Biomarker Selection Research Articles

Changes in Daily Apparent Diffusion Coefficient on Fully Quantitative Magnetic Resonance Imaging Correlate With Established Genomic Pathways of Radiation Sensitivity and Reveal Novel Biologic Associations

Changes in quantitative magnetic resonance imaging (qMRI) are frequently observed during chemotherapy or radiation therapy (RT). It is hypothesized that qMRI features are reflective of underlying tissue responses. It's unknown what underlying genomic characteristics underly qMRI changes. We hypothesized that qMRI changes may correlate with DNA damage response (DDR) capacity within human tumors. Therefore, we designed the current study to correlate qMRI changes from daily RT treatment with underlying tumor transcriptomic profiles. Study participants were prospectively enrolled (National Clinical Trial 03500081). RNA expression levels for 757 genes from pretreatment biopsies were obtained using a custom panel that included signatures of radiation sensitivity and DDR. Daily qMRI data were obtained from a 1.5 Tesla MR linear accelerator. Using these images, d-slow, d-star, perfusion, and apparent diffusion coefficient-mean values in tumors were plotted per-fraction, over time, and associated with genomic pathways. A total of 1022 qMRIs were obtained from 39 patients and both genomic data and qMRI data from 27 total patients. For 20 of those patients, we also generated normal tissue transcriptomic data. Radio sensitivity index values most closely associated with tissue of origin. Multiple genomic pathways including DNA repair, peroxisome, late estrogen receptor responses, KRAS signaling, and UV response were significantly associated with qMRI feature changes (P < .001). Genomic pathway associations across metabolic, RT sensitivity, and DDR pathways indicate common tumor biology that may correlate with qMRI changes during a course of treatment. Such data provide hypothesis-generating novel mechanistic insight into the biologic meaning of qMRI changes during treatment and enable optimal selection of imaging biomarkers for biologically MR-guided RT.

Eosinophilic Inflammation in COPD: Mechanisms, Diagnostic Markers, Clinical Features and Therapy Guidance

Chronic obstructive pulmonary disease (COPD) is one of the main causes of morbidity and mortality worldwide. Eosinophilia, which may have a significant role in the inflammation process and obstruction of airways, is present in about one third patients suffering from COPD. The significance of eosinophil counts in COPD is currently debated, but they can potentially serve as biomarkers for treatment selection. Blood eosinophil counts can assist in determining the patients who can benefit from inhaled corticosteroid therapy to prevent or eliminate exacerbations.&lt;br /&gt; The aim of this review is to demonstrate the significance of eosinophilic inflammation COPD and the use of eosinophilic inflammation biomarkers to guide therapy decisions.&lt;br /&gt; To reach this goal, a search of relevant literature on the subject was conducted. Articles were searched in electronic sources: PubMed and Google Scholar. The keywords "COPD and eosinophilia", "COPD exacerbations and eosinophilia", "inhaled corticosteroids, COPD and eosinophilia" were used. One hundred and twenty sources were found, of which 66 were selected.&lt;br /&gt; Results of the review showed high frequency of eosinophilic phenotype detection in COPD. Blood eosinophilia becomes a potential universal marker of eosinophilic COPD. Blood eosinophils level can predict response to inhaled corticosteroids treatment patients with COPD, but increases the likelihood of pneumonia. Overall, the role of eosinophilia in COPD has not been obtained to date, which suggests it needs further study.

A comparative study on the dose–effect of low-dose radiation based on microdosimetric analysis and single-cell sequencing technology

The biological mechanisms triggered by low-dose exposure still need to be explored in depth. In this study, the potential mechanisms of low-dose radiation when irradiating the BEAS-2B cell lines with a Cs-137 gamma-ray source were investigated through simulations and experiments. Monolayer cell population models were constructed for simulating and analyzing distributions of nucleus-specific energy within cell populations combined with the Monte Carlo method and microdosimetric analysis. Furthermore, the 10 × Genomics single-cell sequencing technology was employed to capture the heterogeneity of individual cell responses to low-dose radiation in the same irradiated sample. The numerical uncertainties can be found both in the specific energy distribution in microdosimetry and in differential gene expressions in radiation cytogenetics. Subsequently, the distribution of nucleus-specific energy was compared with the distribution of differential gene expressions to guide the selection of differential genes bioinformatics analysis. Dose inhomogeneity is pronounced at low doses, where an increase in dose corresponds to a decrease in the dispersion of cellular-specific energy distribution. Multiple screening of differential genes by microdosimetric features and statistical analysis indicate a number of potential pathways induced by low-dose exposure. It also provides a novel perspective on the selection of sensitive biomarkers that respond to low-dose radiation.

