Improved detection of prostate cancer using a magneto-nanosensor assay for serum circulating autoantibodies

Metabolic Disturbances in a Mouse Model of MPTP/Probenecid-Induced Parkinson's Disease: Evaluation Using Liquid Chromatography-Mass Spectrometry

Purpose

Parkinson's disease (PD) is a common neurodegenerative disease that severely affects patients' daily lives and places a significant burden on the global economy. There are currently no specific biomarkers for distinguishing between the different stages of PD.

Methods

We divided 78 mice into six equal groups, including five model PD groups (W1-W5; based on the PD stage induced by length of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine/propofol induction time) and a control group. Then, we used metabolomics technology to detect the serum small-molecule metabolites present in each group. Ultimately, we screened for potential biomarkers using the variable importance in the projection of the orthogonal partial least squares discriminant analysis and the coefficient value of LASSO ordinal logistic regression.

Results

We identified 12 potential biomarkers, including dehydroepiandrosterone sulfate, pipecolic acid, N-acetylleucine, 2-aminoadipic acid, L-tyrosine, uric acid, and 5-hydroxyindoleacetaldehyde. Pathway analysis revealed their involvement in amino acid metabolism, caffeine metabolism, steroid hormone biosynthesis, and purine metabolism. Additionally, the receiver operating characteristic curve indicated that a biomarker panel comprising the 12 biomarkers could differentiate between the different PD stages.

Conclusion

Different PD stages are characterized by different metabolites. The biomarkers identified in this study are helpful to understand the PD process.

Autoantibodies in cancer: a systematic review of their clinical role in the most prevalent cancers

Although blood autoantibodies were initially associated with autoimmune diseases, multiple evidence have been accumulated showing their presence in many types of cancer. This has opened their use in clinics, since cancer autoantibodies might be useful for early detection, prognosis, and monitoring of cancer patients. In this review, we discuss the different techniques available for their discovery and validation. Additionally, we discuss here in detail those autoantibody panels verified in at least two different reports that should be more likely to be specific of each of the four most incident cancers. We also report the recent developed kits for breast and lung cancer detection mostly based on autoantibodies and the identification of novel therapeutic targets because of the screening of the cancer humoral immune response. Finally, we discuss unsolved issues that still need to be addressed for the implementation of cancer autoantibodies in clinical routine for cancer diagnosis, prognosis, and/or monitoring.

Upregulation of CALD1 predicted a poor prognosis for platinum-treated ovarian cancer and revealed it as a potential therapeutic resistance target

BACKGROUND

Ovarian cancer (OC) has the worst prognosis among gynecological malignancies, most of which are found to be in advanced stage. Cell reduction surgery based on platinum-based chemotherapy is the current standard of treatment for OC, but patients are prone to relapse and develop drug resistance. The objective of this study was to identify a specific molecular target responsible for platinum chemotherapy resistance in OC.

RESULTS

We screened the protein-coding gene Caldesmon (CALD1), expressed in cisplatin-resistant OC cells in vitro. The prognostic value of CALD1 was evaluated using survival curve analysis in OC patients treated with platinum therapy. The diagnostic value of CALD1 was verified by drawing a Receiver Operating Characteristic (ROC) curve using clinical samples from OC patients. This study analyzed data from various databases including Gene Expression Omnibus (GEO), Human Protein Atlas (HPA), The Cancer Cell Line Encyclopedia (CCLE), The Cancer Genome Atlas (TCGA), GEPIA 2, UALCAN, Kaplan-Meier (KM) plotter, LinkedOmics database, and String. Different expression genes (DEGs) between cisplatin-sensitive and cisplatin-resistant cells were acquired respectively from 5 different datasets of GEO. CALD1 was selected as a common gene from 5 groups DEGs. Online data analysis of HPA and CCLE showed that CALD1 was highly expressed in both normal ovarian tissue and OC. In TCGA database, high expression of CALD1 was associated with disease stage and venous invasion in OC. Patients with high CALD1 expression levels had a worse prognosis under platinum drug intervention, according to Kaplan-Meier (KM) plotter analysis. Analysis of clinical sample data from GEO showed that CALD1 had superior diagnostic value in distinguishing patients with platinum "resistant" and platinum "sensitive" (AUC = 0.816), as well as patients with worse progression-free survival (AUC = 0.741), and those with primary and omental metastases (AUC = 0.811) in ovarian tumor. At last, CYR61 was identified as a potential predictive molecule that may play an important role alongside CALD1 in the development of platinum resistance in OC.

