Cardiorenal Syndrome: New Pathways and Novel Biomarkers

Cardiorenal syndrome (CRS) is a multi-organ disease characterized by the complex interaction between heart and kidney during acute or chronic injury. The pathogenesis of CRS involves metabolic, hemodynamic, neurohormonal, and inflammatory mechanisms, and atherosclerotic degeneration. In the process of better understanding the bi-directional pathophysiological aspects of CRS, the need to find precise and easy-to-use markers has also evolved. Based on the new pathophysiological standpoints and an overall vision of the CRS, the literature on renal, cardiac, metabolic, oxidative, and vascular circulating biomarkers was evaluated. Though the effectiveness of different extensively applied biomarkers remains controversial, evidence for several indicators, particularly when combined, has increased in recent years. From new aspects of classic biomarkers to microRNAs, this review aimed at a 360-degree analysis of the pathways that balance the kidney and the heart physiologies. In this delicate system, different markers and their combination can shed light on the diagnosis, risk, and prognosis of CRS.

Proteome profiling of formalin-fixed, paraffin-embedded lung adenocarcinoma tissues using a tandem mass tag-based quantitative proteomics approach

Over the past few decades, increasing efforts have been made to improve the understanding of, and treatment options for, lung adenocarcinoma (LUAD). However, considering the heterogeneity of LUAD, precise proteomics-based characterization at the molecular level is an urgent clinical requirement for effective treatment. Formalin-fixed, paraffin-embedded (FFPE) tissue is a good option as the working tool for proteomics studies. The present study aimed to obtain a global protein profile using LUAD FFPE tissue samples. Using a quantitative proteomics approach, the study revealed that 360 proteins were significantly more highly expressed in LUAD than in adjacent nontumor lung tissues. Also, 19 differentially expressed membrane proteins were found to be primarily responsible for immune processes. Epidermal growth factor (EGF)-like domain and laminin EGF domain showed markedly different expression levels between cancer tissues and tumor-adjacent normal tissues. Furthermore, Gene Ontology functional enrichment analysis showed that significantly upregulated proteins were associated with the endoplasmic reticulum lumen, protein disulfide isomerase activity, vitamin binding, cell cycle G₁/S phase transition, to name but a few. Also, numerous kinases and post-translational modification enzymes were significantly upregulated across all eight LUAD samples compared with paracarcinoma tissues. Proteomics analysis revealed that AAA domain containing 3A (ATAD3a), a member of the ATPase family, was highly expressed in LUAD tissues, which was supported by immunohistochemical analysis. Furthermore, the study confirmed that ATAD3a enhanced the cisplatin sensitivity of LUAD cells. Collectively, the findings of the present study provide new potential candidate targets in patients with LUAD, and may aid auxiliary LUAD diagnosis and surveillance in a noninvasive manner.

Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is the metabolic disorder that appears during pregnancy. The current investigation aimed to identify central differentially expressed genes (DEGs) in GDM. The transcription profiling by array data (E-MTAB-6418) was obtained from the ArrayExpress database. The DEGs between GDM samples and non-GDM samples were analyzed. Functional enrichment analysis were performed using ToppGene. Then we constructed the protein–protein interaction (PPI) network of DEGs by the Search Tool for the Retrieval of Interacting Genes database (STRING) and module analysis was performed. Subsequently, we constructed the miRNA–hub gene network and TF–hub gene regulatory network. The validation of hub genes was performed through receiver operating characteristic curve (ROC). Finally, the candidate small molecules as potential drugs to treat GDM were predicted by using molecular docking. Through transcription profiling by array data, a total of 869 DEGs were detected including 439 up-regulated and 430 down-regulated genes. Functional enrichment analysis showed these DEGs were mainly enriched in reproduction, cell adhesion, cell surface interactions at the vascular wall and extracellular matrix organization. Ten genes, HSP90AA1, EGFR, RPS13, RBX1, PAK1, FYN, ABL1, SMAD3, STAT3 and PRKCA were associated with GDM, according to ROC analysis. Finally, the most significant small molecules were predicted based on molecular docking. This investigation identified hub genes, signal pathways and therapeutic agents, which might help us, enhance our understanding of the mechanisms of GDM and find some novel therapeutic agents for GDM.