Expression of miRNA from spent pre-implantation embryos culture media

This study examines the expression of three microRNAs (hsa-miR-661, hsa-miR-21–5p, hsa-miR-372–5p) in spent pre-implantation embryos culture media to identify possible new non-invasive biomarkers of embryo competence, predictive of development to the blastocyst stage. A preliminary analysis on 16 patients undergoing IVF cycles was performed by collecting and stored spent culture media on the fifth/sixth day of embryo culture. Expression of miRNAs was evaluated according to the embryos’ fate: 1) NE/DG: non-evolved or degenerate embryos; 2) BLOK: embryos developed to the blastocyst stage. Preliminary results revealed a higher miRNAs expression in NE/DG spent media. To elucidate the roles of these miRNAs, we employed a robust bioinformatics pipeline involving: 1) in-silico miRNA Target Prediction using RNAHybrid, which identified the most-likely gene targets; 2) Construction of a Protein-Protein Interaction network via GeneMania, linking genes with significant biological correlations; 3) application of modularity-based clustering with the gLay app in Cytoscape, resulting in three size-adapted subnets for focused analysis; 4) Enrichment Analysis to discern the biological pathways influenced by the miRNAs. Our bioinformatics analysis revealed that hsa-miR-661 was closely associated with pathways regulating cell shape and morphogenesis of the epithelial sheet. These data suggest the potential use of certain miRNAs to identify embryos with a higher likelihood of developing to the blastocyst stage. Further analysis will be necessary to explore the reproducibility of these findings and to understand if miRNAs here investigated can be used as biomarkers for embryo selection before implantation into the uterus or if they may be reliable predictors of IVF outcome.

Biomarkers for Precision Patient Selection in Cancer Therapy Approvals in the US, from 2011 to 2023.

During the period of 2011-2023, the US Food and Drug Administration (US FDA) granted 139 accelerated and 329 regular approvals for 86 and 152 cancer therapeutic products, respectively. The percentage of approvals for a biomarker-defined population was numerically higher in accelerated approvals in comparison to regular approvals, that is, 48% vs. 40%. From 2011-2016 to 2017-2023, there was an increasing number of approvals with biomarker-defined populations in lung and breast cancers, serving as the primary driver for the overall increase in the percentage of approvals for biomarker-defined populations in solid tumors relative to hematological malignancies. Over the years, approvals were incorporating a more diverse collection of distinct biomarkers, from 3 in 2011 to 16 in 2022. Overall, HER2, hormone receptor (HR), EGFR, ALK, BRAF, and PD-L1-defined populations received the highest numbers of approvals. The FDA decision on approving a biomarker-defined or an all-comers population may depend on a number of factors and may evolve over time based on emerging evidence. The review discusses selected FDA approvals where a pivotal trial enrolled an all-comers population but the approved indication was restricted to a biomarker-defined population, as well as challenges in clinical trial design in the context of precision medicine. The prominent role of biomarkers in optimizing trial design and identifying a population most likely to benefit from treatment underlines the significance of a comprehensive understanding of disease biology and drug mechanisms. Our review illustrates that biomarker-driven approaches enhance the likelihood of identifying optimal patient populations, potentially streamlining trials through accelerated approval pathways for cancer drug development.

SPP1 expression indicates outcome of immunotherapy plus tyrosine kinase inhibition in advanced renal cell carcinoma

