP3-injected tumors. Biomarker studies from patients demonstrate increases in CD8-T cell infiltration and PD-L1 expression post RP3 +/- nivolumab treatment, including increases in the expression of genes associated with response to anti-PD-1 therapy. These data indicate the potential for broad utility of RP3 in a range of tumor types, including in tumors that are not sensitive to PD-1 blockade. Citation Format: Praveen K. Bommareddy, Kevin Harrington, Victoria Roulstone, Joan Kyula, Aaron Clack, Linta Kuncheria, Sylwia Jones, Robert Coffin. Preclinical characterization and clinical biomarker studies with RP3, a novel oncolytic immunotherapy expressing a fusogenic protein, a human anti-CTLA-4 antibody, hCD40L and h4-1BBL. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6639.

Semi-Automated Lectin Magnetic Bead Array (LeMBA) for Translational Serum Glycoprotein Biomarker Discovery and Validation.

Aberrant protein glycosylation is a characteristic of diverse diseases which has been explored as biomarkers. To support translational serum glycoprotein biomarker discovery and validation, we developed a semi-automated workflow using individual lectin-coupled magnetic beads to conduct lectin pulldowns in a high-throughput format. Lectins are naturally occurring glycoprotein binding proteins widely used in glycobiology. While lectin-affinity isolation has been coupled to mass spectrometry-based proteomics, the lectin magnetic bead array (LeMBA) platform allows technically robust screening and measurement of clinical cohorts. This chapter describes detailed lectin-magnetic bead coupling, serum denaturation, lectin magnetic bead pulldown, and on-bead trypsin digest. The resulting tryptic peptides are analyzed by untargeted or targeted liquid chromatography-mass spectrometry (LC-MS), for biomarker discovery, or qualification/validation, respectively. LeMBA-MS generates quantitative data for glycoforms based on lectin affinity of the glycoprotein coupled with MS measurement of one or more prototypic peptides and has successfully been used to discover and validate novel serum cancer glycoprotein biomarkers. This chapter includes detailed protocols for two different liquid handlers, along with recommendations on quality control measures for clinical biomarker studies.

Longitudinal increase of sTREM2 in CSF and its relationship with other biomarkers and cognition along the evolution of autosomal dominant Alzheimer’s disease

AbstractBackgroundTherapeutic modulation of TREM2‐dependent microglial function provides an additional strategy to slow progression of Alzheimer’s disease (AD). Although studies on animal models suggest that TREM2 is protective, clinical biomarker studies reach different conclusions regarding TREM2 effect on tau pathology and its potential beneficial role in human AD. The longitudinal study of cerebrospinal fluid (CSF) soluble TREM2 (sTREM2) as a biomarker of TREM2 signalling during the evolution of autosomal dominant AD and its relationship with different biomarkers shed additional light on these controversies.MethodWe measured sTREM2 by a novel MSD‐immunoassay selectively detecting ADAM10/17 generated sTREM2 in longitudinal CSF samples from 93 non‐carriers (NC) and 155 mutation carriers (MC) ‐presenilin 1, presenilin 2 and amyloid precursor protein genes‐, participating in the Dominantly Inherited Alzheimer Network (DIAN) observational study, and with available longitudinal data on amyloid‐β (Aβ) and tau‐related CSF biomarkers, structural MRI, Pittsburgh compound B PET (PIB‐PET) and cognition. We based our statistical analysis on univariate and bivariate linear mixed effects models.ResultOur recent results showed that longitudinal sTREM2 increase was predicted by the earliest Aβ‐aggregation captured by lower CSF‐Aβ42, but not yet by a higher cortical uptake in PiB‐PET. In line with previous cross‐sectional studies, higher sTREM2 increase rate was associated with slower Aβ‐deposition, as measured by CSF Aβ42 in presymptomatic MC, and by PIB‐PET in symptomatic MC. Furthermore, MC with high or low sTREM2 increase rates had opposite associations between CSF Aβ42 and PiB‐PET longitudinal changes, further suggesting that TREM2 modifies Aβ‐plaque deposition and compaction. Regarding tau‐related pathology, we found that lower sTREM2 increase rate enhanced the increase of CSF p‐tau associated with PiB‐PET signal increase. Finally, higher sTREM2 increase rate in presymptomatic MC was associated with slower cortical shrinkage in the precuneus and slower cognitive decline.ConclusionThe most novel results on longitudinal sTREM2 in CSF position the TREM2 response right after the first pathological changes in Aβ‐aggregation and support its beneficial effect on Aβ‐deposition, Aβ‐dependent tau pathology, cortical shrinkage, and cognitive decline. These findings strongly support ongoing efforts to develop TREM2‐boosting therapies and suggest sTREM2 as a key marker for clinical trial design and interpretation.