Endothelial Dysfunction, Inflammation and Coronary Artery Disease: Potential Biomarkers and Promising Therapeutical Approaches

Coronary artery disease (CAD) and its complications are the leading cause of death worldwide. Inflammatory activation and dysfunction of the endothelium are key events in the development and pathophysiology of atherosclerosis and are associated with an elevated risk of cardiovascular events. There is great interest to further understand the pathophysiologic mechanisms underlying endothelial dysfunction and atherosclerosis progression, and to identify novel biomarkers and therapeutic strategies to prevent endothelial dysfunction, atherosclerosis and to reduce the risk of developing CAD and its complications. The use of liquid biopsies and new molecular biology techniques have allowed the identification of a growing list of molecular and cellular markers of endothelial dysfunction, which have provided insight on the molecular basis of atherosclerosis and are potential biomarkers and therapeutic targets for the prevention and or treatment of atherosclerosis and CAD. This review describes recent information on normal vascular endothelium function, as well as traditional and novel potential biomarkers of endothelial dysfunction and inflammation, and pharmacological and non-pharmacological therapeutic strategies aimed to protect the endothelium or reverse endothelial damage, as a preventive treatment for CAD and related complications.

Advanced Approaches to Breast Cancer Classification and Diagnosis

The International Agency for Research on Cancer (IARC) has recently reported a 66% increase in the global number of cancer deaths since 1960. In the US alone, about one in eight women is expected to develop invasive breast cancer(s) (breast cancer) at some point in their lifetime. Traditionally, a BC diagnosis includes mammography, ultrasound, and some high-end molecular bioimaging. Unfortunately, these techniques detect BC at a later stage. So early and advanced molecular diagnostic tools are still in demand. In the past decade, various histological and immuno-molecular studies have demonstrated that BC is highly heterogeneous in nature. Its growth pattern, cytological features, and expression of key biomarkers in BC cells including hormonal receptor markers can be utilized to develop advanced diagnostic and therapeutic tools. A cancer cell's progression to malignancy exhibits various vital biomarkers, many of which are still underrepresented in BC diagnosis and treatment. Advances in genetics have also enabled the development of multigene assays to detect genetic heterogeneity in BC. However, thus far, the FDA has approved only four such biomarkers-cancer antigens (CA); CA 15-3, CA 27-29, Human epidermal growth factor receptor 2 (HER2), and circulating tumor cells (CTC) in assessing BC in body fluids. An adequately structured portable-biosensor with its non-invasive and inexpensive point-of-care analysis can quickly detect such biomarkers without significantly compromising its specificity and selectivity. Such advanced techniques are likely to discriminate between BC and a healthy patient by accurately measuring the cell shape, structure, depth, intracellular and extracellular environment, and lipid membrane compositions. Presently, BC treatments include surgery and systemic chemo- and targeted radiation therapy. A biopsied sample is then subjected to various multigene assays to predict the heterogeneity and recurrence score, thus guiding a specific treatment by providing complete information on the BC subtype involved. Thus far, we have seven prognostic multigene signature tests for BC providing a risk profile that can avoid unnecessary treatments in low-risk patients. Many comparative studies on multigene analysis projected the importance of integrating clinicopathological information with genomic-imprint analysis. Current cohort studies such as MINDACT, TAILORx, Trans-aTTOM, and many more, are likely to provide positive impact on long-term patient outcome. This review offers consolidated information on currently available BC diagnosis and treatment options. It further describes advanced biomarkers for the development of state-of-the-art early screening and diagnostic technologies.

Identification of novel biomarkers and candidate small-molecule drugs in cutaneous melanoma by comprehensive gene microarrays analysis