ABSTRACT Clinical guidelines have recently advised combination therapy involving immunotherapy (IO) and tyrosine kinase inhibitors (TKI) as the first-line therapy approach for advanced renal cell carcinoma (RCC). Nevertheless, there is currently no available biomarker that can effectively distinguish the progression-free survival (PFS). RNA-sequencing and immunohistochemistry were conducted on our cohort of metastatic RCC patients, namely ZS-MRCC, who received combination therapy consisting of IO and TKI. We further applied RNA-sequencing, immunohistochemistry, and flow cytometry to examine the immune cell infiltration and functionality inside the tumor microenvironment of high-risk localized RCC samples. SPP1 expression was significantly higher in non-responders to IO-TKI therapy. Elevated levels of SPP1 were associated with poor PFS in both the ZS-MRCC cohort (HR = 2.73, p = .018) and validated in the JAVELIN Renal 101 cohort (HR = 1.61, p = .004). By multivariate Cox analysis, SPP1 was identified as a significant independent prognosticator. Furthermore, there existed a negative correlation between elevated levels of SPP1 and the presence of GZMB+CD8+ T cells (Spearman’s ρ= −0.48, p < .001). Conversely, SPP1 expression is associated with T cell exhaustion markers. A significant increase in the abundance of Tregs was observed in tumors with high levels of SPP1. Additionally, a machine-learning-based model was constructed to predict the benefit of IO-TKI treatment. High SPP1 is associated with therapeutic resistance and unfavorable PFS in IO-TKI therapy. SPP1 expression have also been observed to be indicative of malfunction and exhaustion in T cells. Increased SPP1 expression has the potential to serve as a potential biomarker for treatment selection of metastatic RCC.

Selection of texture-associated biomarkers in chilled and iced grass carp (Ctenopharyngodon idella) fillets via DIA-based proteomics

Consumers care about the texture of fresh fish flesh, but a rapid quantitative analytical method for this has not been properly established. In this study, texture-associated biomarkers were selected by DIA-based proteomics for possible future application. Results indicated a significant decline in texture and moisture characteristics with extended storage under chilled and iced conditions, and flesh quality was categorized into three intervals. A total of 8 texture-associated biomarkers were identified in the chilled storage group, and 3 distinct ones in the iced storage group. Biomarkers were further refined based on their expression levels. Isobutyryl-CoA dehydrogenase, mitochondrial and [Phosphatase 2A protein]-leucine-carboxy methyltransferase were identified as effective texture-associated biomarkers for chilled fish, and Staphylococcal nuclease domain-containing protein 1 for iced fish. This study provided suitable proteins as indicators of fresh fish flesh texture, which could help establish a rapid and convenient texture testing method in future studies.

Pan-cancer analysis of super-enhancer-induced LINC00862 and validation as a SIRT1-promoting factor in cervical cancer and gastric cancer

Immune checkpoints inhibitors are effective but it needs more precise biomarkers for patient selection. We explored the biological significance of LINC00862 in pan-cancer by bioinformatics. And we studied its regulatory mechanisms using chromatin immunoprecipitation and RNA immunoprecipitation assays etc. TCGA and single-cell sequencing data analysis indicated that LINC00862 was overexpressed in the majority of tumor and stromal cells, which was related with poor prognosis. LINC00862 expression was related with immune cell infiltration and immune checkpoints expression, and had a high predictive value for immunotherapy efficacy. Mechanistically, LINC00862 competitively bound to miR-29c-3p to unleash SIRT1’s tumor-promoting function. SIRT1 inhibitor-EX527 were screened by virtual screening and verified by in vitro and vivo assays. Notably, acetyltransferase P300-mediated super-enhancer activity stimulated LINC00862 transcription. Collectively, LINC00862 could be a diagnostic and prognostic biomarker. LINC00862 could also be a predictive biomarker for immunotherapy efficacy. Super-enhancer activity is the driver for LINC00862 overexpression in cervical cancer and gastric cancer.

Baseline serum testosterone and differential efficacy of bipolar androgen therapy and enzalutamide in the randomized TRANSFORMER trial.

Bipolar androgen therapy (BAT) is effective in a subset of metastatic castration-resistant prostate cancer (mCRPC) patients. Treatment selection biomarkers are needed due to other therapies that can be equally efficacious. We performed post-hoc analysis to determine whether baseline serum testosterone (T) is a treatment selection marker in the TRANSFORMER study, a randomized trial of abiraterone-pretreated mCRPC patients assigned to BAT (n = 94) or enzalutamide (n = 101). The findings suggest that patients with poor outcomes to abiraterone and serum T ≥ 20 ng/dL may benefit preferentially from BAT over enzalutamide. Baseline testosterone could be considered in the treatment selection process when BAT is an option.