Abstract CT155: Clinical biomarker studies with an enhanced potency oncolytic HSV expressing an anti-CTLA-4 antibody, as a single agent and combined with nivolumab in patients with advanced solid tumors indicates potent immune activation

Abstract Introduction: RP2 is a novel, enhanced potency oncolytic HSV1 which expresses GM-CSF, an anti-CTLA-4 antibody-like molecule and the fusogenic gibbon ape leukemia virus membrane R- glycoprotein (GALV-GP R-). RP2 is in clinical development in a range of solid tumors alone and with nivolumab (nivo). RP2 + nivo has resulted in deep and durable responses in patients who failed prior anti-PD1 therapy (SITC 2021). Here we present biomarker data in patients treated with RP2 alone or combined with nivo from an ongoing clinical trial (NCT04336241). Methods: Tumor biopsies and peripheral blood mononuclear cells (PBMCs) were collected pre-treatment and at D43. The tumor immune microenvironment (TIME) was analyzed by multi-plex (7 color 6-plex - CD8, PD-L1, PD-1, foxp3, CD68 and S100B) immunohistochemistry (IHC) of tumor biopsies using the Opal Human Panel (OHP) 6043 and by gene expression analysis using the NanoString IO360 panel. The tumor inflammation signature score (TIS) was also calculated using an 18 gene signature (Ayers JCI 2017) . Systemic anti-tumor immunity was assessed using PBMCs by sequencing the CDR3 regions of TCRβ chains using immunoSEQ Assay. Correlation analysis of baseline tumor PD-L1 and CD8 status versus clinical responses was also performed. Results: IHC indicated robust increases in CD8 T cell influx and PD-L1 expression post-RP2 alone and with RP2 + nivo. An increase in the CD8/foxp3+ cell ratio was observed by multi-plex IHC. A consistent increase in CD8 and PD-L1 was observed in most of the tested biopsies (~70%), which generally appeared to be co-located (n=20). These increases in CD8 and PD-L1 expression levels were observed in both superficial and visceral tumors. A particularly striking change was observed in a biopsy obtained from a liver lesion from a tebantafusp and ipi/pembro-failed uveal melanoma patient. Clinical responses were independent of baseline CD8 T cell infiltration, PD-L1 expression levels, and prior anti-PD-1 therapy status. Gene expression analysis of tumor biopsies (n=12) indicated increases in the expression of key genes associated with immune activation, particularly those associated with dendritic cell function, major histocompatibility complex-II and interferon-gamma signature. Increases in expression of genes associated with ARG1, cytotoxicity, IDO1, NK cell and Th1 cell abundance were observed, particularly in responding patients. TCR sequencing of PBMCs revealed expansion of pre-existing T cell clones and the appearance of new clones post-RP2 monotherapy and RP2 + nivo, with ~50% of these changes being newly detected clones. Expansion of pre-existing clones and generation of new T cell clones specific for MART-1 was also observed with RP2 monotherapy and in combination. Conclusion: The biomarker data presented indicates broad immune activation by RP2 and demonstrates that clinical response does not correlate with baseline PD-L1 and CD8 expression status. Clinical responses were often associated with increases in gene signatures associated with cytotoxic T, NK and Th1 cells. These data indicate the potential for broad utility of RP2 in a range of tumor types, including in patients with primary or acquired resistance to immune checkpoint blockade. Citation Format: Kevin J. Harrington, Praveen K. Bommareddy, Mark R. Middleton, Joseph J. Sacco, Anna Olsson-Brown, Tze Y. Chan, Pablo Nenclares, Isla Leslie, Francesca Aroldi, Imran Saleem, Christoph M. Ahlers, Henry Castro, Robert S. Coffin. Clinical biomarker studies with an enhanced potency oncolytic HSV expressing an anti-CTLA-4 antibody, as a single agent and combined with nivolumab in patients with advanced solid tumors indicates potent immune activation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr CT155.

