Neopterin as a potential prognostic and predictive biomarker in metastatic renal cell carcinoma treated with immune checkpoint inhibitors

INTRODUCTION

Immunotherapy represents a significant and essential component of renal carcinoma therapy (RCC), but the selection of an optimal regimen for an individual patient remains unclear. Despite significant improvements in therapeutic options for RCC, predictive biomarkers for immunotherapeutic agents remain elusive. Neopterin is a biomarker of cell-mediated immune response, with concentrations increased in different disorders, including cancer. High neopterin levels herald, in general, a poor prognosis.

AREAS COVERED

This review briefly overviews the contemporary clinical data on biomarkers in metastatic RCC therapy, focusing on neopterin.

EXPERT OPINION

Elevated neopterin levels have been observed in tumors of different primary locations. Research indicates that neopterin may serve as a potential biomarker for assessing the inflammatory status associated with certain cancers. However, it is necessary to interpret neopterin levels in the context of a comprehensive clinical evaluation, as elevated neopterin alone is not specific to cancer and can be influenced by other factors, including comorbid conditions. Neopterin has also been identified as a prognostic biomarker. An increasing neopterin level in serum and urine is associated with advanced cancer, but the role as a potential predictor of response to immunotherapy has yet to be established. A reliable biomarker for optimal therapy selection in metastatic RCC is still putative.

Comprehensive analysis of lung adenocarcinoma: Unveiling differential gene expression, survival-linked genes, subtype stratification, and immune landscape implications

This study offers a detailed exploration of lung adenocarcinoma (LUAD), addressing its heterogeneity and treatment challenges through a multi-faceted analysis that includes gene expression, genetic subtyping, pathway analysis, immune assessment, and drug sensitivity. It identifies 165 genes with significant expression differences and 46 genes associated with survival, revealing insights into oxidative stress and autophagy. LUAD samples were divided into three subtypes using consensus clustering on these 46 genes, with distinct survival outcomes. Gene Set Enrichment Analysis (GSEA) on HALLMARK gene sets indicated pathway variations with survival implications. The immune landscape, analyzed using the CIBERSORT algorithm, showed different immune cell distributions across subtypes, with the first subtype exhibiting a better immune environment and survival prospects. Advanced machine learning techniques developed a risk model from a set of four genes, effectively categorizing patients into high and low-risk groups, validated through external datasets and analyses. This model linked lower risk scores to better clinical stages, with a higher mutation rate and potential immunotherapy benefits observed in the high-risk group. Drug sensitivity assessments highlighted varied treatment responses between risk groups, suggesting avenues for personalized therapy. This comprehensive analysis enhances the understanding of LUAD's molecular and clinical nuances, offering valuable insights for tailored treatment approaches.

Deciphering the prognostic landscape of osteosarcoma: Integrating the roles of hippo pathway genes, programmed cell death, and the tumor immune microenvironment

Osteosarcoma is a highly aggressive cancer prevalent among adolescents and young adults, notorious for its tendency to metastasize to the lungs. This research delves into the molecular foundations of osteosarcoma by examining the role of the Hippo signaling pathway and its interaction with the tumor immune microenvironment (TME). Through analysis of transcriptomic data from the TARGET-OS dataset and control samples from GTEx, we identified a set of 131 genes that link high expression profiles in osteosarcoma with the Hippo pathway. A focused examination through univariate Cox regression analysis revealed eight key genes (DLG5, WNT11, TGFB2, DLG4, WNT16, ID2, WNT10B, and WNT10A) with a significant correlation to patient outcomes. Hierarchical clustering of these genes delineated two distinct patient groups with significantly different survival rates, a finding supported by Kaplan-Meier survival analysis. Further investigation into immune cell infiltration and expression profiles of immunoregulatory factors uncovered a notable pattern of immune evasion in the group with poorer prognosis, marked by reduced effector immune cell activity and lower levels of immunostimulatory factors. Single-cell sequencing highlighted the cellular diversity within osteosarcoma samples and identified markers differentiating malignant from nonmalignant cells, correlating these markers with prognostic risk scores. Our results emphasize the critical prognostic value of Hippo pathway genes and the TME in osteosarcoma, shedding light on new avenues for therapeutic intervention and patient-specific treatment strategies.

Identification of novel prognostic autoantibodies in diffuse large B-cell lymphoma treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone via a high-throughput antigen microarray

BACKGROUND

R-CHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone) is a standard first-line treatment for diffuse large B-cell lymphoma (DLBCL). However, 20%-40% of patients survive less than 5 years. Novel prognostic biomarkers remain in demand.

METHODS

Baseline plasma autoantibodies (AAbs) were assessed in 336 DLBCLs. In the discovery phase (n = 20), a high-density antigen microarray (∼21,000 proteins) was used to expound AAb profiles. In the verification phase (n = 181), with a DLBCL-focused microarray, comparative results based on event-free survival at 24 months (EFS24) and lasso Cox regression models of progression-free survival (PFS) and overall survival (OS) were integrated to identify potential biomarkers. They were further validated by enzyme-linked immunosorbent assay in validation phase 1 (n = 135) and a dynamic cohort (n = 12). In validation phase 2, a two-AAb-based risk score was established. They were further validated in an immunohistochemistry cohort (n = 55) and four independent Gene Expression Omnibus datasets (n = 1598).

RESULTS

Four AAbs (CREB1, N4BP1, UBAP2, and DEAF1) were identified that showed associations with EFS24 status (p < .05) and superior PFS and OS (p < .05). A novel risk score model based on CREB1 and N4BP1 AAbs was developed to predict PFS with areas under the curve of 0.72, 0.71, 0.76, and 0.82 at 1, 3, 5, and 7 years, respectively, in DLBCL treated with R-CHOP independent of the International Prognostic Index (IPI) and provided significant additional recurrence risk discrimination (p < .05) for the IPI. CREB1 and N4BP1 proteins and messenger RNAs were also associated with better PFS and OS (p < .05).

CONCLUSIONS

This study identified a novel prognostic panel of CREB1, N4BP1, DEAF1, and UBAP2 AAbs that is independent of the IPI in DLBCL.

The Clinicopathological Significance of the Cyclin D1/E1-Cyclin-Dependent Kinase (CDK2/4/6)-Retinoblastoma (RB1/pRB1) Pathway in Epithelial Ovarian Cancers

Cyclin-dependent kinases (CDK2, CDK4, CDK6), cyclin D1, cyclin E1 and phosphorylated retinoblastoma (pRB1) are key regulators of the G1/S cell cycle checkpoint and may influence platinum response in ovarian cancers. CDK2/4/6 inhibitors are emerging targets in ovarian cancer therapeutics. In the current study, we evaluated the prognostic and predictive significance of the CDK2/4/6-cyclin D1/E1-pRB1 axis in clinical ovarian cancers (OC). The CDK2/4/6, cyclin D1/E1 and RB1/pRB1 protein expression were investigated in 300 ovarian cancers and correlated with clinicopathological parameters and patient outcomes. CDK2/4/6, cyclin D1/E1 and RB1 mRNA expression were evaluated in the publicly available ovarian TCGA dataset. We observed nuclear and cytoplasmic staining for CDK2/4/6, cyclins D1/E1 and RB1/pRB1 in OCs with varying percentages. Increased nuclear CDK2 and nuclear cyclin E1 expression was linked with poor progression-free survival (PFS) and a shorter overall survival (OS). Nuclear CDK6 was associated with poor OS. The cytoplasmic expression of CDK4, cyclin D1 and cyclin E1 also has predictive and/or prognostic significance in OCs. In the multivariate analysis, nuclear cyclin E1 was an independent predictor of poor PFS. Tumours with high nuclear cyclin E1/high nuclear CDK2 have a worse PFS and OS. Detailed bioinformatics in the TCGA cohort showed a positive correlation between cyclin E1 and CDK2. We also showed that cyclin-E1-overexpressing tumours are enriched for genes involved in insulin signalling and release. Our data not only identified the prognostic/predictive significance of these key cell cycle regulators but also demonstrate the importance of sub-cellular localisation. CDK2 targeting in cyclin-E1-amplified OCs could be a rational approach.

Predictive and Prognostic Biomarkers in Patients With Mycosis Fungoides and Sézary Syndrome (BIO-MUSE): Protocol for a Translational Study

BACKGROUND

Cutaneous T-cell lymphoma (CTCL) is a rare group of lymphomas that primarily affects the skin. Mycosis fungoides (MF) is the most common form of CTCL and Sézary syndrome (SS) is more infrequent. Early stages (IA-IIA) have a favorable prognosis, while advanced stages (IIB-IVB) have a worse prognosis. Around 25% of patients with early stages of the disease will progress to advanced stages. Malignant skin-infiltrating T-cells in CTCL are accompanied by infiltrates of nonmalignant T-cells and other immune cells that produce cytokines that modulate the inflammation. Skin infection, often with Staphylococcus aureus, is frequent in advanced stages and can lead to sepsis and death. S. aureus has also been reported to contribute to the progression of the disease. Previous reports indicate a shift from Th1 to Th2 cytokine production and dysfunction of the skin barrier in CTCL. Treatment response is highly variable and often unpredictable, and there is a need for new predictive and prognostic biomarkers.

OBJECTIVE

This prospective translational study aims to identify prognostic biomarkers in the blood and skin of patients with MF and SS.

METHODS

The Predictive and Prognostic Biomarkers in Patients With MF and SS (BIO-MUSE) study aims to recruit 120 adult patients with MF or SS and a control group of 20 healthy volunteers. The treatments will be given according to clinical routine. The sampling of each patient will be performed every 3 months for 3 years. The blood samples will be analyzed for lactate dehydrogenase, immunoglobulin E, interleukins, thymus and activation-regulated chemokine, and lymphocyte subpopulations. The lymphoma microenvironment will be investigated through digital spatial profiling and single-cell RNA sequencing. Microbiological sampling and analysis of skin barrier function will be performed. The life quality parameters will be evaluated. The results will be evaluated by the stage of the disease.

RESULTS

Patient inclusion started in 2021 and is still ongoing in 2023, with 18 patients and 20 healthy controls enrolled. The publication of selected translational findings before the publication of the main results of the trial is accepted.