Background: Melanoma is a pernicious skin cancer with high aggressiveness. This study aimed to identify potential novel biomarkers associated with the prognosis and pathogenesis of cutaneous melanoma and to explore new targeted drugs for melanoma. Methods: Two Gene Expression Omnibus (GEO) microarray datasets, GSE3189 and GSE7553 were combined to analyze the differentially expressed genes (DEGs). To better understand the DEGs in the melanoma pathogenesis, we performed gene enrichment analyses and established a protein-protein interaction network (PPI). The survival analyses for key genes were conducted based on the GEPIA platform. Finally, we mined the CMap database to explore potential small-molecule drugs to target the obtained DEGs. Results: In short, we identified 500 DEGs between cutaneous melanoma samples and normal samples. The PPI network was established with 349 nodes and 1251 edges. Signaling pathway analysis showed that these genes play a vital role in ECM-receptor interactions, the PPAR signaling pathway and pathways in cancer. Eight DEGs with a relatively high degree of connectivity (CDC45, CENPF, DTL, FANCI, GINS2, HJURP, TPX2 and TRIP13) were selected as hub-genes that remarkably correlated to a poor survival rate. Based on 500 DEGs, 20 small-molecule drugs that potentially target genes with abnormal expression in cutaneous melanoma were obtained from the CMap database. Among these compounds, we found that menadione has the greatest therapeutic value for melanoma. Conclusions: In conclusion, we identified the 8 candidate biomarkers and potential key signaling pathways in cutaneous melanoma through comprehensive microarray analyses. The identified candidate drugs have provided several directive significances for the synthesis medicine for melanoma.

Update of early phase clinical trials in cancer immunotherapy

Immunotherapy has revolutionized the landscape of cancer treatment and become a standard pillar of the treatment. The two main drivers, immune checkpoint inhibitors and chimeric antigen receptor T cells, contributed to this unprecedented success. However, despite the striking clinical improvements, most patients still suffer from disease progression because of the evolution of primary or acquired resistance. This mini-review summarizes new treatment options including novel targets and interesting combinational approaches to increase our understanding of the mechanisms of the action of and resistance to immunotherapy, to expand our knowledge of advances in biomarker and therapeutics development, and to help to find the most appropriate option or a way of overcoming the resistance for cancer patients. [BMB Reports 2021; 54(1): 70-88].

Relationship of Circulating Endothelial Cells With Obesity and Cardiometabolic Risk Factors in Children and Adolescents

Background Circulating endothelial cells (CECs) reflect early changes in endothelial health; however, the degree to which CEC number and activation is related to adiposity and cardiovascular risk factors in youth is not well described. Methods and Results Youth in this study (N=271; aged 8-20 years) were classified into normal weight (body mass index [BMI] percentage <85th; n=114), obesity (BMI percentage ≥95th to <120% of the 95th; n=63), and severe obesity (BMI percentage ≥120% of the 95th; n=94) catagories. CEC enumeration was determined using immunohistochemical examination of buffy coat smears and activated CEC (percentage of vascular cell adhesion molecule-1 expression) was assessed using immunofluorescent staining. Cardiovascular risk factors included measures of body composition, blood pressure, glucose, insulin, lipid profile, C-reactive protein, leptin, adiponectin, oxidized low-density lipoprotein cholesterol, carotid artery intima-media thickness, and pulse wave velocity. Linear regression models examined associations between CEC number and activation with BMI and cardiovascular risk factors. CEC number did not differ among BMI classes (P>0.05). Youth with severe obesity had a higher degree of CEC activation compared with normal weight youth (8.3%; 95% CI, 1.1-15.6 [P=0.024]). Higher CEC number was associated with greater body fat percentage (0.02 per percentage; 95% CI, 0.00-0.03 [P=0.020]) and systolic blood pressure percentile (0.01 per percentage; 95% CI, 0.00-0.01 [P=0.035]). Higher degree of CEC activation was associated with greater visceral adipose tissue (5.7% per kg; 95% CI, 0.4-10.9 [P=0.034]) and non-high-density lipoprotein cholesterol (0.11% per mg/dL; 95% CI, 0.01-0.21 [P=0.039]). Conclusions Methods of CEC quantification are associated with adiposity and cardiometabolic risk factors and may potentially reflect accelerated atherosclerosis as early as childhood.