Abstract 1130: CETSA interaction proteomics define specific RNA modification pathways as key components of fluorouracil based cancer drug cytotoxicity

Abstract Introduction: Our current understanding of the mechanism of action (MoA) of many cancer drugs is still incomplete. This hampers efforts in establishing efficient personalised medicine regimens, the optimisation of combination therapies, and the development of next generation drugs. Results: Here, we apply a high-resolution implementation of the proteome-wide cellular thermal shift assay (CETSA) to follow protein interaction changes induced by the antimetabolite 5-fluorouracil (5-FU) and related nucleosides. We focus on the relatively early drug effects, up to 12 hours, when this time frame is less accessible to other omics methods, while critical for defining drug MoAs. We confirm anticipated effects on the known main target, thymidylate synthase (TYMS), and enzymes in pyrimidine metabolism and DNA damage pathways. However, most interaction changes we see are for proteins previously not associated with the MoA of 5-FU, including wide-ranging effects on RNA modification and processing pathways. Attenuated responses of specific proteins in a resistant cell model identify key components of the 5-FU MoA, where intriguingly the abrogation of TYMS inhibition is not required for cell proliferation. Conclusions: When 5-FU is one of the most used and studied cancer drugs, this novel information significantly expands our understanding of the 5-FU MoA and will be important to direct further work towards dissecting its complete MoA. Furthermore, the CETSA responses of several proteins now provide ideal readouts for directly monitoring whether the required 5-FU effects are accomplished and can now be examined as CETSA-based candidate biomarkers in clinical studies. Together, this work also validates an efficient strategy for dissecting the MoA of cancer drugs, which could be broadly applicable to other cancer drugs in clinical use or in development. Citation Format: Smaranda Bacanu, Ying Yu Liang, Anderson D. Ramos, Nayana Prabhu, Pär Nordlund. CETSA interaction proteomics define specific RNA modification pathways as key components of fluorouracil based cancer drug cytotoxicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1130.

Current status and future perspective of neoadjuvant therapy in locally advanced and borderline resectable pancreatic adenocarcinoma: a narrative review.

The concept of neoadjuvant approach for patients with locally advanced pancreatic cancer (LAPC) has been evolving with the advancement in therapeutic modalities. In this narrative review, we aimed to discuss the updates and future perspectives on the treatment of LAPC. We discussed the recent literature and up-to-date evidence along with the future perspectives for the treatment of LAPC using the neoadjuvant approach. Reviewed literatures were searched by systematic search of PubMed and Google Scholar, including articles published in English between January 1st, 2013, and October 31st, 2021. We aimed to review the efficacy outcomes of modern-era chemotherapy regimens and chemoradiation therapy for LAPC based on the results of up-to-date clinical trials and pivotal observational studies. Moreover, we aimed to discuss the role of conversion surgery and studies on the prediction of resectability after neoadjuvant therapy along with the necessity of adjuvant therapy for patients who have received neoadjuvant systemic treatments. Finally, we have addressed several unanswered questions regarding the optimal management of patients with LAPC and determined the future directions by introducing some ongoing trials. Current chemotherapy and chemoradiation therapy has improved clinical outcomes and the conversion surgery rate in patients with LAPC. Future randomized clinical trials and biomarker studies are needed to provide better evidence that can aid in the selection of optimal treatment modalities for individual patients.

Methods for quantification of glycopeptides by liquid separation and mass spectrometry.