Abstract PO1-15-01: Digital pathology models reveal case-specific characteristics of the tumor microenvironment

Abstract Background Phenotypic characteristics and genetic content have been observed to vary within individual tumors. However, translational research and some clinical practices often rely on extrapolating single histopathology slides to be representative of whole-tumor biology, even when the extent of intra-tumor biological heterogeneity is unknown. In addition, technical factors in slide preparation and digitization can also contribute to variability. Here, we use digital pathology models to identify cell and tissue types in whole-slide images of breast cancer tumors, and quantify intra- and inter-case heterogeneity in cell and tissue features of the tumor microenvironment. Methods We developed PathExplore, a suite of convolutional neural network models trained on pathologist annotations of cell and tissue types in hematoxylin and eosin-stained slides. The models were deployed on the TCGA breast cancer dataset (n=1083 primary solid tumors). Quantitative human-interpretable features (HIFs) relating to cancer, stromal, and necrotic tissue areas, as well as the abundance and distribution of cancer cells, fibroblasts, and immune cells within these tissues, were extracted for each slide. Similarity between slides on sets of HIFs was assessed using Pearson correlation. Intra- and inter-case variability of individual HIFs was measured using the normalized percent difference (range divided by mean) for each slide pair. Case-specificity was quantified by the AUC of correlation or difference distributions for intra-case vs inter-case slide pairs. Only pairs of slides with matching metadata, including tissue source site, cancer stage, and scanner model, were considered for inter-case analysis. Results A total of 55 cases, comprising 114 slides, were identified as having more than one slide per case. Considering all 123 proportional HIFs, intra-case slide pairs showed high correlation compared to inter-case pairs (r=0.97 vs r=0.90, AUC=0.88), with 29% of slides coming from a multi-slide case most closely correlated with another slide from the same case out of the entire TCGA breast dataset. Subsets of these proportional HIFs relating to each identified cell type were also case-specific, with AUC’s ranging from 0.79 for macrophage HIFs to 0.87 for cancer cell HIFs. All proportion, density, and ratio HIFs (n=297) individually showed case specificity (AUC &amp;gt;0.5), with median intra-case differences ranging from 0.6% to 69%. Area proportion of necrosis was more variable than cancer or stroma tissue, while cancer cell count proportions were less variable than fibroblast or immune cell proportions. Cell count proportions were in general less variable and more specific than their corresponding density HIFs; for instance, the frequency of fibroblasts out of all cells in stroma had a median intra-case difference of 11% compared to 20% for the density of fibroblasts in stroma. Conclusions We quantified heterogeneity of key features of the tumor microenvironment both within and across tumors. These results reveal biological and technical variability that can inform selection and interpretation of biomarkers derived from single slides. The ability to uniquely identify slides from the same case additionally demonstrates the technical robustness of digital pathology models for yielding quantitative insights into tumor biology. Citation Format: Ylaine Gerardin, Christian Kirkup, Archit Khosla, Laura Chambre, Michael Drage, Amaro Taylor-Weiner. Digital pathology models reveal case-specific characteristics of the tumor microenvironment [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-15-01.

Abstract PO3-04-12: SUMIT-BC: Phase 2 randomized study of fulvestrant with or without the cyclin-dependent kinase 7 inhibitor (CDK7i) samuraciclib in advanced hormone receptor positive (HR+) breast cancer after CDK4/6i