The Utility of Novel Renal Biomarkers in Assessment of Chronic Kidney Disease of Unknown Etiology (CKDu): A Review

Chronic Kidney Disease (CKD) is a globally prevalent non-communicable disease with significant mortality and morbidity. It is typically associated with diabetes and hypertension; however, over the last two decades, an emergence of CKD of unknown etiology (CKDu) has claimed thousands of lives in several tropical agricultural communities. CKDu is associated with gradual loss of renal function without initial symptoms until reaching complete kidney failure and eventually death. The most impacted are young adult males of lower socio-economic strata. Since the disease progression can be successfully attenuated through early detection, the development of superior screening and management measures is of utmost importance. In contrast to the conventional biomarkers, novel biomarkers with improved sensitivity and specificity are being discussed as promising tools for early diagnosis of the disease. This review summarizes emerging novel biomarkers used in assessing CKD and discusses the current utility and diagnostic potential of such biomarkers for CKDu screening in clinical settings of different communities impacted by CKDu. Our goal is to provide a framework for practitioners in CKDu impacted regions to consider the use of these novel biomarkers through this synthesis. The increased use of these biomarkers will not only help to validate their diagnostic power further and establish potential prognostic value but may also provide critical insights into sites and mechanisms of renal damage.

Construction and Comprehensive Analysis of a ceRNA Network to Reveal Potential Novel Biomarkers for Triple-Negative Breast Cancer

Background

Triple-negative breast cancer (TNBC) is the most common and aggressive type of breast cancer with an unfavourable outcome worldwide. Novel therapeutic targets are urgently required to explore this malignancy. This study explored the ceRNA network and the important genes for predicting the therapeutic targets.

Methods

It identified the differentially expressed genes of mRNAs, lncRNAs and miRNAs between TNBC and non-TNBC samples in four cohorts (TCGA, GSE38959, GSE45827 and GSE65194) to explore the novel therapeutic targets for TNBC. Downstream analyses, including functional enrichment analysis, ceRNA network, protein–protein interaction and survival analysis, were then conducted by bioinformatics analysis. Finally, the potential core protein of the ceRNA network in TNBC was validated by immunohistochemistry.

Results

A total of 1,045 lncRNAs and 28 miRNAs were differentially expressed in the TCGA TNBC samples, and the intersections of 282 mRNAs (176 upregulations and 106 downregulations) between the GEO and TCGA databases were identified. A ceRNA network composed of 7 lncRNAs, 62 mRNAs, 12 miRNAs and 244 edges specific to TNBC was established. The functional assay showed dysregulated genes, and GO, DO and KEGG enrichment analysis were performed. Survival analysis showed that mRNA LIFR and lncRNA AC124312.3 were significantly correlated with the overall survival of patients with TNBC in the TCGA databases (P < 0.05). Finally, the LIFR protein was validated, and immunohistochemical results showed the upregulated expression of LIFR in TNBC tissues.

Conclusion

Thus, our study presents an enhanced understanding of the ceRNA network in TNBC, where the key gene LIFR may be a new promising potential therapeutic target for patients with TNBC.

Bioinformatics analysis of high-throughput data to validate potential novel biomarkers and small molecule drugs for glioblastoma multiforme

Objective

There have been no recent improvements in the glioblastoma multiforme (GBM) outcome, with median survival remaining 15 months. Consequently, the need to identify novel biomarkers for GBM diagnosis and prognosis, and to develop targeted therapies is high. This study aimed to establish biomarkers for GBM pathogenesis and prognosis.

Methods

In total, 220 overlapping differentially expressed genes (DEGs) were obtained by integrating four microarray datasets from the Gene Expression Omnibus database (GSE4290, GSE12657, GSE15824, and GSE68848). Then a 140-node protein–protein interaction network with 343 interactions was constructed.

Results

The immune response and cell adhesion molecules were the most significantly enriched functions and pathways, respectively, among DEGs. The designated hub genes ITGB5 and RGS4, which have a high degree of connectivity, were closely correlated with patient prognosis, and GEPIA database mining further confirmed their differential expression in GBM versus normal tissue. We also determined the 20 most appropriate small molecules that could potentially reverse GBM gene expression, Prestwick-1080 was the most promising and had the highest negative scores.

Conclusions

This study identified ITGB5 and RGS4 as potential biomarkers for GBM diagnosis and prognosis. Insights into molecular mechanisms governing GBM occurrence and progression will help identify alternative biomarkers for clinical practice.