CONCLUSIONS

CALD1, as a member of cytoskeletal protein, was associated with poor prognosis of platinum resistance in OC, and could be used as a target protein for mechanism study of platinum resistance in OC.

Giant Magnetoresistance Based Biosensors for Cancer Screening and Detection

Early-stage screening of cancer is critical in preventing its development and therefore can improve the prognosis of the disease. One accurate and effective method of cancer screening is using high sensitivity biosensors to detect optically, chemically, or magnetically labeled cancer biomarkers. Among a wide range of biosensors, giant magnetoresistance (GMR) based devices offer high sensitivity, low background noise, robustness, and low cost. With state-of-the-art micro- and nanofabrication techniques, tens to hundreds of independently working GMR biosensors can be integrated into fingernail-sized chips for the simultaneous detection of multiple cancer biomarkers (i.e., multiplexed assay). Meanwhile, the miniaturization of GMR chips makes them able to be integrated into point-of-care (POC) devices. In this review, we first introduce three types of GMR biosensors in terms of their structures and physics, followed by a discussion on fabrication techniques for those sensors. In order to achieve target cancer biomarker detection, the GMR biosensor surface needs to be subjected to biological decoration. Thus, commonly used methods for surface functionalization are also reviewed. The robustness of GMR-based biosensors in cancer detection has been demonstrated by multiple research groups worldwide and we review some representative examples. At the end of this review, the challenges and future development prospects of GMR biosensor platforms are commented on. With all their benefits and opportunities, it can be foreseen that GMR biosensor platforms will transition from a promising candidate to a robust product for cancer screening in the near future.

Magnetic supercluster particles for highly sensitive magnetic biosensing of proteins

A strategy is reported to improve the detection limits of current giant magnetoresistance (GMR) biosensors by augmenting the effective magnetic moment that the magnetic tags on the biosensors can exert. Magnetic supercluster particles (MSPs), each of which consists of ~ 1000 superparamagnetic cores, are prepared by a wet-chemical technique and are utilized to improve the limit of detection of GMR biosensors down to 17.6 zmol for biotin as a target molecule. This value is more than four orders of magnitude lower than that of the conventional colorimetric assay performed using the same set of reagents except for the signal transducer. The applicability of MSPs in immunoassay is further demonstrated by simultaneously detecting vascular endothelial growth factor (VEGF) and C-reactive protein (CRP) in a duplex assay format. MSPs outperform commercially available magnetic nanoparticles in terms of signal intensity and detection limit.

Hidden in Plants-A Review of the Anticancer Potential of the Solanaceae Family in In Vitro and In Vivo Studies

Many of the anticancer agents that are currently in use demonstrate severe side effects and encounter increasing resistance from the target cancer cells. Thus, despite significant advances in cancer therapy in recent decades, there is still a need to discover and develop new, alternative anticancer agents. The plant kingdom contains a range of phytochemicals that play important roles in the prevention and treatment of many diseases. The Solanaceae family is widely used in the treatment of various diseases, including cancer, due to its bioactive ingredient content. The purpose of this literature review is to highlight the antitumour activity of Solanaceae extracts-single isolated compounds and nanoparticles with extracts-and their synergistic effect with chemotherapeutic agents in various in vitro and in vivo cancer models. In addition, the biological properties of many plants of the Solanaceae family have not yet been investigated, which represents a challenge and an opportunity for future anticancer therapy.

Retinal Degeneration: A Window to Understand the Origin and Progression of Parkinson’s Disease?