CONCLUSIONS

This study aims to investigate blood and skin with a focus on immune cells and the microbiological environment to identify potential new prognostic biomarkers in MF and SS.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04904146; https://www.clinicaltrials.gov/study/NCT04904146.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/55723.

Bioinformatics-driven identification of prognostic biomarkers in kidney renal clear cell carcinoma

Renal cell carcinoma (RCC), particularly the clear cell subtype (ccRCC), poses a significant global health concern due to its increasing prevalence and resistance to conventional therapies. Early detection of ccRCC remains challenging, resulting in poor patient survival rates. In this study, we employed a bioinformatic approach to identify potential prognostic biomarkers for kidney renal clear cell carcinoma (KIRC). By analyzing RNA sequencing data from the TCGA-KIRC project, differentially expressed genes (DEGs) associated with ccRCC were identified. Pathway analysis utilizing the Qiagen Ingenuity Pathway Analysis (IPA) tool elucidated key pathways and genes involved in ccRCC dysregulation. Prognostic value assessment was conducted through survival analysis, including Cox univariate proportional hazards (PH) modeling and Kaplan-Meier plotting. This analysis unveiled several promising biomarkers, such as MMP9, PIK3R6, IFNG, and PGF, exhibiting significant associations with overall survival and relapse-free survival in ccRCC patients. Cox multivariate PH analysis, considering gene expression and age at diagnosis, further confirmed the prognostic potential of MMP9, IFNG, and PGF genes. These findings enhance our understanding of ccRCC and provide valuable insights into potential prognostic biomarkers that can aid healthcare professionals in risk stratification and treatment decision-making. The study also establishes a foundation for future research, validation, and clinical translation of the identified prognostic biomarkers, paving the way for personalized approaches in the management of KIRC.

Unveiling NRlncRNAs as prognostic biomarkers and therapeutic targets for head-and-neck squamous cell carcinoma through machine learning

Head-and-neck squamous cell carcinoma (HNSCC) patients often exhibit insensitivity to immunotherapy, leading to treatment failure. Identifying potential biomarkers that can predict prognosis and improve the efficacy of treatment is crucial. In this study, we aimed to identify necroptosis-related long noncoding RNAs (NRlncRNAs) as potential therapeutic targets to improve the prognosis of HNSCC patients. By exploring the Genotype-Tissue Expression Project (GTEx) and the Cancer Genome Atlas (TCGA) databases, we identified NRlncRNAs and developed a risk model comprising 17 NRlncRNAs to predict the prognosis of HNSCC patients and to classify patients into two clusters based on their expression levels. We conducted various analyses, such as the Kaplan-Meier analysis, GSEA and IC50 prediction, to evaluate the differences in sensitivity to immunotherapy between the two clusters. Our findings suggest that NRlncRNAs have potential as therapeutic targets for improving the prognosis of HNSCC patients, and that individualized treatment approaches based on NRlncRNA expression levels can improve the sensitivity of immunotherapy and overall treatment outcomes. This study highlights new perspectives within clinical cancer informatics and provides insight into potential therapeutic strategies for HNSCC patients.

Prognostic value of histopathologic traits independent of stromal tumor-infiltrating lymphocyte levels in chemotherapy-naïve patients with triple-negative breast cancer

BACKGROUND

In the absence of prognostic biomarkers, most patients with early-stage triple-negative breast cancer (eTNBC) are treated with combination chemotherapy. The identification of biomarkers to select patients for whom treatment de-escalation or escalation could be considered remains an unmet need. We evaluated the prognostic value of histopathologic traits in a unique cohort of young, (neo)adjuvant chemotherapy-naïve patients with early-stage (stage I or II), node-negative TNBC and long-term follow-up, in relation to stromal tumor-infiltrating lymphocytes (sTILs) for which the prognostic value was recently reported.

MATERIALS AND METHODS

We studied all 485 patients with node-negative eTNBC from the population-based PARADIGM cohort which selected women aged <40 years diagnosed between 1989 and 2000. None of the patients had received (neo)adjuvant chemotherapy according to standard practice at the time. Associations between histopathologic traits and breast cancer-specific survival (BCSS) were analyzed with Cox proportional hazard models.

RESULTS

With a median follow-up of 20.0 years, an independent prognostic value for BCSS was observed for lymphovascular invasion (LVI) [adjusted (adj.) hazard ratio (HR) 2.35, 95% confidence interval (CI) 1.49-3.69], fibrotic focus (adj. HR 1.61, 95% CI 1.09-2.37) and sTILs (per 10% increment adj. HR 0.75, 95% CI 0.69-0.82). In the sTILs <30% subgroup, the presence of LVI resulted in a higher cumulative incidence of breast cancer death (at 20 years, 58%; 95% CI 41% to 72%) compared with when LVI was absent (at 20 years, 32%; 95% CI 26% to 39%). In the ≥75% sTILs subgroup, the presence of LVI might be associated with poor survival (HR 11.45, 95% CI 0.71-182.36, two deaths). We confirm the lack of prognostic value of androgen receptor expression and human epidermal growth factor receptor 2 -low status.

CONCLUSIONS

sTILs, LVI and fibrotic focus provide independent prognostic information in young women with node-negative eTNBC. Our results are of importance for the selection of patients for de-escalation and escalation trials.

Promoter DNA methylation patterns in oral, laryngeal and oropharyngeal anatomical regions are associated with tumor differentiation, nodal involvement and survival

Differentially methylated regions (DMRs) can be used as head and neck squamous cell carcinoma (HNSCC) diagnostic, prognostic and therapeutic targets in precision medicine workflows. DNA from 21 HNSCC and 10 healthy oral tissue samples was hybridized to a genome-wide tiling array to identify DMRs in a discovery cohort. Downstream analyses identified differences in promoter DNA methylation patterns in oral, laryngeal and oropharyngeal anatomical regions associated with tumor differentiation, nodal involvement and survival. Genome-wide DMR analysis showed 2,565 DMRs common to the three subsites. A total of 738 DMRs were unique to laryngeal cancer (n=7), 889 DMRs were unique to oral cavity cancer (n=10) and 363 DMRs were unique to pharyngeal cancer (n=6). Based on the genome-wide analysis and a Gene Ontology analysis, 10 candidate genes were selected to test for prognostic value and association with clinicopathological features. TIMP3 was associated with tumor differentiation in oral cavity cancer (P=0.039), DAPK1 was associated with nodal involvement in pharyngeal cancer (P=0.017) and PAX1 was associated with tumor differentiation in laryngeal cancer (P=0.040). A total of five candidate genes were selected, DAPK1, CDH1, PAX1, CALCA and TIMP3, for a prevalence study in a larger validation cohort: Oral cavity cancer samples (n=42), pharyngeal cancer tissues (n=25) and laryngeal cancer samples (n=52). PAX1 hypermethylation differed across HNSCC anatomic subsites (P=0.029), and was predominantly detected in laryngeal cancer. Kaplan-Meier survival analysis (P=0.043) and Cox regression analysis of overall survival (P=0.001) showed that DAPK1 methylation is associated with better prognosis in HNSCC. The findings of the present study showed that the HNSCC subsites oral cavity, pharynx and larynx display substantial differences in aberrant DNA methylation patterns, which may serve as prognostic biomarkers and therapeutic targets.

Prognostic Value of Inflammatory Burden Index in Advanced Gastric Cancer Patients Undergoing Multimodal Treatment

Since increasing evidence underlines the prominent role of systemic inflammation in carcinogenesis, the inflammation burden index (IBI) has emerged as a promising biomarker to estimate survival outcomes among cancer patients. The IBI has only been validated in Eastern gastric cancer (GC) patients; therefore, the aim of this study was to evaluate the IBI as a prognostic biomarker in Central European GC patients undergoing multimodal treatment. Ninety-three patients with histologically confirmed GC who underwent multimodal treatment between 2013 and 2021 were included. Patient recruitment started with the standardization of neoadjuvant chemotherapy (NAC). Blood samples were obtained one day prior to surgical treatment. The textbook outcome (TO) served as the measure of surgical quality, and tumor responses to NAC were evaluated according to Becker's system tumor regression grade (TRG). A high IBI was associated with an increased risk of postoperative complications (OR 2.95, 95% CI 1.13-7.72). In multivariate analysis, a high IBI (HR = 2.56, 95% CI 1.28-5.13) and a high neutrophil-to-lymphocyte ratio (NLR, HR = 2.55, 95% CI 1.32-4.94) were associated with an increased risk of death, while NAC administration (HR = 0.40, 95% CI 0.18-0.90) and TO achievement (HR = 0.42, 95% CI 0.22-0.81) were associated with a lower risk of death. The IBI was associated with postoperative complications and mortality among GC patients undergoing multimodal treatment.

Inflammation-related molecular signatures involved in the anticancer activities of brigatinib as well as the prognosis of EML4-ALK lung adenocarcinoma patient

Although ALK tyrosine kinase inhibitors (ALK-TKIs) have shown remarkable benefits in EML4-ALK positive NSCLC patients compared to conventional chemotherapy, the optimal sequence of ALK-TKIs treatment remains unclear due to the emergence of primary and acquired resistance and the lack of potential prognostic biomarkers. In this study, we systematically explored the validity of sequential ALK inhibitors (alectinib, lorlatinib, crizotinib, ceritinib and brigatinib) for a heavy-treated patient with EML4-ALK fusion via developing an in vitro and in vivo drug testing system based on patient-derived models. Based on the patient-derived models and clinical responses of the patient, we found that crizotinib might inhibit proliferation of EML4-ALK positive tumors resistant to alectinib and lorlatinib. In addition, NSCLC patients harboring the G1269A mutation, which was identified in alectinib, lorlatinib and crizotinib-resistant NSCLC, showed responsiveness to brigatinib and ceritinib. Transcriptomic analysis revealed that brigatinib suppressed the activation of multiple inflammatory signaling pathways, potentially contributing to its anti-tumor activity. Moreover, we constructed a prognostic model based on the expression of IL6, CXCL1, and CXCL5, providing novel perspectives for predicting prognosis in EML4-ALK positive NSCLC patients. In summary, our results delineate clinical responses of sequential ALK-TKIs treatments and provide insights into the mechanisms underlying the superior effects of brigatinib in patients harboring ALKG1269A mutation and resistant towards alectinib, lorlatinib and crizotinib. The molecular signatures model based on the combination of IL6, CXCL1 and CXCL5 has the potential to predict prognosis of EML4-ALK positive NSCLC patients.

