Kidney sequelae in 281 Shiga toxin-producing Escherichia coli-hemolytic uremic syndrome patients after a median follow-up of 12 years

BACKGROUND

A substantial proportion of patients with Escherichia coli-hemolytic uremic syndrome (STEC-HUS) evolve to chronic kidney disease (CKD). The objectives of this study were to evaluate long-term kidney outcomes and to identify CKD predictors.

METHODS

In this single-center retrospective study, long-term outcomes of patients were analyzed according to the presence of complete recovery (CR) or CKD at last visit. Then, they were grouped into favorable (CR + CKD1) or poor (CKD2-5) outcome to compare predictors at diagnosis (sex, age, leukocytes, creatinine, hemoglobin, HUS severity score), dialysis duration, and follow-up time between them.

RESULTS

Of 281 patients followed up for a median of 12 years, 139 (49%) had CR, 104 (37%) CKD1, 27 (10%) CKD2-4, and 11 (4%) CKD5. Thirty-eight patients progressed to CKD2-5 after a median of 4.8 years, 7% in the first 5 years, increasing to 8%, 10%, and 14% after 5-10 years, 10-15 years, and > 15 years, respectively. They were younger, had higher baseline hemoglobin and leukocytes, and required longer dialysis and follow-up than those with favorable outcome. By multivariate analysis, days of dialysis and follow-up time remained as independent predictors of poor outcome. The best cutoff for days of dialysis was 10 days. After 5 years, 20% of those dialyzed ≥ 10 days evolved to CKD2-5 versus 1% of those non-dialyzed or dialyzed < 10 days.

CONCLUSIONS

Fifty-one percent of patients evolved to CKD after 12 years of follow-up and 14% to CKD2-5. Ten days of dialysis was the best cutoff to recognize outcomes. In some cases, kidney damage was evident after 15 years of surveillance, highlighting the need for follow-up until adulthood in all STEC-HUS patients.

Caveolin-1 gene expression provides additional prognostic information combined with PAM50 risk of recurrence (ROR) score in breast cancer

Combining information from the tumor microenvironment (TME) with PAM50 Risk of Recurrence (ROR) score could improve breast cancer prognostication. Caveolin-1 (CAV1) is a marker of an active TME. CAV1 is a membrane protein involved in cell signaling, extracellular matrix organization, and tumor-stroma interactions. We sought to investigate CAV1 gene expression in relation to PAM50 subtypes, ROR score, and their joint prognostic impact. CAV1 expression was compared between PAM50 subtypes and ROR categories in two cohorts (SCAN-B, n = 5326 and METABRIC, n = 1980). CAV1 expression was assessed in relation to clinical outcomes using Cox regression and adjusted for clinicopathological predictors. Effect modifications between CAV1 expression and ROR categories on clinical outcome were investigated using multiplicative and additive two-way interaction analyses. Differential gene expression and gene set enrichment analyses were applied to compare high and low expressing CAV1 tumors. All samples expressed CAV1 with the highest expression in the Normal-like subtype. Gene modules consistent with epithelial-mesenchymal transition (EMT), hypoxia, and stromal activation were associated with high CAV1 expression. CAV1 expression was inversely associated with ROR category. Interactions between CAV1 expression and ROR categories were observed in both cohorts. High expressing CAV1 tumors conferred worse prognosis only within the group classified as ROR high. ROR gave markedly different prognostic information depending on the underlying CAV1 expression. CAV1, a potential mediator between the malignant cells and TME, could be a useful biomarker that enhances and further refines PAM50 ROR risk stratification in patients with ROR high tumors and a potential therapeutic target.

Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology

Recent genome-wide association studies have successfully identified associations between genetic variants and simple cardiac morphological parameters derived from cardiac magnetic resonance images. However, the emergence of large databases, including genetic data linked to cardiac magnetic resonance facilitates the investigation of more nuanced patterns of cardiac shape variability than those studied so far. Here we propose a framework for gene discovery coined unsupervised phenotype ensembles. The unsupervised phenotype ensemble builds a redundant yet highly expressive representation by pooling a set of phenotypes learnt in an unsupervised manner, using deep learning models trained with different hyperparameters. These phenotypes are then analysed via genome-wide association studies, retaining only highly confident and stable associations across the ensemble. We applied our approach to the UK Biobank database to extract geometric features of the left ventricle from image-derived three-dimensional meshes. We demonstrate that our approach greatly improves the discoverability of genes that influence left ventricle shape, identifying 49 loci with study-wide significance and 25 with suggestive significance. We argue that our approach would enable more extensive discovery of gene associations with image-derived phenotypes for other organs or image modalities.

Lipid metabolism-related long noncoding RNA RP11-817I4.1 promotes fatty acid synthesis and tumor progression in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common types of tumors. The influence of lipid metabolism disruption on the development of HCC has been demonstrated in published studies.

AIM

To establish an HCC prognostic model for lipid metabolism-related long non-coding RNAs (LMR-lncRNAs) and conduct in-depth research on the specific role of novel LMR-lncRNAs in HCC.

METHODS

Correlation and differential expression analyses of The Cancer Genome Atlas data were used to identify differentially expressed LMR-lncRNAs. Quantitative real-time polymerase chain reaction analysis was used to evaluate the expression of LMR-lncRNAs. Nile red staining was employed to observe intracellular lipid levels. The interaction between RP11-817I4.1, miR-3120-3p, and ATP citrate lyase (ACLY) was validated through the performance of dual-luciferase reporter gene and RIP assays.

RESULTS

Three LMR-lncRNAs (negative regulator of antiviral response, RNA transmembrane and coiled-coil domain family 1 antisense RNA 1, and RP11-817I4.1) were identified as predictive markers for HCC patients and were utilized in the construction of risk models. Additionally, proliferation, migration, and invasion were reduced by RP11-817I4.1 knockdown. An increase in lipid levels in HCC cells was significantly induced by RP11-817I4.1 through the miR-3120-3p/ACLY axis.

CONCLUSION

LMR-lncRNAs have the capacity to predict the clinical characteristics and prognoses of HCC patients, and the discovery of a novel LMR-lncRNAs, RP11-817I4.1, revealed its role in promoting lipid accumulation, thereby accelerating the onset and progression of HCC.

The prognostic effect of tumor-associated macrophages in stage I-III colorectal cancer depends on T cell infiltration

BACKGROUND

Tumor-associated macrophages (TAMs) are associated with unfavorable patient prognosis in many cancer types. However, TAMs are a heterogeneous cell population and subsets have been shown to activate tumor-infiltrating T cells and confer a good patient prognosis. Data on the prognostic value of TAMs in colorectal cancer are conflicting. We investigated the prognostic effect of TAMs in relation to tumor-infiltrating T cells in colorectal cancers.

METHODS

The TAM markers CD68 and CD163 were analyzed by multiplex fluorescence immunohistochemistry and digital image analysis on tissue microarrays of 1720 primary colorectal cancers. TAM density in the tumor stroma was scored in relation to T cell density (stromal CD3+ and epithelial CD8+ cells) and analyzed in Cox proportional hazards models of 5-year relapse-free survival. Multivariable survival models included clinicopathological factors, MSI status and BRAFV600E mutation status.

RESULTS

High TAM density was associated with a favorable 5-year relapse-free survival in a multivariable model of patients with stage I-III tumors (p = 0.004, hazard ratio 0.94, 95% confidence interval 0.90-0.98). However, the prognostic effect was dependent on tumoral T-cell density. High TAM density was associated with a good prognosis in patients who also had high T-cell levels in their tumors, while high TAM density was associated with poorer prognosis in patients with low T-cell levels (pinteraction = 0.0006). This prognostic heterogeneity was found for microsatellite stable tumors separately.

CONCLUSIONS

This study supported a phenotypic heterogeneity of TAMs in colorectal cancer, and showed that combined tumor immunophenotyping of multiple immune cell types improved the prediction of patient prognosis.

A robust primary liver cancer subtype related to prognosis and drug response based on a multiple combined classifying strategy

The recurrence or resistance to treatment of primary liver cancer (PLL) is significantly related to the heterogeneity present within the tumor. In this study, we integrated prognosis risk score, mRNAsi index, and immune characteristics clustering to classify patients. The four subtypes obtained from the combined classification are associated with PLC's prognosis and drug response. In these subtypes, we observed mRNAsiH_ICCA subtype, the intersection between high mRNAsi and immune characteristics clustering A, had the worst prognosis. Specifically, immune characteristics clustering B (ICC_B) had high drug sensitivity in most drugs regardless of the value of mRNAsi. On the other hand, patients with low mRNAsi responded better to ten drugs including KU-55933 and NU7441, while patients with high mRNAsi might benefit from drugs like Leflunomide. By matching the specific characteristics of each combined subtype with the drug-induced cell line expression profile, we identified a group of potential therapeutic drugs that might regulate the expression of disease signature genes. We developed a feasible multiple combined typing strategy, hoping to guide therapeutic selection and promote the development of precision medicine.