Parkinson’s disease (PD), the second most prevalent neurodegenerative disorder, manifests with motor and non-motor symptoms associated with two main pathological hallmarks, including the deterioration of dopaminergic cells and aggregation of alpha-synuclein. Yet, PD is a neurodegenerative process whose origin is uncertain and progression difficult to monitor and predict. Currently, a possibility is that PD may be secondary to long lasting peripheral affectations. In this regard, it has been shown that retinal degeneration is present in PD patients. Although it is unknown if retinal degeneration precedes PD motor symptoms, the possibility exists since degeneration of peripheral organs (e.g., olfaction, gut) have already been proven to antedate PD motor symptoms. In this paper, we explore this possibility by introducing the anatomical and functional relationship of retina and brain and providing an overview of the physiopathological changes of retinal structure and visual function in PD. On the basis of the current status of visual deficits in individuals with PD, we discuss the modalities and pathological mechanism of visual function or morphological changes in the retina and focus on the correlation between visual impairment and some representative structural features with clinical significance. To consider retinal degeneration as a contributor to PD origin and progress is important because PD evolution may be monitored and predicted by retinal studies through state-of-the-art techniques of the retina. It is significant to integrally understand the role of retinal morphological and functional changes in the neurodegenerative process for the diagnosis and therapeutic strategies of PD.

The Regulatory Role of RNA Metabolism Regulator TDP-43 in Human Cancer

TAR-DNA-binding protein-43 (TDP-43) is a member of hnRNP family and acts as both RNA and DNA binding regulator, mediating RNA metabolism and transcription regulation in various diseases. Currently, emerging evidence gradually elucidates the crucial role of TDP-43 in human cancers like it is previously widely researched in neurodegeneration diseases. A series of RNA metabolism events, including mRNA alternative splicing, transport, stability, miRNA processing, and ncRNA regulation, are all confirmed to be closely involved in various carcinogenesis and tumor progressions, which are all partially regulated and interacted by TDP-43. Herein we conducted the first overall review about TDP-43 and cancers to systematically summarize the function and precise mechanism of TDP-43 in different human cancers. We hope it would provide basic knowledge and concepts for tumor target therapy and biomarker diagnosis in the future.

A Master Autoantigen-ome Links Alternative Splicing, Female Predilection, and COVID-19 to Autoimmune Diseases

Chronic and debilitating autoimmune sequelae pose a grave concern for the post-COVID-19 pandemic era. Based on our discovery that the glycosaminoglycan dermatan sulfate (DS) displays peculiar affinity to apoptotic cells and autoantigens (autoAgs) and that DS-autoAg complexes cooperatively stimulate autoreactive B1 cell responses, we compiled a database of 751 candidate autoAgs from six human cell types. At least 657 of these have been found to be affected by SARS-CoV-2 infection based on currently available multi-omic COVID data, and at least 400 are confirmed targets of autoantibodies in a wide array of autoimmune diseases and cancer. The autoantigen-ome is significantly associated with various processes in viral infections, such as translation, protein processing, and vesicle transport. Interestingly, the coding genes of autoAgs predominantly contain multiple exons with many possible alternative splicing variants, short transcripts, and short UTR lengths. These observations and the finding that numerous autoAgs involved in RNA-splicing showed altered expression in viral infections suggest that viruses exploit alternative splicing to reprogram host cell machinery to ensure viral replication and survival. While each cell type gives rise to a unique pool of autoAgs, 39 common autoAgs associated with cell stress and apoptosis were identified from all six cell types, with several being known markers of systemic autoimmune diseases. In particular, the common autoAg UBA1 that catalyzes the first step in ubiquitination is encoded by an X-chromosome escape gene. Given its essential function in apoptotic cell clearance and that X-inactivation escape tends to increase with aging, UBA1 dysfunction can therefore predispose aging women to autoimmune disorders. In summary, we propose a model of how viral infections lead to extensive molecular alterations and host cell death, autoimmune responses facilitated by autoAg-DS complexes, and ultimately autoimmune diseases. Overall, this master autoantigen-ome provides a molecular guide for investigating the myriad of autoimmune sequalae to COVID-19 and clues to the rare but reported adverse effects of the currently available COVID vaccines.