Investigation of the Proteasome 26S Subunit, ATPase Family Genes as Potential Prognostic Biomarkers and Therapeutic Targets for Hepatocellular Carcinoma

Background

Several studies suggest that Proteasome 26S Subunit, ATPase (PSMC) family genes are of great importance in tumor progression and spreading, but the study for systematic evaluation of the function of PSMC genes in hepatocellular carcinoma (HCC) is currently lacking.

Methods

The functions of PSMC genes in HCC were analyzed using multiple online databases, including the TCGA database, GEO database, HPA database, cBioPortal database, DAVID, and KEGG pathway. Experiments were later conducted to verify PSMC expression.

Results

High levels of PSMC gene expression were detected in HCC tissues and PSMCs exhibited potentially powerful abilities in diagnosing HCC patients. All PSMC proteins are expressed to varying degrees in HCC tissues and high expression of the PSMC genes lead to poor prognosis in patients with HCC. Moreover, DNA methylation involves the regulation of the expression of PSMC2 and PSMC5 in HCC, and the levels of methylation of PSMC2 or PSMC5 correlate positively with patient overall survival in HCC patients. The copy number alteration and mutation of PSMC genes were observed and related to the expression of PSMCs in HCC. Functional enrichment analysis showed that many highly co-expressed genes of PSMCs had a potential role in tumor progression and metastasis, which merited further in-depth study. Functional network analysis also suggests that the primary biological function of PSMC genes is the regulation of protein homeostasis and energy metabolism in HCC. Moreover, the expression levels of PSMCs are related to immune cell infiltrates and immunomodulatory factors in HCC.

Conclusion

Our study indicates that PSMC genes are the potential target for precision immunotherapy and novel prognostic biomarkers for HCC.

m6A mRNA Modifications in Glioblastoma: Emerging Prognostic Biomarkers and Therapeutic Targets

Glioblastoma, the most common and aggressive primary brain tumor, is highly invasive and neurologically destructive. The mean survival for glioblastoma patients is approximately 15 months and there is no effective therapy to significantly increase survival times to date. The development of effective therapy including mechanism-based therapies is urgently needed. At a molecular biology level, N6-methyladenine (m6A) mRNA modification is the most abundant posttranscriptional RNA modification in mammals. Recent studies have shown that m6A mRNA modifications affect cell survival, cell proliferation, invasion, and immune evasion of glioblastoma. In addition, m6A mRNA modifications are critical for glioblastoma stem cells, which could initiate the tumor and lead to therapy resistance. These findings implicate the function of m6A mRNA modification in tumorigenesis and progression, implicating its value in prognosis and therapies of human glioblastoma. This review focuses on the potential clinical significance of m6A mRNA modifications in prognostic and therapeutics of glioblastoma. With the identification of small-molecule compounds that activate or inhibit components of m6A mRNA modifications, a promising novel approach for glioblastoma therapy is emerging.

PLAU and GREM1 are prognostic biomarkers for predicting immune response in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a common malignant tumor. Identification of biomarkers and understanding their potential functions will facilitate the treatment and diagnosis in LUAD patients. The yellow module (cor = 0.31, P = 2e-6) was selected as the core module based on weighted gene co-expression network analysis (WGCNA) by integrating RNA-seq data and tumor stage. Two upregulated genes (PLAU and GREM1) in yellow module were identified to be biomarkers. Kaplan-Meier curve analysis displayed that high expression levels of them had a poor overall survival (OS). And, their high expression levels revealed higher tumor stage and relapse possibility in LUAD patients, and could be a prognostic parameter. Both biomarkers showed similar immune cell expression profiles in low- and high-expression groups. Strongly positive correlation between both biomarkers and biomarkers of tumor-infiltrating lymphocytes were also clarified in TCGA-LUAD cohort. Importantly, single gene GSEA showed that transcriptional mis-regulation in cancer and microRNAs in cancer were enriched in LUAD patients. Therefore, a miRNA-mRNA-transcription factors (TFs) co-expression regulatory networks was constructed for each biomarker, various miRNAs and TFs were related to PLAU and GREM1. Among which, 6 downstream TFs were overlapped genes for both biomarkers. Notably, 2 of these TFs (FOXF1 and TFAP2A) exhibited significantly abnormal expression levels. Among which, FOXF1 was downregulated and TFAP2A was upregulated in TCGA-LUAD cohort. Both TFs showed a significantly positive correlation with the expression level of PLAU. In conclusion, we identified 2 biomarkers related to immune response and achieved a good accuracy in predicting OS in patients with LUAD.

Prognostic Thresholds of Mitotic Count and Ki-67 Labeling Index for Recurrence and Survival in Lung Atypical Carcinoids

Atypical carcinoid (AC) is a rare neuroendocrine neoplasm of the lung, which exhibits a varying malignant potential. In this study, we aimed to identify the prognostic thresholds of the mitotic count and Ki-67 labeling index for recurrence and survival in AC. We retrospectively reviewed 78 patients who had been radically resected for AC and calculated said thresholds using time-dependent receiver operating characteristic curves and the Youden index. We then dichotomized the patients into groups of above or below these thresholds and estimated the cumulative incidences of the groups using the Aalen-Johansen estimator. We compared the groups using univariable and multivariable Fine-Gray subdistribution hazard models. Our findings show that more patients recurred and died from this disease if their mitotic count exceeded three and four mitoses per 2 mm2, respectively, or if their Ki-67 labeling index exceeded 14% and 11%, respectively. Both thresholds independently predicted survival (p < 0.001 and p = 0.015, respectively). These thresholds may serve as a valuable tool for clinicians and researchers in making treatment plans and predicting outcomes for patients with AC.

Association between immune-related hub genes CD36, CXCL13, FGFR4, GABBR1, LAMP3, MMP12, and PPM1H and colorectal cancer prognosis

The present study aims to identify immune-related prognostic genes in colorectal cancer (CRC), and to explore potential mechanisms through which these genes regulate CRC progression. We first constructed a prognostic risk model based on seven gene signatures [cluster of differentiation-36 (CD36), chemokine (C-X-C-motif) ligand 13 (CXCL13), fibroblast growth factor receptor 4 (FGFR4), gamma-amino-butyric acid type B receptor 1 (GABBR1), lysosome-associated membrane glycoprotein 3 (LAMP3), recombinant matrix metalloproteinase 12 (MMP12), and protein phosphatase 1H (PPM1H)] using integrated bioinformatic analyses. FGFR4, GABBR1, and LAMP3 were highly expressed in CRC cell lines (in comparison with a normal colonic epithelial cell line), while CD36, CXCL13, MMP12, and PPM1H were weakly expressed. These in vitro expression results were largely consistent with our bioinformatic analysis. A prognostic model was generated to identify a high-risk group with worse survival outcome based on Kaplan-Meier analysis. Our prognostic model showed superior accuracy in both the training and test cohorts. In addition, we found that the low-risk subgroup exhibited greater infiltration by M1 macrophages, CD8+ T cells, CD4+ T cells, and activated NK cells. In conclusion, our findings provide evidence that seven immune-related hub genes can be considered as gene signatures to predict CRC prognosis and to differentiate CRC patient benefit, ultimately serving as a guide for individualized immunotherapy.

Downregulation of Serum miR-133b and miR-206 Associate with Clinical Outcomes of Progression as Monitoring Biomarkers for Metastasis Colorectal Cancer Patients

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer in the world. Non-coding RNAs or microRNAs (miRNAs; miRs) biomarkers can play a role in cancer carcinogenesis and progression. Specific KRAS and EGFR mutation are associated with CRC development playing a role in controlling the cellular process as epigenetic events. Circulating serum miRs can serve for early diagnosis, monitoring, and prognosis of CRC as biomarkers but it is still unclear, clinically.

OBJECTIVE

To determine potential biomarkers of circulating serum miR-133b and miR-206 in CRC patients Methods: Bioinformatic prediction of microRNA was screened followed by TargetScanHu-man7.2, miRTar2GO, miRDB, MiRanda, and DIANA-microT-CDS. Forty-four CRC serum (19 locally advanced, 23 distant advanced CRC) and 12 normal serum samples were subsequently extracted for RNA isolation, cDNA synthesis, and miR validation. The candidate circulating serum miR-133b and miR-206 were validated resulting in a relative expression via quantitative RT-PCR. Relative expression was normalized to the spike-internal control and compared to normal samples as 1 using the 2-ΔΔCt method in principle.

RESULTS

Our results represented 9 miRs of miR-206, miR-155-5p, miR-143-3p, miR-193a-3p, miR-30a-5p, miR-30d-5p, miR-30e-5p, miR-543, miR-877-5p relate to KRAS-specific miRs, whereas, 9 miRs of miR-133b, miR-302a-3p, miR-302b-3p, miR-302d-3p, miR-302e, miR-520a-3p, miR-520b, miR-520c-3p and miR-7-5p relevance to EGFR-specific miRs by using the bioinformatic prediction tools. Our results showed a decreased expression level of circulating serum miR-133b as well as miR-206 associating with CRC patients (local and advanced metastasis) when compared to normal (P < 0.05), significantly.

CONCLUSION

The circulating serum miR-133b and miR-206 can serve as significant biomarkers for monitoring the clinical outcome of progression with metastatic CRC patients. Increased drug-responsive CRC patients associated with crucial molecular intervention should be further explored, clinically.

Identification and validation of a prognostic risk-scoring model for AML based on m7G-associated gene clustering

Background

Acute myeloid leukemia (AML) patients still suffer from poor 5-year survival and relapse after remission. A better prognostic assessment tool is urgently needed. New evidence demonstrates that 7-methylguanosine (m7G) methylation modifications play an important role in AML, however, the exact role of m7G-related genes in the prognosis of AML remains unclear.

Methods

The study obtained AML expression profiles and clinical information from TCGA, GEO, and TARGET databases. Using the patient data from the TCGA cohort as the training set. Consensus clustering was performed based on 29 m7G-related genes. Survival analysis was performed by KM curves. The subgroup characteristic gene sets were screened using WGCNA. And tumor immune infiltration correlation analysis was performed by ssGSEA.