Clinicopathological and radiological stratification within FIGO 2018 stages improves risk-prediction in cervical cancer

OBJECTIVE

Assess the added prognostic value of the updated International Federation of Gynecology and Obstetrics (FIGO) 2018 staging system, and to identify clinicopathological and radiological biomarkers for improved FIGO 2018 prognostication.

METHODS

Patient data were retrieved from a prospectively collected patient cohort including all consenting patients with cervical cancer diagnosed and treated at Haukeland University Hospital during 2001-2022 (n = 948). All patients were staged according to the FIGO 2009 and FIGO 2018 guidelines based on available data for individual patients. MRI-assessed maximum tumor diameter and stromal tumor invasion, as well as histopathologically assessed lymphovascular space invasion were applied to categorize patients according to the Sedlis criteria.

RESULTS

FIGO 2018 stage yielded the highest area under the receiver operating characteristic (ROC) curve (AUC) (0.86 versus 0.81 for FIGO 2009) for predicting disease-specific survival. The most common stage migration in FIGO 2018 versus FIGO 2009 was upstaging from stages IB/II to stage IIIC due to suspicious lymph nodes identified by PET/CT and/or MRI. In FIGO 2018 stage III patients, extent and size of primary tumor (p = 0.04), as well as its histological type (p = 0.003) were highly prognostic. Sedlis criteria were prognostic within FIGO 2018 IB patients (p = 0.04).

CONCLUSIONS

Incorporation of cross-sectional imaging increases prognostic precision, as suggested by the FIGO 2018 guidelines. The 2018 FIGO IIIC stage could be refined by including the size and extent of primary tumor and histological type. The FIGO IB risk prediction could be improved by applying MRI-assessed tumor size and stromal invasion.

NCAPG2 promotes prostate cancer malignancy and stemness via STAT3/c-MYC signaling

BACKGROUND

Prostate cancer (PCa) is the second leading cause of cancer-related mortality among men worldwide, and its incidence has risen substantially in recent years. Therefore, there is an urgent need to identify novel biomarkers and precise therapeutic targets for managing PCa progression and recurrence.

METHODS

We investigated the clinical significance of NCAPG2 in PCa by exploring public datasets and our tissue microarray. Receiver operating characteristic (ROC) curve and survival analyses were performed to evaluate the correlation between NCAPG2 and PCa progression. Cell proliferation, wound healing, transwell, flow cytometry, cell cycle, tumor sphere formation, immunofluorescence (IF), co-immunoprecipitation (co-IP), and chromatin immunoprecipitation (ChIP) assays were conducted to further elucidate the molecular mechanism of NCAPG2 in PCa. Subcutaneous and orthotopic xenograft models were applied to investigate the effects of NCAPG2 on PCa proliferation in vivo. Tandem mass tag (TMT) quantitative proteomics was utilized to detect proteomic changes under NCAPG2 overexpression.

RESULTS

NCAPG2 was significantly upregulated in PCa, and its overexpression was associated with PCa progression and unfavorable prognosis. Knockdown of NCAPG2 inhibited the malignant behavior of PCa cells, whereas its overexpression promoted PCa aggressiveness. NCAPG2 depletion attenuated the development and growth of PCa in vivo. TMT quantitative proteomics analyses indicated that c-MYC activity was strongly correlated with NCAPG2 expression. The malignancy-promoting effect of NCAPG2 in PCa was mediated via c-MYC. NCAPG2 could directly bind to STAT3 and induce STAT3 occupancy on the MYC promoter, thus to transcriptionally activate c-MYC expression. Finally, we identified that NCAPG2 was positively correlated with cancer stem cell (CSC) markers and enhanced self-renewal capacity of PCa cells.

CONCLUSIONS

NCAPG2 is highly expressed in PCa, and its level is significantly associated with PCa prognosis. NCAPG2 promotes PCa malignancy and drives cancer stemness via the STAT3/c-MYC signaling axis, highlighting its potential as a therapeutic target for PCa.

Current advances in comprehensive omics data mining for oncology and cancer research

The availability of a large amount of multiomics data enables data-driven discovery studies on cancers. High-throughput data on mutations, gene/protein expression, immune scores (tumor-infiltrating cells), drug screening, and RNAi (shRNAs and CRISPRs) screening are major integrated components of patient samples and cell line datasets. Improvements in data access and user interfaces make it easy for general scientists to carry out their data mining practices on integrated multiomics data platforms without computational expertise. Here, we summarize the extent of data integration and functionality of several portals and software that provide integrated multiomics data mining platforms for all cancer studies. Recent progress includes programming interfaces (APIs) for customized data mining. Precalculated datasets assist noncomputational users in quickly browsing data associations. Furthermore, stand-alone software provides fast calculations and smart functions, guiding optimal sampling and filtering options for the easy discovery of significant data associations. These efforts improve the utility of cancer omics big data for noncomputational users at all levels of cancer research. In the present review, we aim to provide analytical information guiding general scientists to find and utilize data mining tools for their research.

Consultation on UTUC II Stockholm 2022: diagnostic and prognostic methods-what's around the corner?

PURPOSE

To map current literature and provide an overview of upcoming future diagnostic and prognostic methods for upper tract urothelial carcinoma (UTUC), including translational medical science.

METHODS

A scoping review approach was applied to search the literature. Based on the published literature, and the experts own experience and opinions consensus was reached through discussions at the meeting Consultation on UTUC II in Stockholm, September 2022.

RESULTS

The gene mutational profile of UTUC correlates with stage, grade, prognosis, and response to different therapeutic strategies. Analysis of pathway proteins downstream of known pathogenic mutations might be an alternative approach. Liquid biopsies of cell-free DNA may detect UTUC with a higher sensitivity and specificity than urinary cytology. Extracellular vesicles from tumour cells can be detected in urine and may be used to identify the location of the urothelial carcinoma in the urinary tract. 3D microscopy of UTUC samples may add information in the analysis of tumour stage. Chemokines and chemokine receptors were linked to overall survival and responsiveness to neoadjuvant chemotherapy in muscle-invasive bladder cancer, which is potentially also of interest in UTUC.

CONCLUSION

Current diagnostic methods for UTUC have shortcomings, especially concerning prognostication, which is important for personalized treatment decisions. There are several upcoming methods that may be of interest for UTUC. Most have been studied for urothelial carcinoma of the bladder, and it is important to keep in mind that UTUC is a different entity and not all methods are adaptable or applicable to UTUC.

Impact of Remdesivir on inflammatory and prognostic markers of COVID-19: Findings of an event-monitoring study

Introduction

Remdesivir is currently approved for treating hospitalised patients with COVID-19. However, it is a priority to monitor its safety and effectiveness in various clinical settings. This study was undertaken to assess the impact of remdesivir on inflammatory and prognostic markers of COVID-19.

Materials and Methods

A hospital-based prospective longitudinal study was conducted over two months comprising event monitoring of COVID-19 patients administered remdesivir as per standard guidelines. The demographic details, risk factors and all baseline parameters were collected. The patients were followed up for the appearance of any adverse drug reactions (ADRs) after the start of remdesivir therapy from Day 1 to discharge or death every day. Repeat Lab tests were done on days 2, 4, 6 and 10 days to assess the impact of remdesivir on inflammatory and prognostic markers of COVID-19 over time. Significant predictors of survival in the cohort were also assessed.

Results

A total of 60 COVID-19 patients were administered remdesivir. The mean age of the patients was 59.2 (+13.7) years. There was a significant improvement in the serum creatinine (decreased from 0.9 to 0.7 mg/dL), lymphocyte count {decreased from 9.2 to 7.3 (109 cells/L)} and serum sodium (increased from 134.6 to 137.4) of the patients over six days after the administration of remdesivir. The significant survival predictors were multiple organ failure (P 0.046) and WBC count on Day 10 (P 0.001).

Conclusion

Remdesivir administration improved the prognostic biomarker profile in COVID-19 patients.

Pathological determinants of outcome following resection of locally advanced or locally recurrent rectal cancer

INTRODUCTION

Pathological factors that influence and predict survival following pelvic exenteration (PE) for locally advanced (LARC) or locally recurrent rectal cancer (LRRC), especially LRRC, remain poorly understood. A clear resection margin has previously been demonstrated to be of most significance.

MATERIALS AND METHODS

A retrospective cohort study was performed for all patients undergoing a curative PE for LARC or LRRC between 2008 and 2021 at a tertiary referral UK specialist colorectal hospital. Cox regression analysis was planned to identify pathological factors associated with overall (OS), disease free (DFS) and local recurrence free survival (LRFS).