Chromatin-directed proteomics-identified network of endogenous androgen receptor in prostate cancer cells

Treatment of prostate cancer confronts resistance to androgen receptor (AR)-targeted therapies. AR-associated coregulators and chromatin proteins hold a great potential for novel therapy targets. Here, we employed a powerful chromatin-directed proteomics approach termed ChIP-SICAP to uncover the composition of chromatin protein network, the chromatome, around endogenous AR in castration resistant prostate cancer (CRPC) cells. In addition to several expected AR coregulators, the chromatome contained many nuclear proteins not previously associated with the AR. In the context of androgen signaling in CRPC cells, we further investigated the role of a known AR-associated protein, a chromatin remodeler SMARCA4 and that of SIM2, a transcription factor without a previous association with AR. To understand their role in chromatin accessibility and AR target gene expression, we integrated data from ChIP-seq, RNA-seq, ATAC-seq and functional experiments. Despite the wide co-occurrence of SMARCA4 and AR on chromatin, depletion of SMARCA4 influenced chromatin accessibility and expression of a restricted set of AR target genes, especially those involved in cell morphogenetic changes in epithelial-mesenchymal transition. The depletion also inhibited the CRPC cell growth, validating SMARCA4's functional role in CRPC cells. Although silencing of SIM2 reduced chromatin accessibility similarly, it affected the expression of a much larger group of androgen-regulated genes, including those involved in cellular responses to external stimuli and steroid hormone stimulus. The silencing also reduced proliferation of CRPC cells and tumor size in chick embryo chorioallantoic membrane assay, further emphasizing the importance of SIM2 in CRPC cells and pointing to the functional relevance of this potential prostate cancer biomarker in CRPC cells. Overall, the chromatome of AR identified in this work is an important resource for the field focusing on this important drug target.

Identification and Validation of a Prognostic 5-Protein Signature for Biochemical Recurrence Following Radical Prostatectomy for Prostate Cancer

Background: Biochemical recurrence (BCR) is an indicator of prostate cancer (PCa)-specific recurrence and mortality. However, there is a lack of an effective prediction model that can be used to predict prognosis and to determine the optimal method of treatment for patients with BCR. Hence, the aim of this study was to construct a protein-based nomogram that could predict BCR in PCa. Methods: Protein expression data of PCa patients was obtained from The Cancer Proteome Atlas (TCPA) database. Clinical data on the patients was downloaded from The Cancer Genome Atlas (TCGA) database. Lasso and Cox regression analyses were conducted to select the most significant prognostic proteins and formulate a protein signature that could predict BCR. Subsequently, Kaplan-Meier survival analysis and Cox regression analyses were conducted to evaluate the performance of the prognostic protein-based signature. Additionally, a nomogram was constructed using multivariate Cox regression analysis. Results: We constructed a 5-protein-based prognostic prediction signature that could be used to identify high-risk and low-risk groups of PCa patients. The survival analysis demonstrated that patients with a higher BCR showed significantly worse survival than those with a lower BCR (p < 0.0001). The time-dependent receiver operating characteristic curve showed that the signature had an excellent prognostic efficiency for 1, 3, and 5-year BCR (area under curve in training set: 0.691, 0.797, 0.808 and 0.74, 0.739, 0.82 in the test set). Univariate and multivariate analyses indicated that this 5-protein signature could be used as independent prognosis marker for PCa patients. Moreover, the concordance index (C-index) confirmed the predictive value of this 5-protein signature in 3, 5, and 10-year BCR overall survival (C-index: 0.764, 95% confidence interval: 0.701-0.827). Finally, we constructed a nomogram to predict BCR of PCa. Conclusions: Our study identified a 5-protein-based signature and constructed a nomogram that could reliably predict BCR. The findings might be of paramount importance for the prediction of PCa prognosis and medical decision-making. Subjects: Bioinformatics, oncology, urology.

Advances of Mechanisms-Related Metabolomics in Parkinson's Disease

Parkinson's disease (PD) is a multifactorial disorder characterized by progressively debilitating dopaminergic neurodegeneration in the substantia nigra and the striatum, along with various metabolic dysfunctions and molecular abnormalities. Metabolomics is an emerging study and has been demonstrated to play important roles in describing complex human diseases by integrating endogenous and exogenous sources of alterations. Recently, an increasing amount of research has shown that metabolomics profiling holds great promise in providing unique insights into molecular pathogenesis and could be helpful in identifying candidate biomarkers for clinical detection and therapies of PD. In this review, we briefly summarize recent findings and analyze the application of molecular metabolomics in familial and sporadic PD from genetic mutations, mitochondrial dysfunction, and dysbacteriosis. We also review metabolic biomarkers to assess the functional stage and improve therapeutic strategies to postpone or hinder the disease progression.