Results

The patients were classified into 3 groups based on m7G-related genebased cluster analysis, and the differential genes were screened by differential analysis and WGCNA. After LASSO regression analysis, 6 characteristic genes (including CBR1, CCDC102A, LGALS1, RD3L, SLC29A2, and TWIST1) were screened, and a prognostic risk-score model was constructed. The survival rate of low-risk patients was significantly higher than that of high-risk patients (p < 0.0001). The area under the curve values at 1, 3, and 5 years in the training set were 0.871, 0.874, and 0.951, respectively, indicating that this predictive model has an excellent predictive effect. In addition, after univariate and multivariate Cox regression screening, histograms were constructed with clinical characteristics and prognostic risk score models to better predict individual survival. Further analysis showed that the prognostic risk score model was associated with immune cell infiltration.

Conclusion

These findings suggest that the scoring model and essential risk genes could provide potential prognostic biomarkers for patients with acute myeloid leukemia.

Pathologic and immunohistochemical prognostic markers in residual triple-negative breast cancer after neoadjuvant chemotherapy

Background

The persistence of residual tumour after neoadjuvant chemotherapy (NAC) in localised triple-negative breast cancer (TNBC) is known to have a negative prognostic value. However, different degrees of expression of some immunohistochemical markers may correlate with different prognoses.

Methods

The expression of biomarkers with a known prognostic value, i.e., cytokeratin 5/6 (CK5/6), androgen receptor (AR), epidermal growth factor receptor (EGFR) proliferation-related nuclear antigen Ki-67, human epidermal growth factor receptor 2 (HER2), protein 53 (p53), forkhead box protein 3 (FOXP3), and cluster differentiation 8 (CD8), was analysed by immunohistochemistry in 111 samples after NAC in non-metastatic TNBC patients addressed to Georges-François Leclerc Cancer Centre Dijon, France. Clinical and pathological variables were retrospectively collected. Cox regression was used to identify immunohistochemical (IHC) and clinicopathological predictors of event-free survival (EFS) (relapse or death).

Results

Median age was 50.4 years (range 25.6-88.3), 55.9% (n = 62) were non-menopausal, 70 (63.1%) had stage IIA-IIB disease. NAC was mostly sequential anthracycline-taxanes (72.1%), and surgical intervention was principally conservative (51.3%). We found 65.7% ypT1, 47.2% lymph node involvement (ypN+), and 29.4% lymphovascular invasion (LVI). Most residual tumours were EGFR >110 (H-score) (60.5%, n = 66), AR ≥4% (53.2%, n = 58), p53-positive mutated (52.7%, n = 58), CD8 ≥26 (58.1%, n = 61), FOXP3 ≥7 (51.4%, n = 54), more than half in the stroma, and 52.3% (n = 58) HER2 score 0. After a median follow-up of 80.8 months, 48.6% had relapsed. Median EFS was 62.3 months (95% CI, 37.2-not reached (NR)). Factors independently associated with poor EFS were AR-low (p = 0.002), ypN+ (p < 0.001), and LVI (p = 0.001). Factors associated with lower overall survival (OS) were EGFR-low (p = 0.041), Ki-67 high (p = 0.024), and ypN+ (p < 0.001).

Conclusion

Post-NAC residual disease in TNBC showed biomarkers specific to a basal-like subtype and markers of lymphocyte infiltration mostly present in the stroma. Prognostic markers for EFS were AR, LVI, and ypN and warrant further validation in a prognostic model.

Establishment of a pathomic-based machine learning model to predict CD276 (B7-H3) expression in colon cancer

CD276 is a promising prognostic indicator and an attractive therapeutic target in various malignancies. However, current methods for CD276 detection are time-consuming and expensive, limiting extensive studies and applications of CD276. We aimed to develop a pathomic model for CD276 prediction from H&E-stained pathological images, and explore the underlying mechanism of the pathomic features by associating the pathomic model with transcription profiles. A dataset of colon adenocarcinoma (COAD) patients was retrieved from the Cancer Genome Atlas (TCGA) database. The dataset was divided into the training and validation sets according to the ratio of 8:2 by a stratified sampling method. Using the gradient boosting machine (GBM) algorithm, we established a pathomic model to predict CD276 expression in COAD. Univariate and multivariate Cox regression analyses were conducted to assess the predictive performance of the pathomic model for overall survival in COAD. Gene Set Enrichment Analysis (GESA) was performed to explore the underlying biological mechanisms of the pathomic model. The pathomic model formed by three pathomic features for CD276 prediction showed an area under the curve (AUC) of 0.833 (95%CI: 0.784-0.882) in the training set and 0.758 (95%CI: 0.637-0.878) in the validation set, respectively. The calibration curves and Hosmer-Lemeshow goodness of fit test showed that the prediction probability of high/low expression of CD276 was in favorable agreement with the real situation in both the training and validation sets (P=0.176 and 0.255, respectively). The DCA curves suggested that the pathomic model acquired high clinical benefit. All the subjects were categorized into high pathomic score (PS) (PS-H) and low PS (PS-L) groups according to the cutoff value of PS. Univariate and multivariate Cox regression analysis indicated that PS was a risk factor for overall survival in COAD. Furthermore, through GESA analysis, we found several immune and inflammatory-related pathways and genes were associated with the pathomic model. We constructed a pathomics-based machine learning model for CD276 prediction directly from H&E-stained images in COAD. Through integrated analysis of the pathomic model and transcriptomics, the interpretability of the pathomic model provide a theoretical basis for further hypothesis and experimental research.

High CTLA-4 transcriptomic expression correlates with high expression of other checkpoints and with immunotherapy outcome

Background

CTLA-4 impedes the immune system's antitumor response. There are two Food and Drug Administration-approved anti-CTLA-4 agents - ipilimumab and tremelimumab - both used together with anti-PD-1/PD-L1 agents.

Objective

To assess the prognostic implications and immunologic correlates of high CTLA-4 in tumors of patients on immunotherapy and those on non-immunotherapy treatments.

Design/methods

We evaluated RNA expression levels in a clinical-grade laboratory and clinical correlates of CTLA-4 and other immune checkpoints in 514 tumors, including 489 patients with advanced/metastatic cancers and full outcome annotation. A reference population (735 tumors; 35 histologies) was used to normalize and rank transcript abundance (0-100 percentile) to internal housekeeping gene profiles.

Results

The most common tumor types were colorectal (140/514, 27%), pancreatic (55/514, 11%), breast (49/514, 10%), and ovarian cancers (43/514, 8%). Overall, 87 of 514 tumors (16.9%) had high CTLA-4 transcript expression (⩾75th percentile rank). Cancers with the largest proportion of high CTLA-4 transcripts were cervical cancer (80% of patients), small intestine cancer (33.3%), and melanoma (33.3%). High CTLA-4 RNA independently/significantly correlated with high PD-1, PD- L2, and LAG3 RNA levels (and with high PD-L1 in univariate analysis). High CTLA-4 RNA expression was not correlated with survival from the time of metastatic disease [N = 272 patients who never received immune checkpoint inhibitors (ICIs)]. However, in 217 patients treated with ICIs (mostly anti-PD-1/anti-PD- L1), progression-free survival (PFS) and overall survival (OS) were significantly longer among patients with high versus non-high CTLA-4 expression [hazard ratio, 95% confidence interval: 0.6 (0.4-0.9) p = 0.008; and 0.5 (0.3-0.8) p = 0.002, respectively]; results were unchanged when 18 patients who received anti-CTLA-4 were omitted. Patients whose tumors had high CTLA-4 and high PD-L1 did best; those with high PD-L1 but non-high CTLA-4 and/or other expression patterns had poorer outcomes for PFS (p = 0.004) and OS (p = 0.009) after immunotherapy.

Conclusion

High CTLA-4, especially when combined with high PD-L1 transcript expression, was a significant positive predictive biomarker for better outcomes (PFS and OS) in patients on immunotherapy.

Genomic instability-associated two-miRNA signature as a novel prognostic biomarker in breast cancer

BACKGROUND

Breast cancer (BC) is the most common cancer among women worldwide and a leading cause of cancer-associated deaths among women. However, there is a lack of accurate prognostic biomarkers for BC. In the present study, we aimed to identify a genomic instability (GI)-associated microRNA signature as a novel potential prognostic biomarker in BC.

METHODS

We performed an integrative analysis to investigate the relationship between GI and BC and identify GI-associated microRNAs (miRNAs). Subsequently, we conducted a discovery and validation study using multicenter cohorts. The GI-associated miRNA signature was developed in the discovery cohort and independently validated in internal and external cohorts.

RESULTS

GI-associated miRNAs expression in BC showed heterogeneity and was significantly correlated with BC prognosis. We identified a GI-associated two-miRNA signature (miR-105-5p and miR-767-5p), termed GI2miR, that stratified BC patients into high-risk and low-risk groups with significantly different clinical outcomes (log-rank p = 0.027) in The Cancer Genome Atlas (TCGA) discovery cohort (n = 763). The prognostic value of GI2miR was further validated in internal TCGA validation cohort (n = 253) (log-rank p = 0.035) and independent GSE22216 cohort (n = 210) (log-rank p = 0.036). The GI2miR demonstrated independent prognostic value in multivariate Cox proportional hazard regression analyses and stratification analysis.

CONCLUSIONS

We have developed a novel prognostic signature based on GI-associated two miRNAs for BC, which may lay the foundation for BC to improve prognosis prediction.

Expression of 3q Oncogene SEC62 Predicts Survival in Head and Neck Squamous Cell Carcinoma Patients Treated with Primary Chemoradiation

Primary chemoradiotherapy (CRT) is an established treatment option for locally advanced head and neck squamous cell carcinomas (HNSCC) usually combining intensity modified radiotherapy with concurrent platinum-based chemotherapy. Though the majority of patients can be cured with this regimen, treatment response is highly heterogeneous and can hardly be predicted. SEC62 represents a metastasis stimulating oncogene that is frequently overexpressed in various cancer entities and is associated with poor outcome. Its role in HNSCC patients undergoing CRT has not been investigated so far. A total of 127 HNSCC patients treated with primary CRT were included in this study. The median follow-up was 5.4 years. Pretherapeutic tissue samples of the primary tumors were used for immunohistochemistry targeting SEC62. SEC62 expression, clinical and histopathological parameters, as well as patient outcome, were correlated in univariate and multivariate survival analyses. High SEC62 expression correlated with a significantly shorter overall survival (p = 0.015) and advanced lymph node metastases (p = 0.024). Further significant predictors of poor overall and progression-free survival included response to therapy (RECIST1.1), nodal status, distant metastases, tobacco consumption, recurrence of disease, and UICC stage. In a multivariate Cox hazard proportional regression analysis, only SEC62 expression (p = 0.046) and response to therapy (p < 0.0001) maintained statistical significance as independent predictors of the patients' overall survival. This study identified SEC62 as an independent prognostic biomarker in HNSCC patients treated with primary CRT. The role of SEC62 as a potential therapeutic target and its interaction with radiation-induced molecular alterations in head and neck cancer cells should further be investigated.