Circular RNAs in gastric cancer: Biomarkers for early diagnosis

Circular RNAs (circRNAs) are highly conserved and stable closed-loop non-coding RNAs. They are involved in numerous biological functions, including regulating gene transcription or protein translation by interacting with proteins and regulating expression of microRNAs. The aberrant expression of circRNAs has been reported in many cancers, including gastric cancer. By regulating gene expression, circRNAs are able to affect the proliferation, invasion and metastasis of gastric cancer. The current review focused on the characteristics and biological functions of circRNAs, the carcinogenic potential and the possible implications of circRNAs on the diagnosis and treatment of gastric cancer. In conclusion, circRNAs may serve as potential biomarkers for diagnosis, as well as therapeutic targets.

Emerging Noninvasive Biomarkers, and Medical Management Strategies for Alcoholic Hepatitis: Present Understanding and Scope

Alcohol use disorder is associated with a wide array of hepatic pathologies ranging from steatosis to alcoholic-related cirrhosis (AC), alcoholic hepatitis (AH), or hepatocellular carcinoma (HCC). Biomarkers are categorized into two main categories: biomarkers associated with alcohol consumption and biomarkers of alcoholic liver disease (ALD). No ideal biomarker has been identified to quantify the degree of hepatocyte death or severity of AH, even though numerous biomarkers have been associated with AH. This review provides information of some of the novel and latest biomarkers that are being investigated and have shown a substantial association with the degree and severity of liver injury and inflammation. Importantly, they can be measured noninvasively. In this manuscript, we consolidate the present understanding and prospects of these biomarkers; and their application in assessing the severity and progression of the alcoholic liver disease (ALD). We also review current and upcoming management options for AH.

Identification of novel biomarkers and candidate small molecule drugs in non-small-cell lung cancer by integrated microarray analysis

Background: Non-small-cell lung cancer (NSCLC) remains the leading cause of cancer morbidity and mortality worldwide. In the present study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC.

Methods: The microarray datasets of GSE18842, GSE30219, GSE31210, GSE32863 and GSE40791 from Gene Expression Omnibus database were downloaded. The differential expressed genes (DEGs) between NSCLC and normal samples were identified by limma package. The construction of protein–protein interaction (PPI) network, module analysis and enrichment analysis were performed using bioinformatics tools. The expression and prognostic values of hub genes were validated by GEPIA database and real-time quantitative PCR. Based on these DEGs, the candidate small molecules for NSCLC were identified by the CMap database.

Results: A total of 408 overlapping DEGs including 109 up-regulated and 296 down-regulated genes were identified; 300 nodes and 1283 interactions were obtained from the PPI network. The most significant biological process and pathway enrichment of DEGs were response to wounding and cell adhesion molecules, respectively. Six DEGs (PTTG1, TYMS, ECT2, COL1A1, SPP1 and CDCA5) which significantly up-regulated in NSCLC tissues, were selected as hub genes according to the results of module analysis. The GEPIA database further confirmed that patients with higher expression levels of these hub genes experienced a shorter overall survival. Additionally, CMap predicted the 20 most significant small molecules as potential therapeutic drugs for NSCLC. DL-thiorphan was the most promising small molecule to reverse the NSCLC gene expression.

Conclusions: Based on the gene expression profiles of 696 NSCLC samples and 237 normal samples, we first revealed that PTTG1, TYMS, ECT2, COL1A1, SPP1 and CDCA5 could act as the promising novel diagnostic and therapeutic targets for NSCLC. Our work will contribute to clarifying the molecular mechanisms of NSCLC initiation and progression.

The promising novel biomarkers and candidate small molecule drugs in lower-grade glioma: Evidence from bioinformatics analysis of high-throughput data

Overall survival of patients with low-grade glioma (LGG) has shown no significant improvement over the past 30 years, with survival averaging approximately 7 years. This study aimed to identify novel promising biomarkers of LGG and reveal its potential molecular mechanisms by integrated bioinformatics analysis. The microarray datasets of GSE68848 and GSE4290 were selected from GEO database for integrated analysis. In total, 293 overlapping differentially expressed genes (DEGs) were detected using the limma package. One hundred and eighty-eight nodes with 603 interactions were obtained from the establishment of protein-protein interaction (PPI) network. Functional and signaling pathway enriched were significantly correlated with the synapse and calcium signaling pathway, respectively. Module analysis revealed eight hub genes with high connectivity, which included CHRM1, DLG2, GABRD, GRIN1, HTR2A, KCNJ3, KCNJ9, and NUSAP1, and they were markedly correlated with patients' prognosis. The mining of the Gene Expression Profiling Interactive Analysis database and qPCR further confirmed the abnormal expression of these key genes with their prognostic value in LGG. We eventually predicted the 20 most vital small molecule drugs, which potentially reverse the carcinogenic state of LGG, as per the CMap (connectivity map) database and these DEGs, and MS-275 (enrichment score = -0.939) was considered as the most promising small molecule to treat LGG. In conclusion, our study provided eight reliable novel molecular biomarkers for diagnosis, prognosis prediction, and treatment targets for LGG. These conclusions will contribute to a better comprehension of molecular mechanisms fundamental to LGG occurrence and progression, and providing new insights for future development of genomic individualized treatment in LGG.