RESULTS

388 patients were included in the analysis with 256 resections for LARC and 132 for LRRC. 62.4% of patients were male with a median age of 59 years (IQR 49-67). 247 (64%) partial pelvic exenterations and 141 (36%) total pelvic exenterations performed. Overall R0 rate 86.6%. Poorly differentiated tumours and a positive resection margin independently influenced OS, DFS and LRFS on multivariate analysis in LARC. On multivariate analysis venous invasion negatively influenced DFS and poorly differentiated lesions negatively influenced LRFS in LRRC.

CONCLUSIONS

A positive resection margin and poorly differentiated tumours are significant negative prognostic markers for survival and recurrence in LARC. The results of this study support the need to look for alternative prognostic markers beyond that in the existing standard reporting dataset for rectal cancers. With increasing R0 rates, novel prognostic pathological markers are required to help guide treatment and surveillance for patients with LRRC.

Development and validation of an individualized gene expression-based signature to predict overall survival of patients with high-grade serous ovarian carcinoma

BACKGROUND

High-grade serious ovarian carcinoma (HGSOC) is a subtype of ovarian cancer with a different prognosis attributable to genetic heterogeneity. The prognosis of patients with advanced HGSOC requires prediction by genetic markers. This study systematically analyzed gene expression profile data to establish a genetic marker for predicting HGSOC prognosis.

METHODS

The RNA-seq data set and information on clinical follow-up of HGSOC were retrieved from Gene Expression Omnibus (GEO) database, and the data were standardized by DESeq2 as a training set. On the other hand, HGSOC RNA sequence data and information on clinical follow-up were retrieved from The Cancer Genome Atlas (TCGA) as a test set. Additionally, ovarian cancer microarray data set was obtained from GEO as the external validation set. Prognostic genes were screened from the training set, and characteristic selection was performed using the least absolute shrinkage and selection operator (LASSO) with 80% re-sampling for 5000 times. Genes with a frequency of more than 2000 were selected as robust biomarkers. Finally, a gene-related prognostic model was validated in both the test and GEO validation sets.

RESULTS

A total of 148 genes were found to be significantly correlated with HGSOC prognosis. The expression profile of these genes could stratify HGSOC prognosis and they were enriched to multiple tumor-related regulatory pathways such as tyrosine metabolism and AMPK signaling pathway. AKR1B10 and ANGPT4 were obtained after 5000-time re-sampling by LASSO regression. AKR1B10 was associated with the metastasis and progression of several tumors. In this study, Cox regression analysis was performed to create a 2-gene signature as an independent prognostic factor for HGSOC, which has the ability to stratify risk samples in all three data sets (p < 0.05). The Gene Set Enrichment Analysis (GSEA) discovered abnormally active REGULATION_OF_AUTOPHAGY and OLFACTORY_TRANSDUCTION pathways in the high-risk group samples.

CONCLUSION

This study resulted in the creation of a 2-gene molecular prognostic classifier that distinguished clinical features and was a promising novel prognostic tool for assessing the prognosis of HGSOC. RiskScore was a novel prognostic model which might be effective in guiding accurate prognosis of HGSOC.

Unraveling the role of disulfidptosis-related LncRNAs in colon cancer: a prognostic indicator for immunotherapy response, chemotherapy sensitivity, and insights into cell death mechanisms

Background: Colon cancer, a prevalent and deadly malignancy worldwide, ranks as the third leading cause of cancer-related mortality. Disulfidptosis stress triggers a unique form of programmed cell death known as disulfidoptosis, characterized by excessive intracellular cystine accumulation. This study aimed to establish reliable bioindicators based on long non-coding RNAs (LncRNAs) associated with disulfidptosis-induced cell death, providing novel insights into immunotherapeutic response and prognostic assessment in patients with colon adenocarcinoma (COAD). Methods: Univariate Cox proportional hazard analysis and Lasso regression analysis were performed to identify differentially expressed genes strongly associated with prognosis. Subsequently, a multifactorial model for prognostic risk assessment was developed using multiple Cox proportional hazard regression. Furthermore, we conducted comprehensive evaluations of the characteristics of disulfidptosis response-related LncRNAs, considering clinicopathological features, tumor microenvironment, and chemotherapy sensitivity. The expression levels of prognosis-related genes in COAD patients were validated using quantitative real-time fluorescence PCR (qRT-PCR). Additionally, the role of ZEB1-SA1 in colon cancer was investigated through CCK8 assays, wound healing experiment and transwell experiments. Results: disulfidptosis response-related LncRNAs were identified as robust predictors of COAD prognosis. Multifactorial analysis revealed that the risk score derived from these LncRNAs served as an independent prognostic factor for COAD. Patients in the low-risk group exhibited superior overall survival (OS) compared to those in the high-risk group. Accordingly, our developed Nomogram prediction model, integrating clinical characteristics and risk scores, demonstrated excellent prognostic efficacy. In vitro experiments demonstrated that ZEB1-SA1 promoted the proliferation and migration of COAD cells. Conclusion: Leveraging medical big data and artificial intelligence, we constructed a prediction model for disulfidptosis response-related LncRNAs based on the TCGA-COAD cohort, enabling accurate prognostic prediction in colon cancer patients. The implementation of this model in clinical practice can facilitate precise classification of COAD patients, identification of specific subgroups more likely to respond favorably to immunotherapy and chemotherapy, and inform the development of personalized treatment strategies for COAD patients based on scientific evidence.

Identification and verification of a novel anoikis-related gene signature with prognostic significance in clear cell renal cell carcinoma

PURPOSE

Clear cell renal cell carcinomas (ccRCCs) are the most common form of renal cancer in the world. The loss of extracellular matrix (ECM) stimulates cell apoptosis, known as anoikis. A resistance to anoikis in cancer cells is believed to contribute to tumor malignancy, particularly metastasis; however, the potential influence of anoikis on the prognosis of ccRCC patients is not fully understood.

METHODS

In this study, anoikis-related genes (ARGs) with discrepant expression were selected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The anoikis-related gene signature (ARS) was built using a combination of the univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses. ARS was also evaluated for their prognostic value. We explored the tumor microenvironment and enrichment pathways between different clusters of ccRCC. We also examined differences in clinical characteristics, immune cell infiltration and drug sensitivity between the high- and low-risk sets. In addition, we utilized three external databases and quantitative real-time polymerase chain reaction (qRT-PCR) to validate the expression and prognosis of ARGs.

RESULTS

Eight ARGs (PLAUR, HMCN1, CDKN2A, BID, GLI2, PLG, PRKCQ and IRF6) were identified as anoikis-related prognostic factors. According to Kaplan-Meier (KM) analysis, ccRCC patients with high-risk ARGs have a worse prognosis. The risk score was found to be a significant independent prognostic indicator. According to tumor microenvironment (TME) scores, stromal score, immune score, and estimated score of the high-risk group were superior to those of the low-risk group. There were significant differences between the two groups regarding the amount of infiltrated immune cells, immune checkpoint expression as well as drug sensitivity. A nomogram was constructed using ccRCC clinical features and risk scores. The signature and the nomogram both performed well in predicting overall survival (OS) for ccRCC patients. According to a decision curve analysis (DCA), clinical treatment options for patients with ccRCC could be improved using this model.

CONCLUSION

The results of validation from external databases and qRT-PCR were basically agreement with findings in TCGA and GEO databases. The ARS serving as biomarkers may provide an important reference for individual therapy of ccRCC patients.

Role of Nuclear Factor-Kappa B Activation and Inflammatory Biomarkers in Critically Ill Children

Mortality prediction is important for cautious monitoring and optimal management of critically ill children. The serum cytokine levels are elevated early in critical illness before the physiological parameters are deranged. This cross-sectional descriptive study included the critically ill children admitted in intensive care unit. Serial serum levels of IL-6, NF-κB and PELOD 2 scoring were measured and compared in 45 children (40 survivors, 5 non-survivors). The median IL-6 levels at 24 h and 72 h were significantly high in non-survivors when compared to survivors [median (IQR) = 1122 (1305) pg/ml vs. 564.39 (153) pg/ml and 1263 (626) pg/ml vs. 82 (191) pg/ml respectively; p <0.0001)]. There was an increasing trend of IL-6 in non-survivors when compared to the survivors. The NF-κB values were comparable. The IL-6 levels correlated well with the illness severity. IL-6 had superior prognostic value compared with NF-κB in predicting mortality.

Prognostic Markers in the Era of Targeted Therapies

BACKGROUND

Small molecules targeting Bruton's tyrosine kinase (BTK) and B-cell lymphoma-2 have become the standard of care for the treatment of chronic lymphocytic leukemia (CLL), replacing chemoimmunotherapy (CIT) in most clinical settings. Ongoing trials explore targeted combinations and minimal residual disease-driven treatment cessation. These dramatic shifts in the current and upcoming treatment landscape of CLL raise the need to reevaluate existing prognostic markers and develop novel ones.

