Prediction of Response to FDA-Approved Targeted Therapy and Immunotherapy in Acute Lymphoblastic Leukemia (ALL).

OPINION STATEMENT: Acute lymphoblastic leukemia (ALL) represents the predominant cancer in pediatric populations, though its occurrence in adults is relatively rare. Pre-treatment risk stratification is crucial for predicting prognosis. Important factors for assessment include patient age, white blood cell (WBC) count at diagnosis, extramedullary involvement, immunophenotype, and cytogenetic aberrations. Minimal residual disease (MRD), primarily assessed by flow cytometry following remission, plays a substantial role in guiding management plans. Over the past decade, significant advancements in ALL outcomes have been witnessed. Conventional chemotherapy has remarkably reduced mortality rates; however, its intensive nature raises safety concerns and has led to the emergence of treatment-resistant cases with recurrence of relapses. Consequently, The U.S. Food and Drug Administration (FDA) has approved several novel treatments for relapsed/refractory ALL due to their demonstrated efficacy, as indicated by improved complete remission and survival rates. These treatments include tyrosine kinase inhibitors (TKIs), the anti-CD19 monoclonal antibody blinatumomab, anti-CD22 inotuzumab ozogamicin, anti-CD20 rituximab, and chimeric antigen receptor (CAR) T-cell therapy. Identifying the variables that influence treatment decisions is a pressing necessity for tailoring therapy based on heterogeneous patient characteristics. Key predictive factors identified in various observational studies and clinical trials include prelymphodepletion disease burden, complex genetic abnormalities, and MRD. Furthermore, the development of serious adverse events following treatment could be anticipated through predictive models, allowing for appropriate prophylactic measures to be considered. The ultimate aim is to incorporate the concept of precision medicine in the field of ALL through valid prediction platform to facilitate the selection of the most suitable treatment approach.

Prognostic and predictive biomarkers with therapeutic targets in nonsmall-cell lung cancer: A 2023 update on current development, evidence, and recommendation.

BACKGROUND: Since the publication of the original work in 2014, significant progress has been made in the characterization of genomic alterations that drive oncogenic addiction of nonsmall cell lung cancer (NSCLC) and how the immune system can leverage non-oncogenic pathways to modulate therapeutic outcomes. This update evaluates and validates the recent and emerging data for prognostic and predictive biomarkers with therapeutic targets in NSCLC. DATA SOURCES: We performed a literature search from January 2015 to October 2023 using the keywords non-small cell lung cancer, clinical practice guidelines, gene mutations, genomic assay, immune cancer therapy, circulating tumor DNA, predictive and prognostic biomarkers, and targeted therapies. STUDY SELECTION AND DATA EXTRACTION: We identified, reviewed, and evaluated relevant clinical trials, meta-analyses, seminal articles, and published clinical practice guidelines in the English language. DATA SYNTHESIS: Regulatory-approved targeted therapies include those somatic gene alterations of EGFR ("classic" mutations, exon 20 insertion, and rare EGFR mutations), ALK, ROS1, BRAF V600, RET, MET, NTRK, HER2, and KRAS G12C. Data for immunotherapy and circulating tumor DNA in next-generation sequencing are considered emerging, whereas the predictive role for PIK3CA gene mutation is insufficient. CONCLUSIONS: Advances in sequencing and other genomic technologies have led to identifying novel oncogenic drivers, novel resistance mechanisms, and co-occurring mutations that characterize NSCLC, creating further therapeutic opportunities. The benefits associated with immunotherapy in the perioperative setting hold initial promise, with their long-term results awaiting.

The Glasgow Prognostic Score Predicts Survival Outcomes in Patients with Extensive-Stage Small Cell Lung Cancer.