Validation of Inflammatory Prognostic Biomarkers in Pleural Mesothelioma

Evoked from asbestos-induced inflammation, pleural mesothelioma represents a fatal diagnosis. Therapy ranges from nihilism to aggressive multimodality regimens. However, it is still unclear who ultimately benefits from which treatment. We aimed to re-challenge inflammatory-related biomarkers' prognostic value in times of modern immune-oncology and lung-sparing surgery. The biomarkers (leukocytes, hemoglobin, platelets, neutrophils, lymphocytes, monocytes, neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), platelet-lymphocyte ratio (PLR), C-reactive protein (CRP)) and clinical characteristics (age, sex, histology, therapy) of 98 PM patients were correlated to overall survival (OS). The median OS was 19.4 months. Significant OS advantages (Log-Rank) were observed in multimodal treatment vs. others (26.1 vs. 7.2 months, p < 0.001), surgery (pleurectomy/decortication) vs. no surgery (25.5 vs. 3.8 months, p < 0.001), a high hemoglobin level (cut-off 12 g/dL, 15 vs. 24.2 months, p = 0.021), a low platelet count (cut-off 280 G/L, 26.1 vs. 11.7 months, p < 0.001), and a low PLR (cut-off 194.5, 25.5 vs. 12.3 months, p = 0.023). Histology (epithelioid vs. non-epithelioid, p = 0.002), surgery (p = 0.004), CRP (cut-off 1 mg/dL, p = 0.039), and platelets (p = 0.025) were identified as independent prognostic variables for this cohort in multivariate analysis (Cox regression, covariates: age, sex, histology, stage, CRP, platelets). Our data verified the previously shown prognostic role of systemic inflammatory parameters in patients treated with lung-sparing surgery within multimodality therapy.

Peripheral blood lymphocytes predict clinical outcomes in hormone receptor-positive HER2-negative advanced breast cancer patients treated with CDK4/6 inhibitors

Background

Cyclin-Dependent Kinase 4/6 inhibitors (CDK4/6i) combined with Endocrine Therapy (ET) are the standard treatment for patients with Hormone Receptor-positive/HER2-negative advanced breast cancer (HR+/HER2- aBC).

Objectives

While CDK4/6i are known to reduce several peripheral blood cells, such as neutrophils, lymphocytes and platelets, the impact of these modulations on clinical outcomes is unknown.

Design

A multicenter, retrospective-prospective Italian study.

Methods

We investigated the association between baseline peripheral blood cells, or their early modifications (i.e. 2 weeks after treatment initiation), and the progression-free survival (PFS) of HR+/HER2- aBC patients treated with ETs plus CDK4/6i. Random Forest models were used to select covariates associated with patient PFS among a large list of patient- and tumor-related variables.

Results

We evaluated 638 HR+/HER2- aBC patients treated with ET plus CDK4/6i at six Italian Institutions between January 2017 and May 2021. High baseline lymphocyte counts were independently associated with longer PFS [median PFS (mPFS) 20.1 versus 13.2 months in high versus low lymphocyte patients, respectively; adjusted Hazard Ratio (aHR): 0.78; 95% confidence interval (CI): 0.66-0.92; p = 0.0144]. Moreover, patients experiencing a lower early reduction of lymphocyte counts had significantly longer PFS when compared to patients undergoing higher lymphocyte decrease (mPFS 18.1 versus 14.5 months; aHR: 0.82; 95% CI: 0.73-0.93; p = 0.0037). Patients with high baseline lymphocytes and undergoing a lower reduction, or even an increase, of lymphocyte counts during CDK4/6i therapy experienced the longest PFS, while patients with lower baseline lymphocytes and undergoing a higher decrease of lymphocytes had the lowest PFS (mPFS 21.4 versus 11 months, respectively).

Conclusion

Baseline and on-treatment modifications of peripheral blood lymphocytes have independent prognostic value in HR+/HER2- aBC patients. This study supports the implementation of clinical strategies to boost antitumor immunity in patients with HR+/HER2- aBC treated with ETs plus CDK4/6i.

Deciphering the Hypoxia-immune interface in esophageal squamous carcinoma: a prognostic network model

Introduction

The rapid progress and poor prognosis of the exercise of esophageal squamous cell carcinoma (ESCA) bring great challenges to the treatment. Hypoxia in the tumor microenvironment has become a key factor in the pathogenesis of tumors. However, due to the lack of clear therapeutic targets, hypoxia targeted therapy of ESCA is still in the exploratory stage.

Methods

To bridge this critical gap, we mined a large number of gene expression profiles and clinical data on ESCA from public databases. First, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed. We next delved into the relationship between hypoxia and apoptotic cell interactions. Meanwhile, using LASAS-Cox regression, we designed a robust prognostic risk score, which was subsequently validated in the GSE53625 cohort. In addition, we performed a comprehensive analysis of immune cell infiltration and tumor microenvironment using cutting-edge computational tools.

Results

Hypoxia-related genes were identified and classified by WGCNA. Functional enrichment analysis further elucidated the mechanism by which hypoxia affected the ESCA landscape. The results of the interaction analysis of hypoxia and apoptotic cells revealed their important roles in driving tumor progression. The validation results of the prognostic risk score model in the GSE53625 cohort obtained a good area under the receiver operating characteristic (ROC) curve, and the risk score was independently verified as a significant predictor of ESCA outcome. The results of immune cell infiltration and tumor microenvironment analysis reveal the profound impact of immune cell dynamics on tumor evolution.

Conclusion

Overall, our study presents a pioneering hypoxiacentered gene signature for prognostication in ESCA, providing valuable prognostic insights that could potentially revolutionize patient stratification and therapeutic management in clinical practice.

Negative hyperselection of elderly patients with RAS and BRAF wild-type metastatic colorectal cancer receiving initial panitumumab plus FOLFOX or 5-FU/LV

BACKGROUND

Upfront anti-EGFR therapy represents the standard of care for patients with left-sided, MSS/pMMR, RAS and BRAF wild-type mCRC. Molecular 'hyperselection' may optimize EGFR inhibition by detecting additional resistance alterations.

MATERIALS AND METHODS

We used comprehensive genomic profiling on archival samples of elderly patients enrolled in the PANDA trial to detect: HER2 amplification/mutations; MET amplification; NTRK/ROS1/ALK/RET rearrangements; PIK3CA exon 20 mutations; PTEN alterations; AKT1 mutations; MAP2K1 mutations. We defined 'Gene Altered' (GA) patients whose tumour harboured at least one alteration, and 'Hyperselected' (HS) those without. Survival and tumour response outcomes were correlated to hyperselection status alone or combined with primary tumour sidedness or treatment arm.

RESULTS

Genomic alterations were detected in 41/147 patients (27.9%). PFS, OS and ORR were inferior in GA versus HS (median PFS: 7.6 versus 12.8 months, HR = 2.08, 95% CI: 1.43-3.03, p < 0.001; median OS: 20.0 versus 29.5 months, HR = 1.82, 95% CI:1.23-2.69, p = 0.002; ORR: 51% versus 71%; OR = 0.43, 95% CI: 0.21-0.91, p = 0.02). In the multivariable models, the impact of hyperselection on PFS and OS was confirmed. Lower ORR was observed with 5-FU/LV/panitumumab in GA (40% versus 62%), but not in HS (70% versus 72%). GA was associated with worse survival and response regardless of primary tumour sidedness, whereas in the HS subgroup, right-and left sided tumours had similar outcomes.

CONCLUSIONS

Molecular hyperselection and comprehensive genomic profiling have a potential usefulness in elderly patients with RAS/BRAF wild-type, pMMR/MSS mCRC, eligible for upfront EGFR inhibition.

Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers

Background: Rare endocrine cancers such as Adrenocortical Carcinoma (ACC) present a serious diagnostic and prognostication challenge. The knowledge about ACC pathogenesis is incomplete, and patients have limited therapeutic options. Identification of molecular drivers and effective biomarkers is required for timely diagnosis of the disease and stratify patients to offer the most beneficial treatments. In this study we demonstrate how machine learning methods integrating multi-omics data, in combination with system biology tools, can contribute to the identification of new prognostic biomarkers for ACC. Methods: ACC gene expression and DNA methylation datasets were downloaded from the Xena Browser (GDC TCGA Adrenocortical Carcinoma cohort). A highly correlated multi-omics signature discriminating groups of samples was identified with the data integration analysis for biomarker discovery using latent components (DIABLO) method. Additional regulators of the identified signature were discovered using Clarivate CBDD (Computational Biology for Drug Discovery) network propagation and hidden nodes algorithms on a curated network of molecular interactions (MetaBase™). The discriminative power of the multi-omics signature and their regulators was delineated by training a random forest classifier using 55 samples, by employing a 10-fold cross validation with five iterations. The prognostic value of the identified biomarkers was further assessed on an external ACC dataset obtained from GEO (GSE49280) using the Kaplan-Meier estimator method. An optimal prognostic signature was finally derived using the stepwise Akaike Information Criterion (AIC) that allowed categorization of samples into high and low-risk groups. Results: A multi-omics signature including genes, micro RNA's and methylation sites was generated. Systems biology tools identified additional genes regulating the features included in the multi-omics signature. RNA-seq, miRNA-seq and DNA methylation sets of features revealed a high power to classify patients from stages I-II and stages III-IV, outperforming previously identified prognostic biomarkers. Using an independent dataset, associations of the genes included in the signature with Overall Survival (OS) data demonstrated that patients with differential expression levels of 8 genes and 4 micro RNA's showed a statistically significant decrease in OS. We also found an independent prognostic signature for ACC with potential use in clinical practice, combining 9-gene/micro RNA features, that successfully predicted high-risk ACC cancer patients. Conclusion: Machine learning and integrative analysis of multi-omics data, in combination with Clarivate CBDD systems biology tools, identified a set of biomarkers with high prognostic value for ACC disease. Multi-omics data is a promising resource for the identification of drivers and new prognostic biomarkers in rare diseases that could be used in clinical practice.