Abstract Background: CDK7 has 3 critical roles in cancer: enhanced transcription of oncogenes and upregulation of anti-apoptotic genes, acceleration of the cell cycle through phosphorylation of other CDKs and driving estrogen receptor (ER) resistance to hormonal therapy. Inhibition of CDK7 is therefore a potential novel anti-cancer therapeutic strategy. In an initial single-arm evaluation samuraciclib (CT7001), a once daily (QD) oral CDK7 inhibitor has demonstrated a favourable safety profile and clinical activity in combination with fulvestrant, a selective estrogen receptor degrader (SERD), in patients with HR+/HER2- advanced breast cancer who have previously been treated with a CDK4/6 inhibitor. There was evidence of enhanced benefit in patients with no detectable TP53 mutation from baseline circulating tumor DNA (ctDNA) analysis and in patients without baseline liver metastases [1]. Samuraciclib is associated with low grade gastrointestinal (GI) adverse events such as nausea, vomiting and diarrhea managed with simple prophylaxis and patient counselling. An instant release capsule formulation was used in the initial clinical evaluation of samuraciclib requiring patients to take multiple capsules designed to rapidly release a large amount of material high in the GI tract. In this study a novel single tablet formulation will be administered which may enhance GI tolerability (2). This Phase 2 open-label randomised study will evaluate the efficacy, safety, pharmacokinetics and Quality of Life (QoL) impact of samuraciclib in combination with fulvestrant in comparison to a fulvestrant monotherapy control arm. Consistent with the principles of the current Project OPTIMUS initiative, 2 dose levels of samuraciclib will be evaluated [3]. All patients will undergo baseline ctDNA evaluation of TP53 mutation status to permit a prospective evaluation of its patient selection biomarker potential. Trial Design: Eligible patients will provide written informed consent, be aged 18 years or older, have histologically or cytologically confirmed ER+/HER2- advanced or metastatic breast cancer not amenable to resection or radiotherapy of curative intent, have received an aromatase inhibitor in combination with a CDK4/6 inhibitor in either the adjuvant or advanced setting, be receiving a luteinizing hormone-releasing hormone agonist if pre/perimenopausal and have RECIST v1.1 evaluable disease. Prior SERD, mammalian target of rapamycin inhibitor (mTORi) or chemotherapy for advanced breast cancer are not permitted. All patients will undergo baseline Guardant360 ctDNA analysis to establish their TP53 mutation status among others. 60 patients will be enrolled and will all receive fulvestrant 500mg IM administered on days 1, 15 and 29 and then monthly thereafter. Patients will be randomized 1:1:1 to fulvestrant alone, fulvestrant and samuraciclib 240mg QD or fulvestrant and samuraciclib 360mg QD. Patients will undergo RECIST v1.1 evaluation at baseline every 8-weeks until week 48, followed by every 12-weeks thereafter. The pharmacokinetics of samuraciclib and fulvestrant will be studied though the first 6 months of the study, with highest intensity during month 1. To evaluate Quality of Life (QoL) The Functional Assessment of Cancer Therapy -Breast questionnaire (FACT-B) will be completed. The primary endpoint is clinical benefit response at 24 weeks. Secondary endpoints are tolerability, progression free survival, overall response rate, duration of response, and the pharmacokinetics of fulvestrant and samuraciclib. QoL and correlations between ctDNA detectable TP53 mutations and efficacy/safety finding in this patient population will be reported. The study opened for recruitment in June 2023.

Intestinal microbiota and gene expression alterations in leopard coral grouper (Plectropomus leopardus) under enteritis

Enteritis poses a significant threat to fish farming, characterized by symptoms of intestinal and hepatic inflammation, physiological dysfunction, and dysbiosis. Focused on the leopard coral grouper (Plectropomus leopardus) with an enteritis outbreak on a South China Sea farm, our prior scrutiny did not find any abnormalities in feeding or conventional water quality factors, nor were any specific pathogen infections related to enteritis identified. This study further elucidates their intestinal flora alterations, host responses, and their interactions to uncover the underlying pathogenetic mechanisms and facilitate effective prevention and management strategies. Enteritis-affected fish exhibited substantial differences in intestinal flora compared to control fish (P = 0.001). Notably, norank_f_Alcaligenaceae, which has a negative impact on fish health, predominated in enteritis-affected fish (91.76 %), while the probiotic genus Lactococcus dominated in controls (93.90 %). Additionally, certain genera with pathogenesis potentials like Achromobacter, Sphingomonas, and Streptococcus were more abundant in diseased fish, whereas Enterococcus and Clostridium_sensu_stricto with probiotic potentials were enriched in control fish. At the transcriptomic level, strong inflammatory responses, accompanied by impaired metabolic functions, tissue damage, and iron death signaling activation were observed in the intestines and liver during enteritis. Furthermore, correlation analysis highlighted that potential pathogen groups were positively associated with inflammation and tissue damage genes while presenting negatively correlated with metabolic function-related genes. In conclusion, dysbiosis in the intestinal microbiome, particularly an aberrantly high abundance of Alcaligenaceae with pathogenic potential may be the main trigger for this enteritis outbreak. Alcaligenaceae alongside Achromobacter, Sphingomonas, and Streptococcus emerged as biomarkers for enteritis, whereas some species of Lactococcus, Clostridium_sensu_stricto, and Enterococcus showed promise as probiotics to alleviate enteritis symptoms. These findings enhance our understanding of enteritis pathogenesis, highlight intestinal microbiota shifts in leopard coral grouper, and propose biomarkers for monitoring, probiotic selection, and enteritis management.