SUMMARY

This review examines prognostic markers in CLL patients treated with standard and investigational targeted therapies. Specifically, initial treatment of TP53 aberrant patients with a BTK inhibitor can achieve 70% progression-free survival (PFS) at 5 years, outperforming the 15% 5-year PFS with a CIT regimen containing fludarabine, cyclophosphamide, and rituximab (FCR). The prognostic implications of the immunoglobulin heavy chain variable gene (IGHV) mutation status have also changed. Unmutated IGHV is associated with inferior PFS and overall survival after FCR and inferior PFS with fixed-duration therapy with venetoclax and anti-CD20 monoclonal antibody but not with continuous BTK inhibitor treatment.

KEY MESSAGES

(1) Genetic variables (e.g., TP53 aberration, IGHV mutation, complex karyotype) have a prognostic significance in CLL patients treated with targeted therapy. (2) Understanding the prognostic and predictive values of these markers is critical for the development of a risk-adapted treatment strategy in CLL.

Role of Hematological Markers in Oral Potentially Malignant Disorders and Oral Squamous Cell Carcinoma

Various haematological markers have been shown to be diagnostic and prognostic in oral cancer. This study compares the values of the inflammatory metrics neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), ESR and HB in precancerous and cancerous lesions to see if one of them can be utilised to make an early diagnosis of oral squamous cell carcinoma. To compare haematological markers as a diagnostic marker to differentiate healthy individuals, oral potentially malignant disorders from oral squamous cell carcinoma patients. One hundred fifty patients were divided into three groups which includes 50 apparently healthy individuals (group A), 50 individuals with premalignant disorders (group B) and 50 individuals with oral squamous cell carcinoma (OSCC) (group C). The levels of various haematological parameters obtained from 5 ml of intravenous blood was drawn from each subject were compared between these three groups. Using Kruskal Wallis and the Mann Whitney post hoc U test, comparisons between the NLR values were examined. A total of number of 150 individuals were included in the current study. The mean age is 43.3 years out of which 49 (81.6%) were male and 11(18.3%) were female. The mean NLR in group 1, 2 and 3 were 2.16, 3.12 and 3.67 respectively and mean PLR were 91.1, 110.3 and 160.6 respectively. The mean Hb content was 14.8, 13.77 and 12.76 respectively. The mean ESR was 9.65, 17.2 and 27.4 respectively. These parameters can be used as valuable adjuvant in identifying and understanding the nature of disease of both potentially malignant diseases and oral cancer.

Analysis of prognostic biomarker models and immune microenvironment in acute myeloid leukemia by integrative bioinformatics

BACKGROUND

Acute myeloid leukemia (AML) is a hematological cancer driven on by aberrant myeloid precursor cell proliferation and differentiation. A prognostic model was created in this study to direct therapeutic care.

METHODS

Differentially expressed genes (DEGs) were investigated using the RNA-seq data from the TCGA-LAML and GTEx. Weighted Gene Coexpression Network Analysis (WGCNA) examines the genes involved in cancer. Find the intersection genes and construct the PPI network to discover hub genes and remove prognosis-related genes. A nomogram was produced for predicting the prognosis of AML patients using the risk prognosis model that was constructed using COX and Lasso regression analysis. GO, KEGG, and ssGSEA analysis were used to look into its biological function. TIDE score predicts immunotherapy response.

RESULTS

Differentially expressed gene analysis revealed 1004 genes, WGCNA analysis revealed 19,575 tumor-related genes, and 941 intersection genes in total. Twelve prognostic genes were found using the PPI network and prognostic analysis. To build a risk rating model, RPS3A and PSMA2 were examined using COX and Lasso regression analysis. The risk score was used to divide the patients into two groups, and Kaplan-Meier analysis indicated that the two groups had different overall survival rates. Univariate and multivariate COX studies demonstrated that risk score is an independent prognostic factor. According to the TIDE study, the immunotherapy response was better in the low-risk group than in the high-risk group.

CONCLUSIONS

We eventually selected out two molecules to construct prediction models that might be used as biomarkers for predicting AML immunotherapy and prognosis.

Recent Developments in Diagnostic and Prognostic Biomarkers for Colorectal Cancer: A Narrative Review

BACKGROUND

Colorectal cancer was reported as the second most common cause of cancer death worldwide, in the year 2020. This disease is an important public health problem considering its high incidence and mortality rates.

SUMMARY

The molecular events that lead to colorectal cancer include genetic and epigenetic abnormalities. Some of the most important molecular mechanisms involved include the APC/β-catenin pathway, the microsatellite pathway, and the CpG island hypermethylation. Evidence in the literature supports a role for the microbiota in the development of colon carcinogenesis, and specific microbes may contribute to or prevent carcinogenesis. Progress in prevention, screening, and management has improved the overall prognosis of the disease when diagnosed at an early stage; yet metastatic disease continues to have a poor long-term prognosis due to late-stage diagnosis and treatment failure. Biomarkers are a key tool for early detection and prognosis and aim to reduce morbidity and mortality associated with colorectal cancer. The main focus of this narrative review is to provide an update on the recent development of diagnostic and prognostic biomarkers in stool, blood, and tumor tissue samples.

KEY MESSAGES

The review focuses on recent investigations in microRNAs, cadherins, Piwi-interacting RNAs, circulating cell-free DNA, and microbiome biomarkers which can be applied for the diagnosis and prognosis of colorectal cancer.

Dengue hepatitis: Incidence, spectrum and outcome

BACKGROUND AND AIMS

While dengue infection is common in India, there is scarce information on dengue hepatitis. The aim of this study was to analyze the incidence, spectrum and outcome of dengue hepatitis.

METHODS

We retrospectively analyzed consecutive patients, who had hepatitis among those with dengue infection admitted to two tertiary care hospitals in western India from January 2016 to March 2021. Diagnosis of dengue infection was made by serology. Dengue hepatitis was diagnosed and the severity of dengue was categorized by standard criteria.

RESULTS

Of 1664 patients admitted with dengue fever during the study period, 199 patients had hepatitis (i.e. incidence of dengue hepatitis was 11.9%). Of the 199 dengue hepatitis patients (age: 29 [13 - 80] years, median [range], 67% males), 100 patients (50%) had severe dengue, 73 (36%) had severe dengue hepatitis, 32 (16%) had dengue shock syndrome and eight (4%) had acute liver failure. Forty-five patients (23%) had acute lung injury and 32 (16%) had acute kidney injury. The dengue hepatitis patients were treated with standard medical care, including vital organ support, as needed-166 (83%) patients survived, while 33 patients (17%) died (cause of death: multi-organ failure: 24 patients, septic shock: nine patients). The presence of shock independently predicted mortality (odds ratio 6.4, 95% confidence interval: 1.2 - 34). Among patients with dengue hepatitis, mortality rate was higher in those with severe dengue (23%), dengue shock syndrome (47%), severe dengue hepatitis (24%) and acute liver failure (38%).

CONCLUSION

In this large series of hospitalized patients with dengue infection, the incidence of dengue hepatitis was 11.9%. Among 199 dengue hepatitis, 17% died; multi-organ failure was the commonest cause for death and death rate was higher in patients with more severe disease. The presence of shock at presentation independently predicted mortality.

Copeptin: Up-to-date diagnostic and prognostic role highlight

Arginine Vasopressin (AVP) is one of the key hormones in the human body. AVP is clinically important because it maintains body fluid balance and vascular tone. Unfortunately, AVP laboratory measurements are always difficult and with low accuracy. Copeptin, the C-terminal of the AVP precursor, is released in equal amounts with AVP, making it a sensitive marker of AVP release. Despite being a non-specific biomarker, copeptin earned a lot of attention as a novel biomarker due to easy and quick laboratory measurements. Recent studies have reported the critical role of copeptin as a clinical indicator, especially in the diagnosis and prognosis of many diseases. Besides, it was reported that the combination between copeptin and gold standard biomarkers improved the prognostic values of those biomarkers. In this review, the role of copeptin as a new predictive diagnostic and prognostic biomarker of various diseases is highlighted according to the most recent studies. In addition, the importance of using copeptin as a marker in different medical departments and the impact of this on improving healthcare service was discussed.

Gender-specific dysregulations of nondifferentially expressed biomarkers of metastatic colon cancer

Colon cancer is a common cancer type in both sexes and its mortality rate increases at the metastatic stage. Most studies exclude nondifferentially expressed genes from biomarker analysis of metastatic colon cancers. The motivation of this study is to find the latent associations of the nondifferentially expressed genes with metastatic colon cancers and to evaluate the gender specificity of such associations. This study formulates the expression level prediction of a gene as a regression model trained for primary colon cancers. The difference between a gene's predicted and original expression levels in a testing sample is defined as its mqTrans value (model-based quantitative measure of transcription regulation), which quantitatively measures the change of the gene's transcription regulation in this testing sample. We use the mqTrans analysis to detect the messenger RNA (mRNA) genes with nondifferential expression on their original expression levels but differentially expressed mqTrans values between primary and metastatic colon cancers. These genes are referred to as dark biomarkers of metastatic colon cancer. All dark biomarker genes were verified by two transcriptome profiling technologies, RNA-seq and microarray. The mqTrans analysis of a mixed cohort of both sexes could not recover gender-specific dark biomarkers. Most dark biomarkers overlap with long non-coding RNAs (lncRNAs), and these lncRNAs might have contributed their transcripts to calculating the dark biomarkers' expression levels. Therefore, mqTrans analysis serves as a complementary approach to identify dark biomarkers generally ignored by conventional studies, and it is essential to separate the female and male samples into two analysis experiments. The dataset and mqTrans analysis code are available at https://figshare.com/articles/dataset/22250536.