Prognostic Biomarkers in Pituitary Tumours: A Systematic Review

Pituitary tumours (PTs) are the second most common intracranial tumour. Although the majority show benign behaviour, they may exert aggressive behaviour and can be resistant to treatment. The aim of this review is to report the recently identified biomarkers that might have possible prognostic value. Studies evaluating potentially prognostic biomarkers or a therapeutic target in invasive/recurrent PTs compared with either non-invasive or non-recurrent PTs or normal pituitaries are included in this review. In the 28 included studies, more than 911 PTs were evaluated. A systematic search identified the expression of a number of biomarkers that may be positively correlated with disease recurrence or invasion in PT, grouped according to role: (1) insensitivity to anti-growth signals: minichromosome maintenance protein 7; (2) evasion of the immune system: cyclooxygenase 2, arginase 1, programmed cell death protein 1 (PD-1)/programmed death ligand 2, cluster of differentiation (CD) 80/CD86; (3) sustained angiogenesis: endothelial cell-specific molecule, fibroblast growth factor receptor, matrix metalloproteinase 9, pituitary tumour transforming gene; (4) self-sufficiency in growth signals: epidermal growth factor receptor; and (5) tissue invasion: matrix metalloproteinase 9, fascin protein. Biomarkers with a negative correlation with disease recurrence or invasion include: (1) insensitivity to anti-growth signals: transforming growth factor β1, Smad proteins; (2) sustained angiogenesis: tissue inhibitor of metalloproteinase 1; (3) tissue invasion: Wnt inhibitory factor 1; and (4) miscellaneous: co-expression of glial fibrillary acidic protein and cytokeratin, and oestrogen receptors α36 and α66. PD-1/programmed cell death ligand 1 showed no clear association with invasion or recurrence, while cyclin A, cytotoxic T lymphocyte-associated protein 4, S100 protein, ephrin receptor, galectin-3 , neural cell adhesion molecule, protein tyrosine phosphatase 4A3 and steroidogenic factor 1 had no association with invasion or recurrence of PT. With the aim to develop a more personalized approach to the treatment of PT, and because of the limited number of molecular targets currently studied in the context of recurrent PT and invasion, a better understanding of the most relevant of these biomarkers by well-d esigned interventional studies will lead to a better understanding of the molecular profile of PT. This should also meet the increased need of treatable molecular targets.

Unveiling the interplay between NSAID-induced dysbiosis and autoimmune liver disease in children: insights into the hidden gateway to autism spectrum disorders. Evidence from ex vivo, in vivo, and clinical studies

Autism spectrum disorders (ASD) represent a diverse group of neuropsychiatric conditions, and recent evidence has suggested a connection between ASD and microbial dysbiosis. Immune and gastrointestinal dysfunction are associated with dysbiosis, and there are indications that modulating the microbiota could improve ASD-related behaviors. Additionally, recent findings highlighted the significant impact of microbiota on the development of autoimmune liver diseases, and the occurrence of autoimmune liver disease in children with ASD is noteworthy. In the present study, we conducted both an in vivo study and a clinical study to explore the relationship between indomethacin-induced dysbiosis, autoimmune hepatitis (AIH), and the development of ASD. Our results revealed that indomethacin administration induced intestinal dysbiosis and bacterial translocation, confirmed by microbiological analysis showing positive bacterial translocation in blood cultures. Furthermore, indomethacin administration led to disturbed intestinal permeability, evidenced by the activation of the NLRP3 inflammasomes pathway and elevation of downstream biomarkers (TLR4, IL18, caspase 1). The histological analysis supported these findings, showing widened intestinal tight junctions, decreased mucosal thickness, inflammatory cell infiltrates, and collagen deposition. Additionally, the disturbance of intestinal permeability was associated with immune activation in liver tissue and the development of AIH, as indicated by altered liver function, elevated ASMA and ANA in serum, and histological markers of autoimmune hepatitis. These results indicate that NSAID-induced intestinal dysbiosis and AIH are robust triggers for ASD existence. These findings were further confirmed by conducting a clinical study that involved children with ASD, autoimmune hepatitis (AIH), and a history of NSAID intake. Children exposed to NSAIDs in early life and complicated by dysbiosis and AIH exhibited elevated serum levels of NLRP3, IL18, liver enzymes, ASMA, ANA, JAK1, and IL6. Further, the correlation analysis demonstrated a positive relationship between the measured parameters and the severity of ASD. Our findings suggest a potential link between NSAIDs, dysbiosis-induced AIH, and the development of ASD. The identified markers hold promise as indicators for early diagnosis and prognosis of ASD. This research highlights the importance of maintaining healthy gut microbiota and supports the necessity for further investigation into the role of dysbiosis and AIH in the etiology of ASD.

Can Whole-Body Baseline CT Radiomics Add Information to the Prediction of Best Response, Progression-Free Survival, and Overall Survival of Stage IV Melanoma Patients Receiving First-Line Targeted Therapy: A Retrospective Register Study

BACKGROUND

The aim of this study was to investigate whether the combination of radiomics and clinical parameters in a machine-learning model offers additive information compared with the use of only clinical parameters in predicting the best response, progression-free survival after six months, as well as overall survival after six and twelve months in patients with stage IV malignant melanoma undergoing first-line targeted therapy.

METHODS

A baseline machine-learning model using clinical variables (demographic parameters and tumor markers) was compared with an extended model using clinical variables and radiomic features of the whole tumor burden, utilizing repeated five-fold cross-validation. Baseline CTs of 91 stage IV malignant melanoma patients, all treated in the same university hospital, were identified in the Central Malignant Melanoma Registry and all metastases were volumetrically segmented (n = 4727).

RESULTS

Compared with the baseline model, the extended radiomics model did not add significantly more information to the best-response prediction (AUC [95% CI] 0.548 (0.188, 0.808) vs. 0.487 (0.139, 0.743)), the prediction of PFS after six months (AUC [95% CI] 0.699 (0.436, 0.958) vs. 0.604 (0.373, 0.867)), or the overall survival prediction after six and twelve months (AUC [95% CI] 0.685 (0.188, 0.967) vs. 0.766 (0.433, 1.000) and AUC [95% CI] 0.554 (0.163, 0.781) vs. 0.616 (0.271, 1.000), respectively).

CONCLUSIONS

The results showed no additional value of baseline whole-body CT radiomics for best-response prediction, progression-free survival prediction for six months, or six-month and twelve-month overall survival prediction for stage IV melanoma patients receiving first-line targeted therapy. These results need to be validated in a larger cohort.

Comprehensive Systematic Review of Biomarkers in Metastatic Renal Cell Carcinoma: Predictors, Prognostics, and Therapeutic Monitoring

BACKGROUND

Challenges remain in determining the most effective treatment strategies and identifying patients who would benefit from adjuvant or neoadjuvant therapy in renal cell carcinoma. The objective of this review is to provide a comprehensive overview of biomarkers in metastatic renal cell carcinoma (mRCC) and their utility in prediction of treatment response, prognosis, and therapeutic monitoring in patients receiving systemic therapy for metastatic disease.

METHODS

A systematic literature search was conducted using the PubMed database for relevant studies published between January 2017 and December 2022. The search focused on biomarkers associated with mRCC and their relationship to immune checkpoint inhibitors, targeted therapy, and VEGF inhibitors in the adjuvant, neoadjuvant, and metastatic settings.

RESULTS

The review identified various biomarkers with predictive, prognostic, and therapeutic monitoring potential in mRCC. The review also discussed the challenges associated with anti-angiogenic and immune-checkpoint monotherapy trials and highlighted the need for personalized therapy based on molecular signatures.

CONCLUSION

This comprehensive review provides valuable insights into the landscape of biomarkers in mRCC and their potential applications in prediction of treatment response, prognosis, and therapeutic monitoring. The findings underscore the importance of incorporating biomarker assessment into clinical practice to guide treatment decisions and improve patient outcomes in mRCC.

Erratum: Preoperative immunological plasma markers TRAIL, CSF1, and TIE2 predict survival after resection for biliary tract cancer

[This corrects the article DOI: 10.3389/fonc.2023.1169537.].

Evaluating [18F]FDG and [18F]FLT Radiotracers as Biomarkers of Response for Combined Therapy Outcome in Triple-Negative and Estrogen-Receptor-Positive Breast Cancer Models

Breast cancer (BC) is the most frequent cancer and the second leading cause of death in women. A typical feature of BC cells is the metabolic shift toward increased glycolysis, which has become an interesting therapeutic target for metabolic drugs such as metformin (MET). Recently, the administration of the antihypertensive syrosingopine (SYRO) in combination with MET has shown a synergistic effect toward a variety of cancers. However, a fundamental need remains, which is the development of in vivo biomarkers that are able to detect early clinical response. In this study, we exploited a triple-negative murine BC cell line (4T1) and a metastatic ER+ murine BC cell line (TS/A) in order to investigate, in vivo, the early response to treatment, based on MET and/or SYRO administration, evaluating [18F]FDG and [18F]FLT as potential biomarkers via PET/CT. The study provides evidence that SYRO plus MET has a synergistic effect on tumor growth inhibition in both 4T1 and TS/A experimental models and has showed the highest efficacy on the TNBC xenograft mice (4T1) via the expression reduction in the lactate transporter MCT4 and in the epithelial-mesenchymal transition biomarker Snail, promoting its potential application in therapy settings. In addition, the selective reduction in the [18F]FLT tumor uptake (at 7 dd), observed in the SYRO plus MET treated mice in comparison with the vehicle group, suggests that this radiotracer could be potentially used as a biomarker for the early detection of therapy response, in both evaluated xenografts models.