Recent advances in analytical techniques provide the opportunity to quantify even low-abundance glycopeptides derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Herein, we discuss the sample preparation procedures and the mass spectrometry (MS) strategies that have facilitated glycopeptide quantification, as well as the standards used for glycopeptide quantification. For sample preparation, various glycopeptide enrichment methods are summarized including the columns used for glycopeptide separation in liquid chromatography separation. For MS analysis strategies, MS1 level-based quantification and MS2 level-based quantification are described, either with or without labeling, where we have covered isotope labeling, TMT/iTRAQ labeling, data dependent acquisition, data independent acquisition, multiple reaction monitoring, and parallel reaction monitoring. The strengths and weaknesses of these methods are compared, particularly those associated with the figures of merit that are important for clinical biomarker studies and the pathological and functional studies of glycoproteins in various diseases. Possible future developments for glycopeptide quantification are discussed.

Exploring the translational potential of clusterin as a biomarker of early osteoarthritis.

BackgroundClusterin (CLU; also known as apolipoprotein J) is an ATP-independent holdase chaperone that prevents proteotoxicity as a consequence of protein aggregation. It is a ∼60 kDa disulfide-linked heterodimeric protein involved in the clearance of cellular debris and the regulation of apoptosis. CLU has been proposed to protect cells from cytolysis by complement components and has been implicated in Alzheimer’s disease due to its ability to bind amyloid-β peptides and prevent aggregate formation in the brain. Recent studies suggest that CLU performs moonlighting functions. CLU exists in two major forms: an intracellular form and a secreted extracellular form. The intracellular form of CLU may suppress stress-induced apoptosis by forming complexes with misfolded proteins and facilitates their degradation. The secreted form of CLU functions as an extracellular chaperone that prevents protein aggregation.MethodsIn this review, we discuss the published literature on the biology of CLU in cartilage, chondrocytes, and other synovial joint tissues. We also review clinical studies that have examined the potential for using this protein as a biomarker in synovial and systemic fluids of patients with rheumatoid arthritis (RA) or osteoarthritis (OA).ResultsSince CLU functions as an extracellular chaperone, we propose that it may be involved in cytoprotective functions in osteoarticular tissues. The secreted form of CLU can be measured in synovial and systemic fluids and may have translational potential as a biomarker of early repair responses in OA.ConclusionThere is significant potential for investigating synovial and systemic CLU as biomarkers of OA. Future translational and clinical orthopaedic studies should carefully consider the diverse roles of this protein and its involvement in other comorbidities. Therefore, future biomarker studies should not correlate circulating CLU levels exclusively to the process of OA pathogenesis and progression. Special attention should be paid to CLU levels in synovial fluid.The Translational potential of this articleThere is significant potential for investigating synovial and systemic CLU as a predictive biomarker of osteoarthritis (OA) progression and response to novel treatments and interventions. Given that CLU plays diverse roles in other comorbidities such as rheumatoid arthritis (RA) and obesity, future translational and clinical orthopaedic biomarker studies should not directly correlate circulating CLU levels to the process of OA pathogenesis and progression. However, special attention should be paid to CLU levels in synovial fluid. The cytoprotective properties of CLU may support the implementation of regenerative strategies and new approaches for developing targeted therapeutics for OA.

Prediction of amyloid‐positivity in individuals with subjective cognitive decline: Machine learning approaches to optimize number‐needed‐to‐screen