Acute Kidney Injury Induced by Bothrops Venom: Insights into the Pathogenic Mechanisms

Acute kidney injury (AKI) following snakebite is common in developing countries and Bothrops genus is the main group of snakes in Latin America. To evaluate the pathogenic mechanisms associated with Bothrops venom nephrotoxicity, we assessed urinary and blood samples of patients after hospital admission resulting from Bothrops snakebite in a prospective cohort study in Northeast Brazil. Urinary and blood samples were evaluated during hospital stay in 63 consenting patients, divided into AKI and No-AKI groups according to the KDIGO criteria. The AKI group showed higher levels of urinary MCP-1 (Urinary monocyte chemotactic protein-1) (median 547.5 vs. 274.1 pg/mgCr; p = 0.02) and urinary NGAL (Neutrophil gelatinase-associated lipocalin) (median 21.28 vs. 12.73 ng/mgCr; p = 0.03). Risk factors for AKI included lower serum sodium and hemoglobin levels, proteinuria and aPTT (Activated Partial Thromboplastin Time) on admission and disclosed lower serum sodium (p = 0.01, OR = 0.73, 95% CI: 0.57–0.94) and aPTT (p = 0.031, OR = 26.27, 95% CI: 1.34–512.11) levels as independent factors associated with AKI. Proteinuria showed a positive correlation with uMCP-1 (r = 0.70, p < 0.0001) and uNGAL (r = 0.47, p = 0.001). FE_Na (Fractional Excretion of sodium) correlated with uMCP-1 (r = 0.47, P = 0.001) and uNGAL (r = 0.56, p < 0.0001). sCr (serum Creatinine) showed a better performance to predict AKI (AUC = 0.85) in comparison with new biomarkers. FE_K showed fair accuracy in predicting AKI (AUC = 0.92). Coagulation abnormality was strongly associated with Bothrops venom-related AKI. Urinary NGAL and MCP-1 were good biomarkers in predicting AKI; however, sCr remained the best biomarker. FE_K (Fractional Excretion of potassium) emerged as another diagnostic tool to predict early AKI. Positive correlations between uNGAL and uMCP-1 with proteinuria and FE_Na may signal glomerular and tubular injury. Defects in urinary concentrations highlighted asymptomatic abnormalities, which deserve further study.

The promising novel biomarkers and candidate small molecule drugs in kidney renal clear cell carcinoma: Evidence from bioinformatics analysis of high-throughput data

Background

Kidney renal clear cell carcinoma (KIRC) is the most common subtype of renal tumor. However, the molecular mechanisms of KIRC pathogenesis remain little known. The purpose of our study was to identify potential key genes related to the occurrence and prognosis of KIRC, which could serve as novel diagnostic and prognostic biomarkers for KIRC.

Methods

Three gene expression profiles from gene expression omnibus database were integrated to identify differential expressed genes (DEGs) using limma package. Enrichment analysis and PPI construction for these DEGs were performed by bioinformatics tools. We used Gene Expression Profiling Interactive Analysis (GEPIA) database to further analyze the expression and prognostic values of hub genes.

The GEPIA database was used to further validate the bioinformatics results. The Connectivity Map was used to identify candidate small molecules that could reverse the gene expression of KIRC.