Aryl hydrocarbon receptor ligand supplementation impacts colitis-associated depressive-like behavior

Abstract Colitis is an inflammatory bowel disease (IBD) with increased incidences of depression in patients. The mechanisms that define this comorbidity remain poorly understood. Our lab previously showed supplementation with indole-3-carbinol (I3C), an aryl hydrocarbon receptor (AhR) ligand, can reduce disease severity in models of colitis. We aimed to determine the behavioral impact I3C supplementation has on colitis-induced depression via alterations in the gut metabolome. Colitis was induced in using the dextran sodium sulfate (DSS) method and treatment groups were given a regimen of 40 mg/kg I3C as previously reported. Untargeted metabolomic studies revealed quinolinic acid (QA), a metabolite produced by the kynurenine (KYN) pathway and linked to depression, was found to be significantly reduced in I3C-treated mice when compared to colitis controls. To determine the effects of I3C and QA modulation on depressive-like behavior, colitis mice were treated with either I3C or an inhibitor of a major enzyme involved in QA production. Depressive-like behavior was measured using the Tail Suspension Test (TST) method, along with evaluation of neural biomarkers of depression (dopamine, BDNF, GFAP) and stabilization of the blood brain barrier (BBB). Results showed I3C reduced depressive-like behavior and altered select biomarkers associated with depression. These studies provide evidence that AhR can be a potential therapeutic target for both colitis and colitis-associated depression.

Combination treatment with PD1/PDL-1 inhibitors for sarcomas: state of the art, next questions.

Only a small fraction of sarcomas exhibit recognized parameters of immune sensitivity, such as tumor mutational burden, PDL-1 expression, or microsatellite instability. Combined strategies aimed to modulate tumor microenvironment to increase the efficacy of PD1/PDL-1 inhibitors in sarcoma. Most explored prospective studies were based on combinations of PD1/PDL-1 inhibitors with antiangiogenics, other immune checkpoints, or chemotherapy. Results on 6-month PFS rate, median PFS, and ORR in trials using PD1/PDL-1 inhibitors plus antiangiogenics ranged respectively as 46.9-55%, 4.7-7.8 months and 21-36.7%. In combination with other immune checkpoint inhibitors, the results of median PFS and ORR ranged from 2.8-4.1 months and 10-16%, respectively. In combination with chemotherapy, the best results were obtained with doxorubicin-based regimens compared to other agents. Duplet-based chemotherapy plus anti-PD1/PDL-1 obtained the highest ORR (56.2%) compared with doxorubicin (19-36.7%). Currently, the most robust predictive biomarker for anti-PD1/PDL-1 efficacy is the presence of tertiary lymphoid structures (TLS) with mature dendritic cells. Even when direct comparisons between PD1/PDL-1 inhibitor-based combinations and single agents have not been performed yet in sarcoma, some combinations appear promising. Studies controlling heterogeneity by biomarker or histotype selection contribute to an increase in efficacy or knowledge crucial for future comparative trials.

Addressing the Challenges of PD-1 Targeted Immunotherapy in Cancer Treatment

Background: Immune checkpoint inhibitors targeting the programmed cell death protein 1 (PD-1)/PD-ligand 1 (PD-L1) axis have revolutionized cancer treatment, demonstrating remarkable clinical efficacy across multiple malignancies. However, their broader applicability and therapeutic potential remain constrained by several challenges. Objective: This review aims to provide a comprehensive overview of the current challenges associated with PD-1 targeted immunotherapy, encompassing resistance mechanisms, patient selection, toxicity management, and the development of novel combination strategies. Methods: A comprehensive literature search was conducted across PubMed, Embase, and Web of Science databases to identify and critically analyze studies investigating the challenges and limitations of PD-1 targeted immunotherapy in cancer treatment. Results: The primary challenges identified include: (1) Intrinsic and acquired resistance mechanisms, such as alterations in antigen presentation, tumor microenvironment factors, and immune cell dysfunction; (2) Lack of reliable predictive biomarkers for patient selection and response monitoring; (3) Immune-related adverse events and their effective management; (4) Optimization of combination regimens with other immunotherapies, targeted therapies, or conventional treatments; (5) Financial and accessibility barriers limiting the broader implementation of immunotherapy. Conclusion: PD-1 targeted immunotherapy has transformed cancer treatment, addressing the current challenges is imperative to maximize its therapeutic potential and broaden its applicability. Ongoing research efforts focused on elucidating resistance mechanisms, developing predictive biomarkers, managing toxicities, and exploring novel combination strategies hold promise for overcoming these limitations. Interdisciplinary collaborations and continued investment in immunotherapy research are essential to ensure that the benefits of these groundbreaking therapies are accessible to a wider patient population.