Prognostic Value of IMP3 and Its Role as an Epithelial-Mesenchymal Transition Promoter in Breast Carcinoma

Breast carcinoma is now the most common cancer in the world. In view of its high mortality, there is a need to identify new prognostic biomarkers. Both IMP3 and SLUG have been implicated in cancer metastasis. This was a retrospective study conducted on 60 breast carcinoma cases using tissue microarrays. Demographic and clinicopathological details were recorded. Immunohistochemistry for IMP3 and SLUG was performed and evaluated in terms of percentage-cell-positivity and intensity of staining. A proforma was used to store data and was analyzed using SPSS v20. IMP3 positivity was found in 87% breast carcinoma cases and was significantly associated with tumor size (p = 0.03) and TNM stage (p = 0.024). IMP3 staining intensity showed significant association with histological grade (p = 0.009), TNM stage (p = 0.036), and molecular subtype (p = 0.03). SLUG immunoexpression was seen in 90% breast carcinoma cases and was significantly associated with TNM stage (p = 0.006). SLUG staining intensity was significantly associated with age (p = 0.025) and TNM stage (p = 0.004). IMP3 and SLUG immunopositivity and their staining intensities were significantly associated (p <0.001, p <0.001). IMP3 and SLUG percentage cell positivities were also significantly correlated (p <0.001). IMP3 and SLUG are, thus, poor prognostic markers with a role in tumor invasiveness and aggressiveness via epithelial-mesenchymal transition. Hence, IMP3 and SLUG-based targeted therapies may be useful in the treatment of breast carcinoma.

Molecular Profiling in Early ER + Breast Cancer to Aid Systemic Therapy Decisions

PURPOSE OF REVIEW

Clinical decisions for (neo)adjuvant treatment in early breast cancer (eBC) have been based mostly on clinical factors over the last decades. We have reviewed development and validation of such assays in the HR + /HER2 eBC and discuss possible future directions in this field.

RECENT FINDINGS

Increasing knowledge about the biology of hormone-sensitive eBC, based on the precise and reproducible multigene expression analysis, has led to a significant change in the treatment pathways and reduction of overtreatment in particular by chemotherapy in HR + /HER2 eBC with up to 3 positive lymph nodes based on results from several retrospective-prospective trials used several genomic assays and in particular prospective trials (TAILORx, RxPonder, MINDACT, and ADAPT used OncotypeDX® and Mammaprint®). Precise evaluation of tumor biology together with endocrine responsiveness assessment appears as promising tools for individualized treatment decisions together with clinical factors and menopausal status in early hormone-sensitive/HER2-negative breast cancer.

An empirical review on the resistance mechanisms of epidermal growth factor receptor inhibitors and predictive molecular biomarkers in colorectal cancer

Despite advances in cytotoxic treatments, colorectal cancer remains a leading cause of death. Metastatic colorectal cancer (mCRC) patients have a poor prognosis despite improved treatments and more prolonged median survival. Monoclonal antibodies like cetuximab and panitumumab target the epidermal growth factor receptor (EGFR). They play an essential role in the treatment of metastatic colorectal cancer (mCRC) due to their efficacy in multiple phase III clinical trials across multiple treatment lines. It was discovered that anti-EGFR moAbs were only effective for a small number of patients. Mutations in KRAS and NRAS have been identified as biomarkers of drug resistance. New molecular predictors and prognostic markers are used clinically. The K-Ras mutation is the first molecular marker of a lack of response to EGFR-targeted therapy in K-Ras-mutant patients. Validating predictive and prognostic markers will improve cancer treatments. This article examines molecular markers that can predict colorectal cancer prognosis.

Role of cancer-associated fibroblasts in colorectal cancer

Colorectal cancer (CRC) is a malignancy that has a high incidence in all countries around the world. Cancer-associated fibroblasts (CAFs) are a vital component of the tumor microenvironment (TME), playing an important role in the development of CRC. CAFs can release multiple cytokines and exosomes, activating a variety of related signaling pathways and boosting the processes of the invasion, metastasis, metabolism, drug resistance, and immunosuppression in CRC. Thus, CAFs are a prognostic marker and therapeutic target for CRC. Understanding the role and mechanism of CAFs can provide new insights for the treatment of CRC.

Role of cancer-associated fibroblasts in colorectal cancer

Colorectal cancer (CRC) is a malignancy that has a high incidence in all countries around the world. Cancer-associated fibroblasts (CAFs) are a vital component of the tumor microenvironment (TME), playing an important role in the development of CRC. CAFs can release multiple cytokines and exosomes, activating a variety of related signaling pathways and boosting the processes of the invasion, metastasis, metabolism, drug resistance, and immunosuppression in CRC. Thus, CAFs are a prognostic marker and therapeutic target for CRC. Understanding the role and mechanism of CAFs can provide new insights for the treatment of CRC.

Lessons from other fields of medicine, Part 1: Breast cancer

Through the understanding of multiple etiologies, pathologies, and disease progression trajectories, breast cancer shifted historically from a singular malignancy of the breast to a complex of molecular/biological entities, translating into individualized disease-modifying treatments. As a result, this led to various de-escalations of treatment compared with the gold standard in the era preceding systems biology: radical mastectomy. Targeted therapies have minimized morbidity from the treatments and mortality from the disease. Biomarkers further individualized tumor genetics and molecular biology to optimize treatments targeting specific cancer cells. Landmark discoveries in breast cancer management have evolved through histology, hormone receptors, human epidermal growth factor, single-gene prognostic markers, and multigene prognostic markers. Relevant to the reliance on histopathology in neurodegenerative disorders, histopathology evaluation in breast cancer can serve as a marker of overall prognosis rather than predict response to therapies. This chapter reviews the successes and failures of breast cancer research through history, with focus on the transition from a universal approach for all patients to divergent biomarker development and individualized targeted therapies, discussing future areas of growth in the field that may apply to neurodegenerative disorders.

A comprehensive computational analysis to explore the importance of SIGLECs in HCC biology

BACKGROUND

Hepatocellular carcinoma (HCC) is an aggressive, malignant cancer with a complex pathogenesis. However, effective therapeutic targets and prognostic biomarkers are limited. Sorafenib provides delaying cancer progression and survival improvement in advanced HCC. But despite 10 years of research on the clinical application of sorafenib, predictive markers for its therapeutic effect are lacking.

METHODS

The clinical significance and molecular functions of SIGLEC family members were assessed by a comprehensive bioinformatic analysis. The datasets included in this study (ICGC-LIRI-JP, GSE22058 and GSE14520) are mainly based on patients with HBV infections or HBV-related liver cirrhosis. The TCGA, GEO, and HCCDB databases were used to explore the expression of SIGLEC family genes in HCC. The Kaplan-Meier Plotter database was used to evaluate relationships between the expression levels of SIGLEC family genes and prognosis. Associations between differentially expressed genes in the SIGLEC family and tumour-associated immune cells were evaluated using TIMER.

RESULTS

The mRNA levels of most SIGLEC family genes were significantly lower in HCC than in normal tissues. Low protein and mRNA expression levels of SIGLECs were strongly correlated with tumour grade and clinical cancer stage in patients with HCC. Tumour-related SIGLEC family genes were associated with tumour immune infiltrating cells. High SIGLEC expression was significantly related to a better prognosis in patients with advanced HCC treated with sorafenib.

CONCLUSIONS

SIGLEC family genes have potential prognostic value in HCC and may contribute to the regulation of cancer progression and immune cell infiltration. More importantly, our results revealed that SIGLEC family gene expression may be used as a prognostic marker for HCC patients treated with sorafenib.

Carcinoembryonic Antigen, Carbohydrate Antigen 19-9, Cancer Antigen 125, Prostate-Specific Antigen and Other Cancer Markers: A Primer on Commonly Used Cancer Markers

Cancer markers are molecules produced by cancer cells which may serve to identify the presence of cancer. Cancer markers can be differentiated as serum-based, radiology-based and tissue-based, and are one of the most important tools in diagnosing, staging and monitoring of treatment of many cancers. The most used cancer markers are serum cancer markers due to its relative ease and lower cost of testing. However, serum cancer markers have poor mass screening utilization due to poor positive predictive value. Several markers such as prostate-specific antigen (PSA), beta-human chorionic gonadotropin (B-hCG), alpha-fetoprotein (AFP), and lactate dehydrogenase (LDH) are used to aid in diagnosis of cancer in cases of high suspicion. Serum markers such as carcinoembryonic antigen (CEA), AFP, carbohydrate antigen 19-9 (CA 19-9), and 5-hydroxyindoleacetic acid (5-HIAA) play a significant role in assessing disease prognosis as well as response to treatment. This work reviews the role of some of the biomarkers in the diagnosis and treatment of cancer.