INTRODUCTION: The Glasgow prognostic score (GPS) is an inflammation-related score based on C-reactive protein and albumin concentrations. Few studies have assessed the correlation between the GPS and the efficacy of chemotherapy in patients with extensive-stage small cell lung cancer (ES-SCLC). Therefore, this study aimed to evaluate the utility of the GPS in predicting the survival outcomes of patients with ES-SCLC. METHODS: This retrospective study evaluated patients with ES-SCLC who had undergone chemotherapy between February 2008 and November 2021. GPS values were evaluated before the initiation of first-line chemotherapy. The Kaplan-Meier method and Cox proportional hazards models were used to assess progression-free survival (PFS) and overall survival (OS). RESULTS: The GPS values of the 113 patients were zero (54 patients, 48%), 1 (37 patients, 33%), and 2 (22 patients, 19%). The median follow-up duration was 10.7 months. Median PFS was 6.2, 5.6, and 3.8 months in the GPS 0, 1, and 2 groups, respectively, suggesting that the GPS zero group had a significantly more favorable PFS than the GPS 2 group (p < 0.001). Median OS was 17.1, 9.4, and 5.6 months in the GPS 0, 1, and 2 groups, respectively, suggesting that the GPS zero group had a significantly more favorable OS than the GPS 2 group (p = 0.001). Multivariate analysis confirmed that a GPS of 2 independently predicted unfavorable PFS (hazard ratio [HR], 2.89; 95% confidence interval [CI]: 1.68-4.88; p < 0.001) and OS (HR, 3.49 [95% CI: 1.83-6.63], p < 0.001). CONCLUSION: The study's findings suggest that the GPS can predict the survival outcomes of patients with ES-SCLC who have undergone chemotherapy. The GPS is an easy-to-calculate biomarker and would be ideal for routine use in clinical settings.

Neutrophil-to-lymphocyte ratio as a predictive and prognostic marker in children with dilated cardiomyopathy.

OBJECTIVES: We aimed to evaluate neutrophil-to-lymphocyte ratio in children with acute heart failure due to dilated cardiomyopathy, to assess the predictive and prognostic values of neutrophil-to-lymphocyte ratio, and to correlate its levels with brain natriuretic peptide and other various data in these patients. METHOD: We included 50 children with acute heart failure due to dilated cardiomyopathy as the patient group. Fifty healthy children of matched age and sex served as the control group. Patients were evaluated clinically and by echocardiography. A complete blood count with differentiation to evaluate neutrophil-to-lymphocyte ratio was done, and the serum level of brain natriuretic peptide was also measured. All patients were followed up for death or readmission for a period of one year. RESULTS: Neutrophil-to-lymphocyte ratio was significantly higher in patient group as compared to the control group. Neutrophil-to-lymphocyte ratio was significantly increased in patients with higher severity of heart failure. There was a significant increase in neutrophil-to-lymphocyte ratio in patients with bad prognoses compared to those with good prognoses. There was a significant positive correlation between neutrophil-to-lymphocyte ratio and both brain natriuretic peptide and clinical stage of heart failure while there was a significant negative correlation between neutrophil-to-lymphocyte ratio and left ventricular systolic function. The best cut-off of neutrophil-to-lymphocyte ratio to predict adverse outcomes in children with dilated cardiomyopathy was >3.6 with 87% sensitivity and 79% specificity. The cut-off of neutrophil-to-lymphocyte ratio to predict patients who will not respond to conventional treatment was ≥3.85 with 85% sensitivity and 100% specificity. CONCLUSION: Neutrophil-to-lymphocyte ratio is a cheap good predictive and prognostic biomarker in children with dilated cardiomyopathy.

Circulating Ubiquitous RNA, A Highly Predictive and Prognostic Biomarker in Hospitalized Coronavirus Disease 2019 (COVID-19) Patients.

BACKGROUND: Approximately 15-30% of hospitalized coronavirus disease 2019 (COVID-19) patients develop acute respiratory distress syndrome, systemic tissue injury, and/or multi-organ failure leading to death in around 45% of cases. There is a clear need for biomarkers that quantify tissue injury, predict clinical outcomes, and guide the clinical management of hospitalized COVID-19 patients. METHODS: We herein report the quantification by droplet-based digital polymerase chain reaction (ddPCR) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNAemia and the plasmatic release of a ubiquitous human intracellular marker, the ribonuclease P (RNase P) in order to evaluate tissue injury and cell lysis in the plasma of 139 COVID-19 hospitalized patients at admission. RESULTS: We confirmed that SARS-CoV-2 RNAemia was associated with clinical severity of COVID-19 patients. In addition, we showed that plasmatic RNase P RNAemia at admission was also highly correlated with disease severity (P < .001) and invasive mechanical ventilation status (P < .001) but not with pulmonary severity. Altogether, these results indicate a consequent cell lysis process in severe and critical patients but not systematically due to lung cell death. Finally, the plasmatic RNase P RNA value was also significantly associated with overall survival. CONCLUSIONS: Viral and ubiquitous blood biomarkers monitored by ddPCR could be useful for the clinical monitoring and the management of hospitalized COVID-19 patients. Moreover, these results could pave the way for new and more personalized circulating biomarkers in COVID-19, and more generally in infectious diseases, specific from each patient organ injury profile.