Combined effect of freshwater salinization and harmful algae on the benthic invertebrate Chironomus pallidivittatus

Global climate change as well as human activities have been reported to increase the frequency and severity of both salinization and harmful algal blooms (HABs) in many freshwater systems, but their co-effect on benthic invertebrates has rarely been studied. This study simultaneously examined the joint toxicity of salinity and different cyanobacterial diets on the behavior, development, select biomarkers, and partial life cycle of Chironomus pallidivittatus (Diptera). High concentrations of salts (e.g., 1 g/L Ca2+ and Mg2+) and toxic Microcystis had synergistic toxicity, inhibiting development, burrowing ability and causing high mortality of C. pallidivittatus, especially for the Mg2+ treatment, which caused around 90% death. Low Ca2+ concentration (e.g., 0.01 g/L) promoted larval burrowing ability and inhibited toxin accumulation, which increased the tolerance of Chironomus to toxic Microcystis. However, low Mg2+ concentration (e.g., 0.01 g/L) was shown to inhibit the behavior, development and increase algal toxicity to Chironomus. Toxic Microcystis resulted in microcystin (MC) accumulation, inhibited the burrowing ability of larvae, and increased the proportion of male adults (>50%). The combined toxicity level from low to high was verified by the weight of evidence and the grey TOPSIS model, which integrated five lines of evidence to increase the risk assessment accuracy and efficiency. This is the first study that provided insights into ecological risk arising from the joint effect of salinity and harmful algae on benthic organisms. We suggest that freshwater salinization and HABs should be considered together when assessing ecological threats that arise from external stress.

Circulating Tumor DNA in Diffuse Large B-Cell Lymphoma: from Bench to Bedside?

Diffuse large B-cell lymphoma (DLBCL) is a curable disease with variable outcomes due to underlying heterogeneous clinical and molecular features-features that are insufficiently characterized with our current tools. Due to these limitations, treatment largely remains a "one-size-fits-all" approach. Circulating tumor DNA (ctDNA) is a novel biomarker in cancers that is increasingly utilized for risk stratification and response assessment. ctDNA is readily detectable from the plasma of patients with DLBCL but has not yet been incorporated into clinical care to guide treatment. Here, we describe how ctDNA sequencing represents a promising technology in development to personalize the care of patients with DLBCL. We will review the different types of ctDNA assays being studied and the rapidly growing body of evidence supporting the utility of ctDNA in different treatment settings in DLBCL. Risk stratification by estimation of tumor burden and liquid genotyping, molecular response assessment during treatment, and monitoring for measurable residual disease (MRD) to identify therapy resistance and predict clinical relapse are all potential applications of ctDNA. It is time for clinical trials in DLBCL to utilize ctDNA as an integral biomarker for patient selection, response-adapted designs, and surrogate endpoints. As more ctDNA assays become commercially available for routine use, clinicians should consider liquid biopsy when treatment response is equivocal on imaging. Incorporating MRD may also guide decision-making if patients experience severe treatment toxicities. Though important barriers remain, we believe that ctDNA will soon be ready to transition from bench to bedside to individualize treatment for our patients with DLBCL.

Proteomics-The State of the Field: The Definition and Analysis of Proteomes Should Be Based in Reality, Not Convenience.