Review novel insights into the diagnostic and prognostic function of copeptin in daily clinical practice

As is shown in previous reports, arginine vasopressin (AVP), as one of the most important hormones within circulation in human beings, is of great clinically significance given that it could maintain the body fluid balance and vascular tone. However, the laboratory measurements AVP in daily clinical practice are shown to be difficult and with low accuracy. Concerning on this notion, it is unpractical to use the serum levels of AVP in diagnosing multiple diseases. On the other hand, another key serum biomarker, copeptin, is confirmed as the C-terminal of the AVP precursor which could be released in equal amounts with AVP, resultantly making it as a sensitive marker of arginine vasopressin release. Notably, emerging recent evidence has demonstrated the critical function of copeptin as a clinical indicator, especially in the diagnosis and prognosis of several diseases in diverse organs, such as cardiovascular disease, kidney disease, and pulmonary disease. In addition, copeptin was recently verified to play an important role in diagnosing multiple acute diseases when combined it with other gold standard serum biomarkers, indicating that copeptin could be recognized as a vital disease marker. Herein, in the current review, the functions of copeptin as a new predictive diagnostic and prognostic biomarker of various diseases, according to the most recent studies, are well summarized. Furthermore, the importance of using copeptin as a serum biomarker in diverse medical departments and the impact of this on improving healthcare service is also summarized in the current review.

Advances in understanding of role and mechanism of Hippo signaling pathway in colorectal cancer

Colorectal cancer (CRC) is one of the most common malignant tumors, and most patients have a poor prognosis. Many studies have shown that the Hippo signaling pathway plays a key role in the occurrence and development of CRC by regulating CRC cell proliferation and apoptosis, tumor invasion and metastasis, autophagy, metabolic reprogramming, drug resistance, and other processes. This article reviews the latest progress in research of the expression of key molecules of the Hippo signaling pathway in CRC as well as the understanding of the mechanism by which this pathway regulates the occurrence and development of CRC.

Long-term kidney outcomes in non-dialyzed children with Shiga-toxin Escherichia coli associated hemolytic uremic syndrome

BACKGROUND

Long-term kidney outcomes of non-dialyzed children with Shiga-toxin Escherichia Coli hemolytic uremic syndrome (STEC-HUS) have been scantily studied. Therefore, we aimed to evaluate kidney outcomes and prognostic markers in these patients.

METHODS

Non-dialyzed STEC-HUS patients followed for at least 5 years were included. They were grouped and compared according to kidney status at last visit: complete recovery (CR) or chronic kidney disease (CKD). Predictors of CKD evaluated at diagnosis were sex, age, leukocytes, hematocrit, hemoglobin (Hb), and serum creatinine (sCr). Peak sCr and time of follow-up were also analyzed.

RESULTS

A total of 122 patients (62 female, median age at diagnosis 1.6 years) with a median follow-up of 11.3 years were included. At last visit, 82 (67%) had CR, 36 (30%) had CKD stage 1, and 4 (3%) had stage 2. No patient developed CKD stage 3-5. Median time to CKD was 5 years (IQR 3.1-8.76 years). Of the 122 patients, 18% evolved to CKD in the first 5 years, increasing to 28% at 10 and 33% at 20 years of follow-up. Serum Cr at diagnosis and peak sCr were significantly higher in patients with CKD than in those with CR.

CONCLUSIONS

One third of non-dialyzed STEC-HUS patients evolved to CKD after a median time of 5 years. However, CKD may appear even after 15 years of CR. Serum Cr was significantly higher among patients who evolved to CKD. These data reinforce that all non-dialyzed patients should be followed until adulthood. A higher resolution version of the Graphical abstract is available as Supplementary information.

Investigating sphingolipids as biomarkers for the outcomes of acute ischemic stroke patients receiving endovascular treatment

BACKGROUND

Long-chain ceramides are associated with the mechanisms and clinical outcomes of acute ischemic stroke (AIS). This study aimed to investigate the plasma ceramides and sphingosine-1-phosphate in AIS patients undergoing endovascular thrombectomy (EVT) and their associations with outcomes.

METHODS

Plasma samples were collected from 75 AIS patients who underwent EVT before (T1), immediately after (T2), and 24 h after (T3) the procedures and 19 controls that were matched with age, sex, and co-morbidities. The levels of ceramides with different fatty acyl chain lengths and sphingosine-1-phosphate were measured by UHPLC-ESI-MS/MS. A poor outcome was defined as a modified Rankin Scale score of 3-6 at 3 months after stroke.

RESULTS

The plasma levels of long-chain ceramides Cer (d18:1/16:0) at all three time points, Cer (d18:1/18:0) at T1 and T3, and Cer (d18:1/20:0) at T1 and very-long-chain ceramide Cer (d18:1/24:1) at T1 were significantly higher in AIS patients than those in the controls. In contrast, the plasma levels of sphingosine-1-phosphate in AIS patients were significantly lower than those in the controls at all three time points. Among the AIS patients, 34 (45.3%) had poor functional outcomes at 3 months poststroke. Multivariable analysis showed that higher levels of Cer (d18:1/16:0) and Cer (d18:1/18:0) at all three time points, Cer (d18:1/20:0) at T1 and T2, and Cer (d18:1/24:0) at T2 remained significantly associated with poor functional outcomes after adjustment for potential confounding factors.

CONCLUSION

Plasma ceramides were elevated early in AIS patients with acute large artery occlusion. Furthermore, Cer (d18:1/16:0) and Cer (d18:1/18:0) could be early prognostic indicators for AIS patients undergoing EVT.

Interpretable machine learning prediction of all-cause mortality

Background

Unlike linear models which are traditionally used to study all-cause mortality, complex machine learning models can capture non-linear interrelations and provide opportunities to identify unexplored risk factors. Explainable artificial intelligence can improve prediction accuracy over linear models and reveal great insights into outcomes like mortality. This paper comprehensively analyzes all-cause mortality by explaining complex machine learning models.

Methods

We propose the IMPACT framework that uses XAI technique to explain a state-of-the-art tree ensemble mortality prediction model. We apply IMPACT to understand all-cause mortality for 1-, 3-, 5-, and 10-year follow-up times within the NHANES dataset, which contains 47,261 samples and 151 features.

Results

We show that IMPACT models achieve higher accuracy than linear models and neural networks. Using IMPACT, we identify several overlooked risk factors and interaction effects. Furthermore, we identify relationships between laboratory features and mortality that may suggest adjusting established reference intervals. Finally, we develop highly accurate, efficient and interpretable mortality risk scores that can be used by medical professionals and individuals without medical expertise. We ensure generalizability by performing temporal validation of the mortality risk scores and external validation of important findings with the UK Biobank dataset.

Conclusions

IMPACT's unique strength is the explainable prediction, which provides insights into the complex, non-linear relationships between mortality and features, while maintaining high accuracy. Our explainable risk scores could help individuals improve self-awareness of their health status and help clinicians identify patients with high risk. IMPACT takes a consequential step towards bringing contemporary developments in XAI to epidemiology.

Induction Therapy and Survival for Acute Myeloid Leukemia in Hispanic Adults from Puerto Rico

BACKGROUND

Acute myeloid leukemia (AML) is the most common type of leukemia in adults. There are no previous studies evaluating AML treatment patterns in Puerto Rico. We describe the first-line therapy patterns and survival of patients diagnosed with AML in Puerto Rico using the Puerto Rico Central Cancer Registry Health Insurance Linkage Database (2011-2015).

METHODS

We describe patient characteristics according to intensive, non-intensive, and non-treatment status. We used Cox proportional hazard models to evaluate the factors associated with the risk of death stratified by intensive and non-intensive therapy. For this study, 385 patients with AML were included.

RESULTS

The mean age was 67 years old and 50.1% were female. Nearly half of AML patients (46.8%) received intensive treatment, 23.6% received non-intensive treatment, and 26.2% did not receive treatment. The overall 3-year survival rate was 17.9%. Among those who received intensive therapy, the risk of death among females was lower than males (hazard ratio [HR]: 0.64, 95% confidence interval [CI]: 0.44-0.93). Patients 60 years or older who received intensive treatment had a higher risk of death than younger patients (HR: 1.67, 95% CI: 1.09-2.55). Patients with poor/adverse risk receiving intensive (HR: 3.43, 95% CI: 1.76-6.69) or non-intensive (HR: 4.32, 95% CI: 1.66-11.28) treatment had a higher risk of death than patients with a favorable risk category.