Cyclic Peptide Mimotopes for the Detection of Serum Anti-ATIC Autoantibody Biomarker in Hepato-Cellular Carcinoma

Tumor-associated (TA) autoantibodies have been identified at the early tumor stage before developing clinical symptoms, which holds hope for early cancer diagnosis. We identified a TA autoantibody from HBx-transgenic (HBx-tg) hepatocellular carcinoma (HCC) model mouse, characterized its target antigen, and examined its relationship to human HCC. The mimotopes corresponding to the antigenic epitope of TA autoantibody were screened from a random cyclic peptide library and used for the detection of serum TA autoantibody. The target antigen of the TA autoantibody was identified as an oncogenic bi-functional purine biosynthesis protein, ATIC. It was upregulated in liver cancer tissues of HBx-tg mouse as well as human HCC tissues. Over-expressed ATIC was also secreted extracellularly via the cancer-derived exosomes, which might cause auto-immune responses. The cyclic peptide mimotope with a high affinity to anti-ATIC autoantibody, CLPSWFHRC, distinguishes between serum samples from HCC patients and healthy subjects with 70.83% sensitivity, 90.68% specificity (AUC = 0.87). However, the recombinant human ATIC protein showed a low affinity to anti-ATIC autoantibody, which may be incompatible as a capture antigen for serum TA autoantibody. This study indicates that anti-ATIC autoantibody can be a potential HCC-associated serum biomarker and suggests that autoantibody biomarker's efficiency can be improved by using antigenic mimicry to native antigens present in vivo.

Nanotreatment and Nanodiagnosis of Prostate Cancer: Recent Updates

The fabrication and development of nanomaterials for the treatment of prostate cancer have gained significant appraisal in recent years. Advancements in synthesis of organic and inorganic nanomaterials with charge, particle size, specified geometry, ligand attachment etc have resulted in greater biocompatibility and active targeting at cancer site. Despite all of the advances made over the years in discovering drugs, methods, and new biomarkers for cancer of the prostate (PCa), PCa remains one of the most troubling cancers among people. Early on, effective diagnosis is an essential part of treating prostate cancer. Prostate-specific antigen (PSA) or serum prostate-specific antigen is the best serum marker widely accessible for diagnosis of PCa. Numerous efforts have been made over the past decade to design new biosensor-based strategies for biomolecules detection and PSA miniaturization biomarkers. The growing nanotechnology is expected to have a significant effect in the immediate future on scientific research and healthcare. Nanotechnology is thus predicted to find a way to solve one of the most and long-standing problem, "early cancer detection". For early diagnosis of PCa biomarkers, different nanoparticles with different approaches have been used. In this review, we provide a brief description of the latest achievements and advances in the use of nanoparticles for PCa biomarker diagnosis.

The paradox of cancer genes in non-malignant conditions: implications for precision medicine

Next-generation sequencing has enabled patient selection for targeted drugs, some of which have shown remarkable efficacy in cancers that have the cognate molecular signatures. Intriguingly, rapidly emerging data indicate that altered genes representing oncogenic drivers can also be found in sporadic non-malignant conditions, some of which have negligible and/or low potential for transformation to cancer. For instance, activating KRAS mutations are discerned in endometriosis and in brain arteriovenous malformations, inactivating TP53 tumor suppressor mutations in rheumatoid arthritis synovium, and AKT, MAPK, and AMPK pathway gene alterations in the brains of Alzheimer's disease patients. Furthermore, these types of alterations may also characterize hereditary conditions that result in diverse disabilities and that are associated with a range of lifetime susceptibility to the development of cancer, varying from near universal to no elevated risk. Very recently, the repurposing of targeted cancer drugs for non-malignant conditions that are associated with these genomic alterations has yielded therapeutic successes. For instance, the phenotypic manifestations of CLOVES syndrome, which is characterized by tissue overgrowth and complex vascular anomalies that result from the activation of PIK3CA mutations, can be ameliorated by the PIK3CA inhibitor alpelisib, which was developed and approved for breast cancer. In this review, we discuss the profound implications of finding molecular alterations in non-malignant conditions that are indistinguishable from those driving cancers, with respect to our understanding of the genomic basis of medicine, the potential confounding effects in early cancer detection that relies on sensitive blood tests for oncogenic mutations, and the possibility of reverse repurposing drugs that are used in oncology in order to ameliorate non-malignant illnesses and/or to prevent the emergence of cancer.