Prognostic and therapeutic implications of iron-related cell death pathways in acute myeloid leukemia

Acute myeloid leukemia (AML) is a blood cancer that is diverse in terms of its molecular abnormalities and clinical outcomes. Iron homeostasis and cell death pathways play crucial roles in cancer pathogenesis, including AML. The objective of this study was to examine the clinical significance of genes involved in iron-related cell death and apoptotic pathways in AML, with the intention of providing insights that could have prognostic implications and facilitate the development of targeted therapeutic interventions. Gene expression profiles, clinical information, and molecular alterations were integrated from multiple datasets, including TCGA-LAML and GSE71014. Our analysis identified specific molecular subtypes of acute myeloid leukemia (AML) displaying varying outcomes, patterns of immune cell infiltration, and profiles of drug sensitivity for targeted therapies based on the expression of genes involved in iron-related apoptotic and cell death pathways. We further developed a risk model based on four genes, which demonstrated promising prognostic value in both the training and validation cohorts, indicating the potential of this model for clinical decision-making and risk stratification in AML. Subsequently, Western blot analysis showed that the expression levels of C-Myc and CyclinD1 were significantly reduced after CD4 expression levels were knocked down. The findings underscore the potential of iron-related cell death pathways as prognostic biomarkers and therapeutic targets in AML, paving the way for further research aimed at understanding the molecular mechanisms underlying the correlation between iron balance, apoptosis regulation, and immune modulation in the bone marrow microenvironment.

Prognostic biomarkers for survival in mucosal melanoma

Mucosal melanoma (MM) is a rare subtype of melanoma with an aggressive clinical course. In cutaneous melanoma (CM), the absence of pigmentation and presence of NRAS/KRAS mutations are biomarkers indicating an aggressive clinical course with shorter overall survival. Similar data for MM are missing. We present the real-world outcome data in a cohort of genotyped MM patients and assessed the prognostic relevance of pigmentation- and NRAS/KRAS mutation status. We correlated pathological reports and clinical data with overall survival of patients with MM. Furthermore, we performed clinically integrated molecular genotyping and analyzed real world treatment regimens for covariates associated with clinical outcome. We identified 39 patients with available clinical and molecular data. Patients with amelanotic MM had a significantly shorter overall survival (p = .003). In addition, the presence of a NRAS or KRAS mutation was significantly associated with poor overall survival (NRAS or KRAS p = .024). Currently, it is unknown if the same prognostic relevance for the lack of pigmentation and RAS mutations in CM, exists in MM. Here we analyzed a cohort of MM for outcome measures and determined that two known prognostic biomarkers for CM are in fact novel prognosticators for MM.

Low Valine Serum Levels Predict Increased 1-Year Mortality in Acute Heart Failure Patients

Considering the relationship between disease severity and the extent of metabolic derangement in heart failure, we hypothesized that the serum levels of metabolites may have prognostic value for 1-year mortality in acute heart failure (AHF). The AHF study was a prospective, observational study enrolling consecutive patients hospitalized due to AHF. Metabolites were measured in serum collected at admission using NMR spectroscopy. Out of 315 AHF patients, 118 (37.5%) died within 1 year after hospitalization for AHF. The serum levels of 8 out of 49 identified metabolites were significantly different between patients who were alive and those who died within 1 year after hospitalization for AHF. Of these, only valine was significantly associated with 1-year mortality (hazard ratio 0.73 per 1 standard deviation increase, 95% confidence interval: 0.59-0.90, p = 0.003) in the multivariable Cox regression analyses. Kaplan-Maier analysis showed significantly higher survival rates in AHF patients with valine levels above the median (>279.2 µmol/L) compared to those with valine levels ≤ 279.2 µmol/L. In a receiver operating characteristics curve analysis, valine was able to discriminate between the two groups with an area under the curve of 0.65 (95% CI 0.59-0.72). We conclude that valine serum levels might be of prognostic value in AHF.

PLEKHA4 is Associated with Tumour Microenvironment, Stemness, Proliferation and Poor Prognosis of Gliomas

BACKGROUND

Glioma is the most common intracranial malignancy. Immune-infiltration and tumour stemness are associated with the prognosis of glioma. Although pleckstrin homology containing family A, number 4 (PLEKHA4) is widely expressed in various human cancers, its role in glioma remains unclear.

METHODS

We examined the features and clinical significance of PLEKHA4 in gliomas by analysing relevant data from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. Gene set enrichment analysis (GSEA) was performed to determine the possible functions and pathways involving PLEKHA4 in glioma. The relationship between PLEKHA4 expression and the degree of oncogenic dedifferentiation was analysed using stemness scores (ss) calculated from epigenetic and transcriptomic features. We also explored the relationship between PLEKHA4 expression and immune cell infiltration in gliomas using the CIBERSORT databases. Furthermore, drug sensitivity analysis was performed using datasets from the GDSC and GTRP databases. In addition, we performed relevant in vitro experimental studies.

RESULTS

PLEKHA4 DNA hypomethylation status was associated with its high expression in glioma tissues as well as poor prognoses. Univariate and multivariate Cox analyses indicated that PLEKHA4 expression may be considered as an independent prognostic factor in patients with glioma. GSEA indicated that high PLEKHA4 expression was associated with Janus kinase (JAK)/signal transducer and activator of transcription (STAT), Wingless-Type MMTV Integration Site Family (Wnt), JUN N-terminal kinase (JNK) signalling pathways and involved in apoptotic, cytoskeletal, and cell adhesion biological processes (BPs). In addition, increased PLEKHA4 expression was associated with higher glioma stemness scores than lower PLEKHA4 expression levels. Furthermore, the expression of PLEKHA4 was shown to be associated with glioma infiltration by CD4+ T cells, B cells, neutrophils, macrophages, and dendritic cells. Drug sensitivity analysis also showed that PLEKHA4 expression was negatively correlated with the sensitivity of several small molecule kinase inhibitors. Furthermore, in vitro experiments confirmed that PLEKHA4 knockdown inhibited the proliferation of glioma cells.

CONCLUSIONS

PLEKHA4 is highly expressed in glioma tissues and correlated with tumour stemness, immune cell infiltration and proliferation, suggesting its potential as a novel prognostic biomarker and therapeutic target in glioma.

SwarmDeepSurv: swarm intelligence advances deep survival network for prognostic radiomics signatures in four solid cancers

Survival models exist to study relationships between biomarkers and treatment effects. Deep learning-powered survival models supersede the classical Cox proportional hazards (CoxPH) model, but substantial performance drops were observed on high-dimensional features because of irrelevant/redundant information. To fill this gap, we proposed SwarmDeepSurv by integrating swarm intelligence algorithms with the deep survival model. Furthermore, four objective functions were designed to optimize prognostic prediction while regularizing selected feature numbers. When testing on multicenter sets (n = 1,058) of four different cancer types, SwarmDeepSurv was less prone to overfitting and achieved optimal patient risk stratification compared with popular survival modeling algorithms. Strikingly, SwarmDeepSurv selected different features compared with classical feature selection algorithms, including the least absolute shrinkage and selection operator (LASSO), with nearly no feature overlapping across these models. Taken together, SwarmDeepSurv offers an alternative approach to model relationships between radiomics features and survival endpoints, which can further extend to study other input data types including genomics.

Identification of angiogenesis-related genes signature for predicting survival and its regulatory network in glioblastoma

Glioblastoma (GBM) is notorious for malignant neovascularization that contributes to undesirable outcome. However, its mechanisms remain unclear. This study aimed to identify prognostic angiogenesis-related genes and the potential regulatory mechanisms in GBM. RNA-sequencing data of 173 GBM patients were obtained from the Cancer Genome Atlas (TCGA) database for screening differentially expressed genes (DEGs), differentially transcription factors (DETFs), and reverse phase protein array (RPPA) chips. Differentially expressed genes from angiogenesis-related gene set were extracted for univariate Cox regression analysis to identify prognostic differentially expressed angiogenesis-related genes (PDEARGs). A risk predicting model was constructed based on 9 PDEARGs, namely MARK1, ITGA5, NMD3, HEY1, COL6A1, DKK3, SERPINA5, NRP1, PLK2, ANXA1, SLIT2, and PDPN. Glioblastoma patients were stratified into high-risk and low-risk groups according to their risk scores. GSEA and GSVA were applied to explore the possible underlying GBM angiogenesis-related pathways. CIBERSORT was employed to identify immune infiltrates in GBM. The Pearson's correlation analysis was performed to evaluate the correlations among DETFs, PDEARGs, immune cells/functions, RPPA chips, and pathways. A regulatory network centered by three PDEARGs (ANXA1, COL6A1, and PDPN) was constructed to show the potential regulatory mechanisms. External cohort of 95 GBM patients by immunohistochemistry (IHC) assay demonstrated that ANXA1, COL6A1, and PDPN were significantly upregulated in tumor tissues of high-risk GBM patients. Single-cell RNA sequencing also validated malignant cells expressed high levels of the ANXA1, COL6A1, PDPN, and key DETF (WWTR1). Our PDEARG-based risk prediction model and regulatory network identified prognostic biomarkers and provided valuable insight into future studies on angiogenesis in GBM.

AhRR and PPP1R3C: Potential Prognostic Biomarkers for Serous Ovarian Cancer

The lack of effective screening and successful treatment contributes to high ovarian cancer mortality, making it the second most common cause of gynecologic cancer death. Development of chemoresistance in up to 75% of patients is the cause of a poor treatment response and reduced survival. Therefore, identifying potential and effective biomarkers for its diagnosis and prognosis is a strong critical need. Copy number alterations are frequent in cancer, and relevant for molecular tumor stratification and patients' prognoses. In this study, array-CGH analysis was performed in three cell lines and derived cancer stem cells (CSCs) to identify genes potentially predictive for ovarian cancer patients' prognoses. Bioinformatic analyses of genes involved in copy number gains revealed that AhRR and PPP1R3C expression negatively correlated with ovarian cancer patients' overall and progression-free survival. These results, together with a significant association between AhRR and PPP1R3C expression and ovarian cancer stemness markers, suggested their potential role in CSCs. Furthermore, AhRR and PPP1R3C's increased expression was maintained in some CSC subpopulations, reinforcing their potential role in ovarian cancer. In conclusion, we reported for the first time, to the best of our knowledge, a prognostic role of AhRR and PPP1R3C expression in serous ovarian cancer.