CONCLUSION

Our findings are the first step to monitor the quality of care of patients with AML in Puerto Rico, particularly related to the administration of appropriate induction therapies, which is one of the most important predictors of AML survival.

Serum levels of matrix metalloproteinases as prognostic markers for severe dengue with plasma leakage

BACKGROUND

Plasma leakage is a major pathogenic manifestation of severe dengue and is a precursor of life-threatening complications associated with dengue. Accumulating evidence indicates the role of Matrix Metalloproteinases (MMPs) in mediating vascular permeability and plasma leakage following induction by the dengue virus. This study aims to investigate the utility of MMP-2, MMP-3, and MMP-9 in predicting the severity of dengue infection and further explore the relationship of these markers with the pathogenic factors associated with plasma leakage.

METHODS

The dengue-positive subjects were classified into mild and severe dengue groups based on the manifestation of warning signs. The samples in each group and healthy controls were quantified for basic laboratory characteristics. The levels of MMP-2, MMP-3, MMP-9, and Macrophage migration inhibitory factor (MIF) were estimated in all serum samples using a multiplex bead-based assay.

RESULTS

MMP-2 and MMP-9 were markedly elevated in severe dengue patients compared to mild dengue patients and healthy controls. No alteration in the circulating levels of MMP-3 was observed between the study groups. ROC curve analysis indicated that MMP-2 and MMP-9 exhibited good potential for predicting severe dengue. Notably, an increase in MMP-9 was associated with increased MIF and Hematocrit levels in severe dengue patients.

CONCLUSION

MMP-2 and MMP-9 could serve as prognostic biomarkers for severe dengue. These findings also identify the association of MMP-9 with markers of plasma leakage, thereby encouraging further studies to explore the therapeutic potential of targeting MMP-9 in managing plasma leakage in severe dengue.

Circulating tumor DNA: a help to guide therapeutic strategy in patients with borderline and locally advanced pancreatic adenocarcinoma?

BACKGROUND

prognostic biomarkers could be useful to better select patients with borderline resectable (BR) or locally advanced (LA) pancreatic adenocarcinoma (PA) for chemoradiotherapy (CRT) and/or secondary resection.

AIMS

The main objective of this work was to study characteristics, received treatments and prognostic of patients with BR or LA PA according to their baseline circulating tumor DNA status and, for secondary objective, neutrophil-to-lymphocyte Ratio (NLR).

METHODS

ctDNA status at baseline was determined using Next Generation Sequencing in a consecutive monocentric cohort of patients with a BR or LA PA.

RESULTS

69 patients were included, 31 with BR PA and 38 with LA PA. 14 (20.3%) patients had baseline positive ctDNA. Five (7.8%) patients had NLR> 5. Patients with positive ctDNA had 3.7 months shorter progression free survival (p = 0.006). Patients with positive ctDNA had earlier progression after the beginning of CRT (4.4 vs 7.1 months; p = 0.068) and shorter relapse free survival after secondary resection (9.2 vs 22.9 months; p = 0.016).

CONCLUSIONS

positive ctDNA at baseline was associated with a worse prognosis in patients with BR or LA PA. These data are exploratory and must be confirmed in further prospective trials.

Data-driven analysis of a validated risk score for ovarian cancer identifies clinically distinct patterns during follow-up and treatment

Background

Ovarian cancer is the eighth most common cancer among women and due to late detection prognosis is poor with an overall 5-year survival of 30-50%. Novel biomarkers are needed to reduce diagnostic surgery and enable detection of early-stage cancer by population screening. We have previously developed a risk score based on an 11-biomarker plasma protein assay to distinguish benign tumors (cysts) from malignant ovarian cancer in women with adnexal ovarian mass.

Methods

Protein concentrations of 11 proteins were characterized in plasma from 1120 clinical samples with a custom version of the proximity extension assay. The performance of the assay was evaluated in terms of prediction accuracy based on receiver operating characteristics (ROC) and multiple hypothesis adjusted Fisher's Exact tests on achieved sensitivity and specificity.

Results

The assay's performance is validated in two independent clinical cohorts with a sensitivity of 0.83/0.91 and specificity of 0.88/0.92. We also show that the risk score follows the clinical development and is reduced upon treatment, and increased with relapse and cancer progression. Data-driven modeling of the risk score patterns during a 2-year follow-up after diagnosis identifies four separate risk score trajectories linked to clinical development and survival. A Cox proportional hazard regression analysis of 5-year survival shows that at time of diagnosis the risk score is the second-strongest predictive variable for survival after tumor stage, whereas MUCIN-16 (CA-125) alone is not significantly predictive.

Conclusion

The robust performance of the biomarker assay across clinical cohorts and the correlation with clinical development indicates its usefulness both in the diagnostic work-up of women with adnexal ovarian mass and for predicting their clinical course.

Machine learning based identification of hub genes in renal clear cell carcinoma using multi-omics data

Renal cell carcinoma is one of the most universal urinary system cancers in the world. The most common renal cell carcinoma subtype is renal clear cell carcinoma. It is usually associated with high rates of metastasis and mortality. Therefore, finding effective therapeutic targets and prognostic molecular markers is of great significance to improve the early diagnosis rate and prognostic accuracy of renal clear cell carcinoma. In this work, we successfully identified six hub genes that are closely related to the occurrence, development and prognosis of renal clear cell carcinoma and proposed three new potential prognostic markers, namely ATP4B, AC144831.1 and Tfcp2l1 through differentially expressed genes (DEGs) analysis, GO functional enrichment and KEGG pathway analysis, WGCNA analysis, and survival analysis. In addition, we established machine learning models to predict the occurrence of tumors through the gene expression data of patients. It is expected that the results of this study can provide reference value for the treatment of renal clear cell carcinoma.

The outcome of children placed in a welfare center or foster care before the age of 4: Prognostic factors

BACKGROUND

In child and adolescent psychiatry, many patients are placed in welfare institutions or foster care.

OBJECTIVE

It is important to study their progress in the long term and to examine the psychological and social care arrangements as well as their impacts.

POPULATION AND METHODS

This qualitative study designed to identify potential prognostic factors relating to the outcome of children placed in a welfare center or foster care before the age of 4 years was based on the analysis of 34 case histories of children placed in a welfare center or foster care in Angers. These records involved 129 cases collected for the "Saint Ex" study, a quantitative case study conducted from 1994 to 2001 designed to assess the outcome of children placed in a welfare center or foster care in Angers before the age of 4. The population sampling was purposive and was based on eight subgroups defined by three clinical criteria: Parent-Infant Relationship Global Scale assessment (PIR-GAS) at T1 (admission into welfare center or foster care), the status of a "infant at risk" at T1, and GAF (Global Assessment of Functioning) at T2 (exit from the welfare center or foster care).

RESULTS

The study population included 11 girls and 23 boys. Factors contributing to adverse progression included problems with interactions at a very early age, failure to listen or respond to a child's request regarding his or her placement, long delays between establishing facts and implementing social measures, discontinuity and/or inconsistency regarding the placement arrangements, and sexual abuse. On the other hand, factors contributing to positive progress included the diagnosis and adapted treatment of a mental disorder in the case of one or both parents, early placement in a foster family, considering the child's requests regarding the placement, responsiveness of social services, and psychological or psychiatric follow-up.

CONCLUSION

The analysis of these 34 cases sheds light on several prognostic elements, with the combination of all these factors as the background. Care based on prevention seems essential to protect early interactions and shorten the time that children are exposed to danger.

Making cough count in tuberculosis care

Cough assessment is central to the clinical management of respiratory diseases, including tuberculosis (TB), but strategies to objectively and unobtrusively measure cough are lacking. Acoustic epidemiology is an emerging field that uses technology to detect cough sounds and analyze cough patterns to improve health outcomes among people with respiratory conditions linked to cough. This field is increasingly exploring the potential of artificial intelligence (AI) for more advanced applications, such as analyzing cough sounds as a biomarker for disease screening. While much of the data are preliminary, objective cough assessment could potentially transform disease control programs, including TB, and support individual patient management. Here, we present an overview of recent advances in this field and describe how cough assessment, if validated, could support public health programs at various stages of the TB care cascade.

Zimmer et al. discuss the importance of cough assessment in clinical management of tuberculosis (TB). They describe how acoustic epidemiology, which uses recording devices and artificial intelligence to detect, record and analyze cough, can be used in TB control and individual patient management.

Pan-cancer analysis of tumor mutation burden sensitive tumors reveals tumor-specific subtypes and hub genes related to immune infiltration

BACKGROUND

High tumor mutation burden (TMB) failed to serve as a favorable prognostic biomarker for immunotherapy across all tumors. This study aimed to explore TMB-sensitive tumors on a pan-cancer level and construct their immune infiltration phenotypes in TMB-high groups.