With growing recognition and acknowledgement of the genuine complexity of proteomes, we are finally entering the post-proteogenomic era. Routine assessment of proteomes as inferred correlates of gene sequences (i.e., canonical 'proteins') cannot provide the necessary critical analysis of systems-level biology that is needed to understand underlying molecular mechanisms and pathways or identify the most selective biomarkers and therapeutic targets. These critical requirements demand the analysis of proteomes at the level of proteoforms/protein species, the actual active molecular players. Currently, only highly refined integrated or integrative top-down proteomics (iTDP) enables the analytical depth necessary to provide routine, comprehensive, and quantitative proteome assessments across the widest range of proteoforms inherent to native systems. Here we provide a broad perspective of the field, taking in historical and current realities, to establish a more balanced understanding of where the field has come from (in particular during the ten years since Proteomes was launched), current issues, and how things likely need to proceed if necessary deep proteome analyses are to succeed. We base this in our firm belief that the best proteomic analyses reflect, as closely as possible, the native sample at the moment of sampling. We also seek to emphasise that this and future analytical approaches are likely best based on the broad recognition and exploitation of the complementarity of currently successful approaches. This also emphasises the need to continuously evaluate and further optimize established approaches, to avoid complacency in thinking and expectations but also to promote the critical and careful development and introduction of new approaches, most notably those that address proteoforms. Above all, we wish to emphasise that a rigorous focus on analytical quality must override current thinking that largely values analytical speed; the latter would certainly be nice, if only proteoforms could thus be effectively, routinely, and quantitatively assessed. Alas, proteomes are composed of proteoforms, not molecular species that can be amplified or that directly mirror genes (i.e., 'canonical'). The problem is hard, and we must accept and address it as such, but the payoff in playing this longer game of rigorous deep proteome analyses is the promise of far more selective biomarkers, drug targets, and truly personalised or even individualised medicine.

Dual-Aptamer Recognition of DNA Logic Gate Sensor-Based Specific Exosomal Proteins for Ovarian Cancer Diagnosis.

Clinical diagnosis of ovarian cancer lacks high accuracy due to the weak selection of specific biomarkers along with the circumstance biomarkers localization. Clustering analysis of proteins transported on exosomes enables a more precise screening of effective biomarkers. Herein, through bioinformatics analysis of ovarian cancer and exosome proteomes, two coexpressed proteins, EpCAM and CD24, specifically enriched, were identified, together with the development of an as-derived dual-aptamer targeted exosome-based strategy for ovarian cancer screening. In brief, a DNA ternary polymer with aptamers targeting EpCAM and CD24 was designed to present a logic gate reaction upon recognizing ovarian cancer exosomes, triggering a rolling circle amplification chemiluminescent signal. A dynamic detection range of 6 orders of magnitude was achieved by quantifying exosomes. Moreover, for clinical samples, this strategy could accurately differentiate exosomes from healthy persons, other cancer patients, and ovarian cancer patients, enabling promising in situ detection. By accurately selecting biomarkers and constructing a dual-targeted exosomal protein detection strategy, the limitation of insufficient specificity of traditional protein markers was circumvented. This work contributed to the development of exosome-based prognosis monitoring in ovarian cancer through the identification of disease-specific exosome protein markers.

There and Back Again: A Perspective on 20 Years of CYP4Z1.

Cytochrome P450 (CYP)4Z1, a highly expressed CYP gene in breast cancer, was one of the last CYPs to be identified in the human genome, some 20 years ago. CYP4 enzymes typically catalyze ω-hydroxylation and metabolize ω3 and ω6 polyunsaturated fatty acids to bioactive lipid metabolites that can influence tumor growth and metastasis. These attributes of CYP4Z1 make it an attractive target for new chemotherapeutic drug design, as a potential biomarker for selection of patients that might respond favorably to drugs and for developing enzyme inhibitors as potential therapeutic agents. This review summarizes the current state of knowledge regarding the advancing biochemistry of CYP4Z1, its role in breast cancer, and the recent synthesis of selective chemical inhibitors of the enzyme. We identify gaps that need to be filled to further advance this field and present new experimental data on recombinant CYP4Z1 expression and purification of the active catalytic form. SIGNIFICANCE STATEMENT: In breast cancer, an unmet need is the availability of highly effective therapeutic agents, especially for triple negative breast cancer. The relevance of the work summarized in this mini-review is that it identifies a new potential drug target, CYP4Z1, and discusses ways in which the gene product's catalytic activity might be modulated in order to combat this malignancy and limit its spread.