Results

A total of 503 DEGs were obtained. The PPI network with 417 nodes and 1912 interactions was constructed. Go and KEGG pathway analysis revealed that these DEGs were most significantly enriched in excretion and valine, leucine, and isoleucine degradation, respectively. Six DEGs with high degree of connectivity (ACAA1, ACADSB, ALDH6A1, AUH, HADH,and PCCA) were selected as hub genes, which significantly associated with worse survival of patients. Finally, we identified the top 20 most significant small molecules and pipemidic acid was the most promising small molecule to reverse the KIRC gene expression.

Conclusions

This study first uncovered six key genes in KIRC which contributed to improving our understanding of the molecular mechanisms of KIRC pathogenesis. ACAA1, ACADSB, ALDH6A1, AUH, HADH,and PCCA could serve as the promising novel biomarkers for KIRC diagnosis, prognosis, and treatment.

Programmed cell death ligand-1 (PD-L1) as a biomarker for non-small cell lung cancer (NSCLC) treatment-are we barking up the wrong tree?

Immunotherapy with monoclonal antibodies targeting programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1) has become a standard of care treatment for patients with advanced or metastatic non-small cell lung cancer (NSCLC) in first and later treatment lines with durable responses seen in approximately 10-20% of patients treated. However, the optimal selection of eligible patients who will benefit most, is far from being clear and the best biomarker has not yet been established. PD-L1 expression as a predictive biomarker for immunotherapy in NSCLC patients has shown some value for predicting response to immune checkpoint inhibitors in some studies, but not in others, and its use has been complicated by a number of factors which has prompted many researchers to establish better predictive biomarkers for immunotherapy of NSCLC. Most recently, two phase III first-line NSCLC studies have provided evidence that tumour mutational burden (TMB) correlates with the clinical response to the combination of nivolumab and ipilimumab (CheckMate-227; NCT02477826), whereas atezolizumab response was correlated with T effector gene signature expression (IMPower 150; NCT02366143). Both studies demonstrated a significant primary endpoint [progression-free survival (PFS)] benefit in the TMB group and in the group of patients expressing a T effector cell signature, respectively. However, PFS benefit in both studies was seen regardless of the PD-L1 status of all patients suggesting that TMB and T effector cell signatures may be more robust to predict clinical response following treatment with checkpoint inhibitors. The role of putative novel predictive biomarkers evaluated in the CheckMate-227 and the IMPower 150 trials may, if confirmed in future prospective studies, offer a new perspective for predicting immunotherapy treatment outcomes of NSCLC patients in the near future.

Strategies to improve monitoring disease progression, assessing cardiovascular risk, and defining prognostic biomarkers in chronic kidney disease

Chronic kidney disease (CKD) is a major global public health problem with significant gaps in research, care, and policy. In order to mitigate the risks and adverse effects of CKD, the International Society of Nephrology has created a cohesive set of activities to improve the global outcomes of people living with CKD. Improving monitoring of renal disease progression can be done by screening and monitoring albuminuria and estimated glomerular filtration rate in primary care. Consensus on how many times and how often albuminuria and estimated glomerular filtration rate are measured should be defined. Meaningful changes in both renal biomarkers should be determined in order to ascertain what is clinically relevant. Increasing social awareness of CKD and partnering with the technological community may be ways to engage patients. Furthermore, improving the prediction of cardiovascular events in patients with CKD can be achieved by including the renal risk markers albuminuria and estimated glomerular filtration rate in cardiovascular risk algorithms and by encouraging uptake of assessing cardiovascular risk by general practitioners and nephrologists. Finally, examining ways to further validate and implement novel biomarkers for CKD will help mitigate the global problem of CKD. The more frequent use of renal biopsy will facilitate further knowledge into the underlying etiologies of CKD and help put new biomarkers into biological context. Real-world assessments of these biomarkers in existing cohorts is important, as well as obtaining regulatory approval to use these biomarkers in clinical practice. Collaborations among academia, physician and patient groups, industry, payer organizations, and regulatory authorities will help improve the global outcomes of people living with CKD.