METHODS

Pan-cancer patients were separated into TMB-high and TMB-low groups based on the median TMB values per tumor. TMB-related genes were identified using differently expressed genes (DEGs) and differently mutated genes (DMGs) between the above two TMB groups. CIBERSORT algorithm was used to estimate the abundance of 22 tumor immune infiltrating cells (TIICs). Consensus clustering analysis was applied to predict molecular subtypes. Cox regression analysis was performed to evaluate the correlations between hub genes and TIICs and immunomodulator genes.

RESULTS

Nine TMB-sensitive tumors were identified by high-frequency of TMB-related genes. A total of 126 tumor-specific hub genes (1 in BLCA, 19 in BRCA, 4 in COAD, 4 in HNSC, 25 in LUAD, 2 in LUSC, 27 in SKCM, 37 in STAD, and 7 UCEC) were identified. In five out of nine TMB-sensitive tumors, the molecular subtypes based on hub gene expression were characterized by TMB values, prognostic values and tumor-specific TIICs levels. In TMB-high groups, hub genes associated immune infiltration phenotypes were constructed with key TIICs and immunomodulators spanning TMB-sensitive tumors.

CONCLUSIONS

Our tumor-specific analysis revealed hub genes associated immune infiltration features may serve as potential therapeutic targets and prognostic markers of immunotherapy, providing the potential underlying mechanism of immune infiltration in TMB-high groups across TMB-sensitive tumors.

Evaluate the diagnostic and prognostic value of NUSAP1 in papillary thyroid carcinoma and identify the relationship with genes, proteins, and immune factors

Background

Nucleolar spindle-associated protein 1 (NUSAP1) is reported to be a useful diagnostic and prognostic marker for a variety of cancers, but relevant studies are lacking in papillary thyroid carcinoma (PTC).

Methods

The relationship between NUSAP1 expression and the overall survival (OS) of pan-cancer was examined by GEPIA and KMplot. We explored the relationship between NUSAP1 and clinical PTC data based on the THCA dataset of TCGA and the GEO dataset of NCBI; GO, KEGG analysis, and ceRNA networks were performed on co-expressed genes through LinkedOmics and Starbase. We assessed the relevance between NUSAP1 and the tumor microenvironment using ESTIMATE, correlations between NUSAP1 and immune cells with TIMER, the relationship between NUSAP1 and immunotherapy by TCIA, and small-molecule drugs targeting NUSAP1 that can be discovered using the CMap database.

Results

Higher expression of NUSAP1 in pan-cancer tissues was correlated with shorter OS. NUSAP1 was also significantly expressed in PTC tissues and was an independent prognostic risk factor. Compared to the NUSAP1 low expression group, the NUSAP1 high expression group was more likely to also have lymph node metastasis, pathological PTC type, shorter progression-free survival (PFS), and higher scores for immune checkpoint inhibitor treatment. The genes associated with NUSAP1 were mostly involved in the cell cycle, immune-related pathways, and AITD. Ten lncRNAs (GAS5, SNHG7, UCA1, SNHG1, HCP5, DLEU2, HOTAIR, TP53TG1, SNHG12, C9orf106), eleven miRNAs (hsa-miR-10a-5p, hsa-miR-10b-5p, hsa-miR-18a-5p, hsa-miR-18b-5p, hsa-miR-128-3p, hsa-miR-214-3p, hsa-miR-219a-2-3p, hsa-miR-339-5p, hsa-miR-494-3p, hsa-miR-545-3p, hsa-miR-769-5p), and one mRNA (NUSAP1) were constructed. NUSAP1 participated in the formation of the tumor microenvironment. CMap predicted the 10 most important small molecules about NUSAP1.

Conclusions

In PTC, NUSAP1 shows good diagnostic value and prognostic value; NUSAP1 impacts the cell cycle, immune-related pathways, and AITD and has a complex effect on the tumor microenvironment in PTC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02652-9.

Diagnostic and prognostic values of pyroptosis-related genes for the hepatocellular carcinoma

Background

Due to the high heterogeneity, the early diagnosis and prognostic prediction of hepatic cellular cancer (HCC) is challenging. In this study, we explored the diagnostic and prognostic value of pyroptosis-related genes (PRGs) in HCC. We downloaded the mRNA expression profiles of HCC and the corresponding clinical data from the TCGA and ICGC databases. Fifty-one PRGs were extracted from Genecards, MsigDB, and relevant literature. The area under the receiver operating characteristic (AUC) was used to explore the diagnostic value of the PRGs.

Results

The results revealed that BAK1, BAX, CHMP2A, CHMP4C, CHMP6, GSDMC, and GSDMD had higher diagnostic values for HCC (AUCs > 0.8, P < 0.05). Then, univariate and multivariate analyses of 51 PRGs were performed for HCC samples, and 4 PRGs (TP53, GPX4, GSDMC, BAK1) associated with HCC prognosis were obtained and used to construct a pyroptosis-related risk model. HCC samples were divided into high-risk and low-risk groups based on the risk score’s cut-off. Kaplan–Meier curve and Log-rank test were used to compare the overall survival (OS) of two risk groups. The OS was lower in the high-risk group than in the low-risk group. In addition, the time-dependent receiver operating characteristics revealed that the risk model could be used to predict the prognosis of HCC more accurately. The risk score also resulted as an independent risk factor for HCC prognosis (TCGA: HR = 2.45, 95% CI 1.53–3.92; ICGC: HR = 2.19, 95% CI 1.39–3.46). Moreover, the AUC of the risk score for diagnosing HCC was relatively higher (TCGA: AUC = 0.840, P < 0.05; ICGC: AUC = 0.795, P < 0.05).

Conclusions

In a word, BAK1, BAX, CHMP2A, CHMP4C, CHMP6, GSDMC, GSDMD, and the pyroptosis-related risk model could be used to diagnose the HCC, and the risk score also resulted as an independent risk factor for the HCC prognosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04726-7.

TRF2 cooperates with CTCF for controlling the oncomiR-193b-3p in colorectal cancer

The Telomeric Repeat binding Factor 2 (TRF2), a key protein involved in telomere integrity, is over-expressed in several human cancers and promotes tumor formation and progression. Recently, TRF2 has been also found outside telomeres where it can affect gene expression. Here we provide evidence that TRF2 is able to modulate the expression of microRNAs (miRNAs), small non-coding RNAs altered in human tumors. Among the miRNAs regulated by TRF2, we focused on miR-193b-3p, an oncomiRNA that positively correlates with TRF2 expression in human colorectal cancer patients from The Cancer Genome Atlas dataset. At the mechanistic level, the control of miR-193b-3p expression requires the cooperative activity between TRF2 and the chromatin organization factor CTCF. We found that CTCF physically interacts with TRF2, thus driving the proper positioning of TRF2 on a binding site located upstream the miR-193b-3p host-gene. The binding of TRF2 on the identified region is necessary for promoting the expression of miR-193b3p which, in turn, inhibits the translation of the onco-suppressive methyltransferase SUV39H1 and promotes tumor cell proliferation. The translational relevance of the oncogenic properties of miR-193b-3p was confirmed in patients, in whom the association between TRF2 and miR-193b-3p has a prognostic value.

Multiplex Technologies in COVID-19 Research, Diagnostics, and Prognostics: Battling the Pandemic

Due to continuous technical developments and new insights into the high complexity of infectious diseases such as COVID-19, there is an increasing need for multiplex biomarkers to aid clinical management and support the development of new drugs and vaccines. COVID-19 disease requires rapid diagnosis and stratification to enable the most appropriate treatment course for the best possible outcomes for patients. In addition, these tests should be rapid, specific, and sensitive. They should rule out other potential causes of illness with simultaneous testing for other diseases. Elevated levels of specific biomarkers can be used to establish severity risks of chronic diseases so that patients can be provided the proper medication at the right time. This review describes the state-of-the-art technologies in proteomics, transcriptomics, and metabolomics, for multiplex biomarker approaches in COVID-19 research.

Cutaneous and uveal melanoma: two different cancers in therapeutic needs

Melanocytes are located in various parts of the human body, such as the skin and the eye. Their transformation leads to melanoma, an aggressive and deadly neoplasm. Cutaneous and uveal melanomas show different characteristics, including significant differences in genetic alterations, metastatic sites and therapeutic response. In recent decades, great efforts have been made to obtain a more comprehensive understanding of genetics, genomics and molecular changes, enabling the identification of key cellular processes and signaling pathways in melanomas. Major breakthroughs were realized in the treatment of metastatic cutaneous melanoma, but most patients relapse. Currently, there is no approved systemic treatment for metastatic uveal melanoma. Thus, these two different cancers are in therapeutic need to overcome treatment failure and improve patient prognosis. In this review we discuss on one hand the mutation of MITF, the master gene of melanocyte homeostasis, which we identified as a new melanoma predisposition gene in cutaneous melanoma, and on the other hand the recent findings of intratumor heterogeneity and characterization of cell sub-populations in primary uveal melanomas. These studies offer new tools for early detection and therapeutic targets.