AbstractBackgroundSubjective cognitive decline (SCD) is defined as the worsening of cognitive functions reported by the patient without any objective cognitive deficits nor any significant impairment of daily functioning. SCD constitutes a heterogeneous clinical condition regarding aetiology, clinical presentation and prognosis that can either progress to dementia, remain stable over time or remit [1, 2]. SCD‐individuals with pathological ß‐amyloid‐42(Aß‐42)‐levels in cerebrospinal fluid are in Alzheimer’s disease (AD) continuum, have an increased risk for conversion to dementia and are an important target for prevention studies in AD. However, the invasiveness of lumbar punctures and costs of positron emmission tomography (PET) limit assessment of amyloid positivity in SCD‐cohorts on large scale. Increasing the likelihood of amyloid positivity is an approach to lower the number needed to screen for amyloid in SCD for intervention trials.MethodsWe conducted a supervised machine learning (ML) analysis in 211 SCD‐individuals of the DELCODE study, of which 88 were amyloid positive [3]. Amyloid positivity (pathological ß‐amyloid‐1‐ 41/40‐ratio) in SCD‐individuals was predicted by different data modalities including clinical (n=42 features), neuropsychological (n=70 features) and neuroimaging (n=231 features) data. Repeated cross‐validation was implemented to tune ML hyperparameters and to obtain reliable model performance. Feature selection methods were employed to derive robust and parsimonious ML models that can be implemented with as little and easy‐to‐collect data as possible.ResultsThe preliminary analyses indicated that Aß‐42‐status could be predicted based on cognitive data with a balanced accuracy of 58% (specificity 65%, sensitivity 51%), based on clinical data with an accuracy of 67% (specificity 75%, sensitivity 59%) and based on neuroimaging data (FSL derived parameters of structural MRI) with an accuracy of 56% (specificity 62%, sensitivity 39%).ConclusionWe demonstrate the potential of ML algorithms to predict Aß‐42‐status in individuals with SCD based on non‐invasively measurable parameters. These results underline the potential of ML to conduct efficient biological risk‐stratification in SCD populations with potential applications in clinical intervention trials or biomarker studies.

Abstract LB180: Clinical biomarker studies with two fusion-enhanced versions of oncolytic HSV (RP1 and RP2) alone and in combination with nivolumab in cancer patients indicate potent immune activation

Abstract Introduction:RP1 and RP2 are novel, enhanced potency oncolytic versions of HSV1 engineered to express human GM-CSF and the gibbon ape leukemia virus membrane R- glycoprotein (GALV-GP R-), providing constitutive fusion activity and increased immunogenic cell death. RP2 further expresses an anti-CTLA-4 antibody-like molecule. Murine versions of RP1 and RP2 exhibited synergy in combination with anti-mouse-PD-1 leading to enhanced regression of both injected and un-injected tumors in mice (Thomas et al JITC 2019). RP1 and RP2 are currently being evaluated in clinical trials in a range of solid tumors alone and combined with anti-PD1 therapy, where deep and durable responses have been demonstrated (SITC 2020). Here we present biomarker data from the Phase 1/2 clinical trial of RP1 alone and combined with nivolumab (NCT03767348) and from the Phase 1 portion of the clinical trial with RP2 alone (NCT04336241). Methods: In the Phase 1/2 studies tumor biopsies and peripheral blood mononuclear samples (PBMCs) were collected at screening and at D43 for biomarker analysis, after combination therapy with nivolumab for RP1 and following single agent treatment for RP2. Immunohistochemistry (IHC) was performed for CD8 (SP57 clone, Ventana) and for PD-L1 (28-8 clone, pharmDx assay). Gene expression was analysed using NanoString to assess effects on a range of genes. The tumor inflammation signature score (TIS) was also calculated. Results:Preliminary Phase 1/2 biomarker data from paired tumor biopsies include the following: Immunohistochemistry for CD8 and PD-L1 (n=30) indicated robust and increased infiltration of CD8+ T cells and PD-L1 expression, both after combined treatment with RP1 and nivolumab and after single agent RP2 across different tumor types, and including reversal of T cell exclusion following prior combined treatment with ipilimumab and nivolumab in melanoma. Gene expression analysis (n=15) demonstrated a significant increase in the expression levels of genes associated with innate and adaptive immune activation and genes previously reported to be associated with responsiveness to anti-PD1 therapy, particularly CD8, CXCL9, CD27 and TIGIT, as well as consistently increased TIS. Conclusion:Consistent with the pre-clinical data, preliminary clinical biomarker data indicate substantial increase in CD8 T cell infiltration and PD-L1 expression, as well as increased TIS score in the majority of patients treated with RP2 alone or RP1 and nivolumab combination. Particularly marked effects were seen in some patients with clinical responses which occurred independent of both baseline PD-L1 and prior anti-PD1 therapy status, which suggests potential broad utility of the RP1/2 treatment approach in igniting an anti-tumor immune response. Tumor mutation burden analysis and T cell receptor sequencing are currently underway and further updates of the dataset will be presented. Citation Format: Kevin J. Harrington, Francesca Aroldi, Joseph J. Sacco, Mohammed M. Milhem, Brendan D. Curti, Ari M. Vanderwalde, Scott Baum, Adel Samson, Anna C. Pavlick, Jason A. Chesney, Jiaxin Niu, Terence D. Rhodes, Tawnya L. Bowles, Robert Conry, Anna Olsson-Brown, Douglas E. Laux, Pablo Nenclares, Lavita Menezes, Alex Deterding, Victoria Roulstone, Joan Kyula, Suzanne Thomas, Praveen K. Bommareddy, Selda Samakoglu, Andrea Pirzkall, Robert S. Coffin, Mark R. Middleton. Clinical biomarker studies with two fusion-enhanced versions of oncolytic HSV (RP1 and RP2) alone and in combination with nivolumab in cancer patients indicate potent immune activation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB180.