Predictive and prognostic value of v-set and transmembrane domain-containing 1 expression in monocytes for coronary artery disease.

The aim of this study was to investigate the correlation between v-set and transmembrane domain-containing 1 (VSTM1) expression and incidence of major adverse cardiac events (MACE) in patients with coronary heart disease (CHD). A total of 310 patients were divided into a non-acute coronary syndrome (non-ACS) group (containing the stable angina group, and the asymptomatic coronary artery diseaseand other patients group) and an ACS group (containing unstable angina and acute myocardial infarction patients). Monocytic VSTM1 expression levels (assessed via average fluorescence intensity derived from antibody binding to VSTM1) in each group were detected and analyzed. The cut-off value of monocytic VSTM1 expression to predict the onset of ACS and MACE was confirmed. VSTM1 expression in monocytes from the ACS group was lower than that of the non-ACS group. The incidence of MACEs in the high VSTM1-expression group was much less than that of those in the low VSTM1 expression group at the 1 year follow-up stage. VSTM1 expression had an independent-inversed association with increased incidence of MACE and ACS. VSTM1 expression in monocytes may help to predict the occurrence of ACS in patients with CHD, and moreover it may provide the means to evaluate MACE prognosis during CHD patient follow-up.

Baseline T1 hyperintense and diffusion-restricted lesions are not linked to prolonged survival in bevacizumab-treated glioblastoma patients of the GLARIUS trial.

PURPOSE: The phase II GLARIUS trial assigned patients with newly diagnosed, O-6-methylguanine-DNA methyltransferase promoter non-methylated glioblastoma to experimental bevacizumab/irinotecan (BEV/IRI) or standard temozolomide (TMZ). To identify subpopulations with a particularly favorable course, we assessed the prognostic potential of magnetic resonance imaging (MRI) markers before treatment onset. METHODS: MRIs at baseline (before treatment onset) were analyzed for T1-hyperintense and diffusion-restricted lesions; as well as the presence of both hyperintense and diffusion-restricted (double positive) lesions. The MRI findings were correlated with overall and progression-free survival. RESULTS: MRI scans were evaluable in 71% of the GLARIUS modified intention-to-treat population (n = 121 of 170; 88 patients in the BEV/IRI arm, and 33 patients in the TMZ control arm). Diffusion-restricted and T1 hyperintense lesions were present in 60% and 65% of patients in BEV/IRI arm, while 57% and 63% were found in the TMZ arm, respectively. Double positive lesions were found in 37% of BEV/IRI patients and in 39% of TMZ patients. Neither the presence of T1-hyperintense, diffusion-restricted lesions, nor double positive lesions were associated with improved survival. CONCLUSIONS: Baseline T1-hyperintense and diffusion-restricted lesions are not suitable to predict progression-free or overall survival of patients treated with bevacizumab/irinotecan or temozolomide.

Microsatellite instability in gastric cancer: molecular bases, clinical perspectives, and new treatment approaches.

Gastric cancer is one of the most aggressive malignancies, with limited treatment options in both locally advanced and metastatic setting, resulting in poor prognosis. Based on genomic characterization, stomach tumour has recently been described as a heterogeneous disease composed by different subtypes, each of them with peculiar molecular aspects and specific clinical behaviour. With an incidence of 22% among all western gastric tumour cases, stomach cancer with microsatellite instability was identified as one of these subgroups. Retrospective studies and limited prospective trials reported differences between gastric cancers with microsatellite stability and those with instability, mainly concerning clinical and pathological features, but also in regard to immunological microenvironment, correlation with prognostic value, and responses to treatment. In particular, gastric cancer with microsatellite instability constitutes a small but relevant subgroup associated with older age, female sex, distal stomach location, and lower number of lymph-node metastases. Emerging data attribute to microsatellite instability status a favourable prognostic meaning, whereas the poor outcomes reported after perioperative chemotherapy administration suggest a detrimental role of cytotoxic drugs in this gastric cancer subgroup. The strong immunogenicity and the widespread expression of immune-checkpoint ligands make microsatellite instability subtype more vulnerable to immunotherapeutic approach, e.g., with anti-PD-L1 and anti-CTLA4 antibodies. Since gastric cancer with microsatellite instability shows specific features and clinical behaviour not overlapping with microsatellite stable disease, microsatellite instability test might be suitable for inclusion in a diagnostic setting for all tumour stages to guarantee the most targeted and effective treatment to every patient.