Dietary Effect on the Proteome of the Common Octopus (Octopus vulgaris) Paralarvae

Nowadays, the common octopus (Octopus vulgaris) culture is hampered by massive mortalities occurring during early life-cycle stages (paralarvae). Despite the causes of the high paralarvae mortality are not yet well-defined and understood, the nutritional stress caused by inadequate diets is pointed out as one of the main factors. In this study, the effects of diet on paralarvae is analyzed through a proteomic approach, to search for novel biomarkers of nutritional stress. A total of 43 proteins showing differential expression in the different conditions studied have been identified. The analysis highlights proteins related with the carbohydrate metabolism: glyceraldehyde-3-phosphate-dedydrogenase (GAPDH), triosephosphate isomerase; other ways of energetic metabolism: NADP⁺-specific isocitrate dehydrogenase, arginine kinase; detoxification: glutathione-S-transferase (GST); stress: heat shock proteins (HSP70); structural constituent of eye lens: S-crystallin 3; and cytoskeleton: actin, actin-beta/gamma1, beta actin. These results allow defining characteristic proteomes of paralarvae depending on the diet; as well as the use of several of these proteins as novel biomarkers to evaluate their welfare linked to nutritional stress. Notably, the changes of proteins like S-crystallin 3, arginine kinase and NAD⁺ specific isocitrate dehydrogenase, may be related to fed vs. starving paralarvae, particularly in the first 4 days of development.

Prognostic clinical and molecular biomarkers of renal disease in type 2 diabetes

Diabetic kidney disease occurs in ∼ 25-40% of patients with type 2 diabetes. Given the high risk of progressive renal function loss and end-stage renal disease, early identification of patients with a renal risk is important. Novel biomarkers may aid in improving renal risk stratification. In this review, we first focus on the classical panel of albuminuria and estimated glomerular filtration rate as the primary clinical predictors of renal disease and then move our attention to novel biomarkers, primarily concentrating on assay-based multiple/panel biomarkers, proteomics biomarkers and metabolomics biomarkers. We focus on multiple biomarker panels since the molecular processes of renal disease progression in type 2 diabetes are heterogeneous, rendering it unlikely that a single biomarker significantly adds to clinical risk prediction. A limited number of prospective studies of multiple biomarkers address the predictive performance of novel biomarker panels in addition to the classical panel in type 2 diabetes. However, the prospective studies conducted so far have small sample sizes, are insufficiently powered and lack external validation. Adequately sized validation studies of multiple biomarker panels are thus required. There is also a paucity of studies that assess the effect of treatments on novel biomarker panels and determine whether initial treatment-induced changes in novel biomarkers predict changes in long-term renal outcomes. Such studies can not only improve our healthcare but also our understanding of the mechanisms of actions of existing and novel drugs and may yield biomarkers that can be used to monitor drug response. We conclude that this will be an area to focus research on in the future.

Facilitating the Validation of Novel Protein Biomarkers for Dementia: An Optimal Workflow for the Development of Sandwich Immunoassays

Different neurodegenerative disorders, such as Alzheimer’s disease (AD) and frontotemporal dementia (FTD), lead to dementia syndromes. Dementia will pose a huge impact on society and thus it is essential to develop novel tools that are able to detect the earliest, most sensitive, discriminative, and dynamic biomarkers for each of the disorders. To date, the most common assays used in large-scale protein biomarker analysis are enzyme-linked immunosorbent assays (ELISA), such as the sandwich immunoassays, which are sensitive, practical, and easily implemented. However, due to the novelty of many candidate biomarkers identified during proteomics screening, such assays or the antibodies that specifically recognize the desired marker are often not available. The development and optimization of a new ELISA should be carried out with considerable caution since a poor planning can be costly, ineffective, time consuming, and it may lead to a misinterpretation of the findings. Previous guidelines described either the overall biomarker development in more general terms (i.e., the process from biomarker discovery to validation) or the specific steps of performing an ELISA procedure. However, a workflow describing and guiding the main issues in the development of a novel ELISA is missing. Here, we describe a specific and detailed workflow to develop and validate new ELISA for a successful and reliable validation of novel dementia biomarkers. The proposed workflow highlights the main issues in the development of an ELISA and covers several critical aspects, including production, screening, and selection of specific antibodies until optimal fine-tuning of the assay. Although these recommendations are designed to analyze novel biomarkers for dementia in cerebrospinal fluid, they are generally applicable for the development of immunoassays for biomarkers in other human body fluids or tissues. This workflow is designed to maximize the quality of the developed ELISA using a time- and cost-efficient strategy. This will facilitate the validation of the dementia biomarker candidates ultimately allowing accurate diagnostic conclusions.