Potential Prospect of CDK4/6 Inhibitors in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is an aggressive, difficult-to-treat subtype of cancer with a poor prognosis; there is an urgent need for effective, targeted molecular therapies. The cyclin D/cyclin-dependent kinase (CDK)4/6–retinoblastoma protein (Rb) pathway plays a critical role in regulating cell cycle checkpoints, a process which is often disrupted in cancer cells. Selective CDK4/6 inhibitors can prevent retinoblastoma protein phosphorylation by invoking cell cycle arrest in the first growth phase (G1), and may therefore represent an effective treatment option. In this article, we review the molecular mechanisms and therapeutic efficacy of CDK4/6 inhibitors in combination with other targeted therapies for the treatment of triple-negative breast cancer. Three selective CDK4/6 inhibitors have so far received the approval of the Food and Drug Administration (FDA) for patients with estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2) breast cancer. Trilaciclib, a small molecule short-acting inhibitor of CDK4/6, has also been approved recently for people with small cell lung cancer, and is also expected to be clinically effective against breast cancer. Although the efficacy of CDK4/6 inhibitors in patients with triple-negative breast cancer remains uncertain, their use in conjunction with other targeted therapies may improve outcomes and is therefore currently being explored. Identifying biomarkers for response or resistance to CDK4/6 inhibitor treatment may optimize the personalization of treatment strategies for this disease. Ongoing and future clinical trials and biomarker studies will shed further light on these topics, and help to realize the full potential of CDK4/6 inhibitor treatment in triple-negative breast cancer.

Differences in levels of phosphatidylinositols in healthy and stable Coronary Artery Disease subjects revealed by HILIC-MRM method with SERRF normalization.

Quantification of endogenous biomarkers in clinical studies requires careful evaluation of a number of assay performance parameters. Comparisons of absolute values from several clinical studies can enable retrospective analyses further elucidating the biology of a given biomarker across various study populations. We characterized the performance of a highly multiplex bioanalytical method for quantification of phosphatidylinositols (PI). Hydrophilic interaction chromatography (HILIC) and multiple reaction monitoring (MRM) were employed for targeted multiplex quantification. Odd-chain PI species that are not normally present in human plasma were utilized as surrogate analytes (SA) to assess various assay performance parameters and establish a definitive dynamic linear range for PI lipids. To correct for batch effects, Systematic Error Removal using Random Forest (SERRF) normalization algorithm was employed and used to bridge raw values between two clinical studies, enabling quantitative comparison of their absolute values. A high throughput method was developed, qualified, transferred to an automation platform and applied to sample testing in two clinical trials in healthy volunteers (NCT03001297) and stable Coronary Artery Disease (CAD, NCT03351738) subjects. The method demonstrated acceptable precision and accuracy (±30%) over linear range of 1–1000 nM for SA and 8-fold dilutional linearity for endogenous PI. We determined that mean-adjusted average QC performed best for normalization using SERRF. The comparison of two studies revealed that healthy subject levels of PI are consistently higher across PI species compared to CAD subjects identifying a potential lipid biomarker to be explored in future studies.