High Intratumoral i-tRF-GlyGCC Expression Predicts Short-Term Relapse and Poor Overall Survival of Colorectal Cancer Patients, Independent of the TNM Stage

Colorectal cancer (CRC), one of the most prevalent types of cancer, requires the discovery of new tumor biomarkers for accurate patient prognosis. In this work, the prognostic value of the tRNA fragment i-tRF-Gly^GCC in CRC was examined. Total RNA extraction from 211 CRC patient cancer tissue specimens and 83 adjacent normal tissues was conducted. Each RNA extract was subjected to in vitro polyadenylation and reverse transcription. A real-time quantitative PCR assay was used to quantify i-tRF-Gly^GCC in all samples. Extensive biostatics analysis showed that i-tRF-Gly^GCC levels in CRC tissues were significantly lower than in matched normal colorectal tissues. Additionally, the disease-free survival (DFS) and overall survival (OS) time intervals were considerably shorter in CRC patients with high i-tRF-Gly^GCC expression. i-tRF-Gly^GCC expression maintained its prognostic value independently of other established prognostic factors, as shown by the multivariate Cox regression analysis. Additionally, survival analysis after TNM stage stratification revealed that higher i-tRF-Gly^GCC levels were linked to shorter DFS time intervals in patients with TNM stage II tumors, as well as an increased probability of having a worse OS for patients in TNM stage II. In conclusion, i-tRF-Gly^GCC has the potential to be a useful molecular tissue biomarker in CRC, independent of other clinicopathological variables.

Ki67 proliferation index in follicular lymphoma is associated with favorable outcome in patients treated with R-CHOP

Follicular lymphoma (FL) is a common, indolent small B-cell lymphoma. While the Follicular Lymphoma International Prognostic Index is widely used, reliable prognostic and predictive biomarkers are needed. A recent study suggested that architectural patterns of CD10, BCL6, and Ki67 expression may correlate with progression-free survival (PFS) in FL patients treated with chemotherapy-free regimens. We examined the prognostic and predictive utility of architectural patterns of CD10, BCL6, Ki67, and FOXP1 in 90 patients treated with immunochemotherapy (bendamustine-rituximab [BR] and R-cyclophosphamide, doxorubicin, vincristine, prednisone [CHOP]). We found that high follicular Ki67 (≥30%) was associated with longer PFS in the subgroup of patients treated with R-CHOP but not among those treated with BR. Validation of this biomarker may support routine use of Ki67 as a predictive marker in FL.

Biomarkers of ocular allergy and dry eye disease

The most common disorders of the ocular surface are dry eye disease (DED) and ocular allergy (OA). These conditions are frequently coexisting with or without a clinical overlap and can cause a severe impact on the patient's quality of life. Therefore, it can sometimes be hard to distinguish between DED and OA because similar changes and manifestations may be present. Atopic patients can also develop DED, which can aggravate their manifestations. Moreover, patients with DED can develop ocular allergies, so these two pathological entities of the ocular surface can be considered as mutual conditions that share the same background. Nowadays, by using different techniques to collect tissue from ocular surfaces, the changes in molecular homeostasis can be detected and this can lead to a precise diagnosis. The article provides an up-to-date review of the various ocular surface biomarkers that have been identified in DED, OA, or both conditions. Abbreviations: DED = dry eye disease, OA = ocular allergy, SS = Sjogren syndrome, TBUT = tear break up time, TFO = tear film osmolarity, AKC = Atopic keratoconjunctivitis, ANXA1 = Annexin 1, ANXA11 = Annexin 11, CALT = Conjunctival associated lymphoid tissue, CCL2/MIP-1 = Chemokine (C-C motif) ligand2/Monocyte chemoattractant protein 1, CCL3/MIP-1α = Chemokine (C-C motif) ligand 3/Macrophage inflammatory protein 1 alpha, CCL4/MIP-1β = Chemokine (C-C motif) ligand 4/Macrophage inflammatory protein 1 beta, CCL5/RANTES = Chemokine (C-C motif) ligand 5 /Regulated on Activation, Normal T cell Expressed and Secreted, CCR2 = Chemokine (C-C motif) receptor 2, CCR5 = Chemokine (C-C motif) receptor 5, CD3+ = Cluster of differentiation 3 positive, CD4+ = Cluster of differentiation 4 positive, CD8+ = Cluster of differentiation 8 positive, CGRP = Calcitonin-gene-related peptide, CX3CL1 C-X3 = C motif -chemokine ligand 1 /Fractalkine, CXCL8 = Chemokine (C-X-C motif) ligand 8, CXCL9 = Chemokine (C-X-C motif) ligand 9, CXCL10 = Chemokine (C-X-C motif) ligand 10, CXCL11 = Chemokine (C-X-C motif) ligand 11, CXCL12 = Chemokine (C-X-C motif) ligand 12, CXCR4 = Chemokine (C-X-C motif) receptor 4, EGF = Epidermal growth factor, HLA-DR = Human leukocyte antigen-D-related, ICAM-1 = Intercellular adhesion molecule 1, IFN-γ = Interferon-gamma, IgG = Immunoglobulin G, IgE = Immunoglobulin E, IL-1 = Interleukin-1, IL-1α = Interleukin-1 alpha, IL-1β = Interleukin-1 beta, CGRP = Calcitonin-Gene-Related Peptide, IL-3 = Interleukin-3, IL-4 = Interleukin-4, IL-6 = Interleukin-6, IL-8 = Interleukin-8, IL-10 = Interleukin-10, IL-17 = Interleukin-17, IL-17A = Interleukin-17A, LPRR3 = Lacrimal proline-rich protein 3, LPRR4 = Lacrimal proline-rich protein 4, MUC5AC = Mucin 5 subtype AC, oligomeric mucus/gel-forming, MUC16 = Mucin 16, OCT = Optical coherence tomography, OGVHD = Ocular graft versus host disease, PAX6 = Paired-box protein 6, VKC = Vernal keratoconjunctivitis, TGF-β = Transforming growth factor β, S100 = proteins Calcium activated signaling proteins, Th1 = T helper 1 cell, Th17 = T helper 17 cell, MGD = Meibomian gland dysfunction, TFOS = Tear film and ocular surface society, SS-KCS = Keratoconjunctivitis Sicca, MMP-9 = Matrix metalloproteinase 9, MMP-1 = Matrix metalloproteinase 1, ZAG = Zinc alpha glycoprotein, CBA = Cytometric bead array, MALDI TOF-MS = matrix assisted laser desorption ionization-time of flight, SELDI TOF-MS = surface-enhanced laser desorption ionization-time of flight, IVCM = in vivo confocal microscopy, AS-OCT = anterior segment optical coherence tomography, iTRAQ = Isobaric tags for relative and absolute quantitation, LC-MS = Liquid chromatography-mass spectrometry, LCN-1 = lipocalin 1, PIP = prolactin induced protein, NGF = Nerve growth factor, PRR4 = proline rich protein 4, VIP = Vasoactive intestinal peptide, ELISA = enzyme linked immunoassay, TNF-α = tumor necrosis factor alpha, PAC = perennial allergic conjunctivitis, SAC = seasonal allergic conjunctivitis, IC = impression cytology, RT-PCR = reverse transcription polymerase chain reaction, PCR = polymerase chain reaction, APCs = antigen-presenting cells, NK cells = natural killer cells, HEL = hexanoyl-lysine, 4-HNE = 4-hydroxy-2-nonenal, MDA = malondialdehyde.

Exploring new prognostic biomarkers in Mantle Cell Lymphoma: a comparison of the circSCORE and the MCL35 score

Mantle cell lymphoma (MCL) is a biologically and clinically heterogeneous disease, emphasizing the need for prognostic biomarkers. In this study we aimed at comparing the prognostic value of two RNA-based risk scores, circSCORE and MCL35, in 149 patients from the MCL2 (ISRCTN87866680) and MCL3 (NCT00514475) patient cohorts. Both risk scores provided significant stratification of high versus low risk for progression free survival (PFS) and overall survival (OS). The circSCORE retained significant prognostic value in adjusted multivariable Cox regressions for PFS, but not for OS. Furthermore, circSCORE added significant prognostic value to MIPI in the pooled cohort (MCL2 and MCL3) for PFS and OS, and for PFS in MCL3 alone, outperforming Ki67 and MCL35. We suggest a new, combined MIPI-circSCORE with improved prognostic value, and with potential for future clinical implementation, if validated in a larger, independent cohort.

High infiltration of CD209+ dendritic cells and CD163+ macrophages in the peritumor area of prostate cancer is predictive of late adverse outcomes

Introduction

Prostate cancer (PCa) shows considerable variation in clinical outcomes between individuals with similar diseases. The initial host-tumor interaction as assessed by detailed analysis of tumor infiltrating immune cells within the primary tumor may dictate tumor evolution and late clinical outcomes. In this study, we assessed the association between clinical outcomes and dendritic cell (DC) or macrophage (MΦ) tumor infiltration as well as with expression of genes related to their functions.

Methods

Infiltration and localization of immature DC, mature DC, total MΦ and M2-type MΦ was analyzed by immunohistochemistry in 99 radical prostatectomy specimens from patients with 15.5 years median clinical follow-up using antibodies against CD209, CD83, CD68 and CD163, respectively. The density of positive cells for each marker in various tumor areas was determined. In addition, expression of immune genes associated with DC and MΦ was tested in a series of 50 radical prostatectomy specimens by Taqman Low-Density Array with similarly long follow-up. Gene expression was classified as low and high after unsupervised hierarchical clustering. Numbers and ratio of positive cells and levels of gene expression were correlated with endpoints such as biochemical recurrence (BCR), need for definitive androgen deprivation therapy (ADT) or lethal PCa using Cox regression analyses and/or Kaplan-Meier curves.

Results

Positive immune cells were observed in tumor, tumor margin, and normal-like adjacent epithelium areas. CD209⁺ and CD163⁺ cells were more abundant at the tumor margin. Higher CD209⁺/CD83⁺ cell density ratio at the tumor margin was associated with higher risk of ADT and lethal PCa while higher density of CD163⁺ cells in the normal-like adjacent epithelium was associated with a higher risk of lethal PCa. A combination of 5 genes expressed at high levels correlated with a shorter survival without ADT and lethal PCa. Among these five genes, expression of IL12A and CD163 was correlated to each other and was associated with shorter survival without BCR and ADT/lethal PCa, respectively.

Conclusion

A higher level of infiltration of CD209⁺ immature DC and CD163⁺ M2-type MΦ in the peritumor area was associated with late adverse clinical outcomes.