Proteomic signatures predict preeclampsia in individual cohorts but not across cohorts – implications for clinical biomarker studies

Background Early identification of pregnant women at risk for preeclampsia (PE) is important, as it will enable targeted interventions ahead of clinical manifestations. The quantitative analyses of plasma proteins feature prominently among molecular approaches used for risk prediction. However, derivation of protein signatures of sufficient predictive power has been challenging. The recent availability of platforms simultaneously assessing over 1000 plasma proteins offers broad examinations of the plasma proteome, which may enable the extraction of proteomic signatures with improved prognostic performance in prenatal care. Objective The primary aim of this study was to examine the generalizability of proteomic signatures predictive of PE in two cohorts of pregnant women whose plasma proteome was interrogated with the same highly multiplexed platform. Establishing generalizability, or lack thereof, is critical to devise strategies facilitating the development of clinically useful predictive tests. A second aim was to examine the generalizability of protein signatures predictive of gestational age (GA) in uncomplicated pregnancies in the same cohorts to contrast physiological and pathological pregnancy outcomes. Study design Serial blood samples were collected during the first, second, and third trimesters in 18 women who developed PE and 18 women with uncomplicated pregnancies (Stanford cohort). The second cohort (Detroit), used for comparative analysis, consisted of 76 women with PE and 90 women with uncomplicated pregnancies. Multivariate analyses were applied to infer predictive and cohort-specific proteomic models, which were then tested in the alternate cohort. Gene ontology (GO) analysis was performed to identify biological processes that were over-represented among top-ranked proteins associated with PE. Results The model derived in the Stanford cohort was highly significant (p = 3.9E–15) and predictive (AUC = 0.96), but failed validation in the Detroit cohort (p = 9.7E–01, AUC = 0.50). Similarly, the model derived in the Detroit cohort was highly significant (p = 1.0E–21, AUC = 0.73), but failed validation in the Stanford cohort (p = 7.3E–02, AUC = 0.60). By contrast, proteomic models predicting GA were readily validated across the Stanford (p = 1.1E–454, R = 0.92) and Detroit cohorts (p = 1.1.E–92, R = 0.92) indicating that the proteomic assay performed well enough to infer a generalizable model across studied cohorts, which makes it less likely that technical aspects of the assay, including batch effects, accounted for observed differences. Conclusions Results point to a broader issue relevant for proteomic and other omic discovery studies in patient cohorts suffering from a clinical syndrome, such as PE, driven by heterogeneous pathophysiologies. While novel technologies including highly multiplex proteomic arrays and adapted computational algorithms allow for novel discoveries for a particular study cohort, they may not readily generalize across cohorts. A likely reason is that the prevalence of pathophysiologic processes leading up to the “same” clinical syndrome can be distributed differently in different and smaller-sized cohorts. Signatures derived in individual cohorts may simply capture different facets of the spectrum of pathophysiologic processes driving a syndrome. Our findings have important implications for the design of omic studies of a syndrome like PE. They highlight the need for performing such studies in diverse and well-phenotyped patient populations that are large enough to characterize subsets of patients with shared pathophysiologies to then derive subset-specific signatures of sufficient predictive power.

A quantitative LC-MS/MS approach for monitoring 2'-fluoro-2'-deoxy-D-glucose uptake in tumor tissue.

Purpose: Develop a quantitative LC-MS/MS method for FDG, FDG-monophosphate, glucose and glucose-monophosphate in mouse tumor models to assist in validating the use of [18F]FDG-positron emission tomography (PET) imaging for anticancer therapies in a clinical setting. Methodology/results: Analytes were isolated from tumors by protein precipitation and detected on a Sciex API-5500 mass spectrometer. Improved assay robustness and selectivity were achieved through chromatographic separation of FDG-monophosphate from glucose-monophosphate, selection of a unique ion transition and incorporation of stable isotope labeled internal standards. In a mouse JIMT-1 tumor model, FDG-monophosphate levels measured by LC-MS/MS correlated with [18F]FDG-PET imaging results. Conclusion: LC-MS/MS analysis of FDG-monophosphate accumulation in tumors is a cost-effective tool to gauge the translational potential of [18F]FDG-PET imaging as a noninvasive biomarker in clinical studies.