Role of ER-α36 in breast cancer by typical xenoestrogens.

About 10 years have passed since the discovery of the estrogen receptor subtype, estrogen receptor alpha 36 (ER-α36). The relationship between cancerous cells and ER-α36 in mediating xenoestrogens (XEs) is a significant issue in the progression and treatment of breast cancer. XEs can combine with classical estrogen receptors and other receptor subtypes especially ER-α36, resulting in activation of nongenomic pathways as well as genomic pathways. Recently, most laboratories have focused on further study into the rapidly nongenomic mechanisms by overexpressing or knocking down ER-α36 in breast cancer cell lines. These rapid responses can induce the deregulation of cell cycle, and then lead to the abnormal proliferation and differentiation by regulating distinct downstream pathways. It appears that ER-α36 is a key factor in increasing risk of breast cancer. However, in several recent studies, the action mechanisms of ER-α36 by XEs in breast cancer cell lines are not always clear. In this review, we firstly summarize the expression pattern and tumor biology of ER-α36, then discuss these related estrogenic effects of ER-α36, and lastly give the predictive and prognostic value of ER-α36 as diagnostic marker by mediating typical XEs in breast cancer.

Novel ultrasensitive automated kinetic exclusion assay for measurement of plasma levels of soluble PD-L1, the predictive and prognostic biomarker in cancer patients treated with immune checkpoint inhibitors.

Recently, the blood plasma or serum levels of soluble programmed death protein 1 (PD-L1), but not tissue PD-L1 expression level, have been proposed as an effective predictive and prognostic biomarker in patients treated with immune checkpoint inhibitors for different types of cancers. The quantification of soluble PD-L1 in blood will provide a quick evaluation of patients' immune status; however, the available assays have limitations in their sensitivity, reproducibility, and accuracy for use in clinical settings. To overcome these problems, this study was dedicated to developing an ultrasensitive automated flow-based kinetic exclusion assay (KinExA) for the accurate and precise measurement of soluble PD-L1 in plasma. The assay was developed with the assistance of KinExA™ 3200 biosensor. In this assay, PD-L1 in its calibrator or plasma sample solution was pre-equilibrated with anti-PD-L1 monoclonal antibody. The equilibrated mixture solution was then passed rapidly over PD-L1 protein that has been coated onto polymethylmethacrylate beads consolidated as a microcolumn in the observation cell of the KinExA™ biosensor. The free anti- PD-L1 antibody was bound to the immobilized PD-L1, however, the unbound molecules were removed from the beads microcolumn by flushing the system with phosphate-buffered saline. Fluorescein-labeled secondary antibody was passed rapidly over the beads, and the fluorescence signals were monitored during the flow of the labeled antibody through the beads. The calibration curve was generated by plotting the binding percentages as a function of PD-L1 concentrations in its sample solution. The working range of the assay with very a good correlation coefficient on a 4-parameter equation (r = 0.9992) was 0.5 - 100 pg mL─1. The assay limit of detection and quantitation were 0.15 and 0.5 pg mL─1, respectively. The recovery values of plasma-spiked PD-L1 were in the range of 96.4-104.3 % (±3.7-6.2 %). The precision of the assay was satisfactory; the values of the coefficient of variations did not exceed 6.2 % for both intra- and inter-day precision. The automated analysis by the proposed KinExA facilitates the processing of many specimens in clinical settings. The overall performance of the proposed KinExA is superior to the available assays for plasma levels of soluble PD-L1. The proposed assay is anticipated to have a great value in the measurement of PD-L1 where a more confident result is needed.

Rheumatoid arthritis-associated interstitial lung disease hotspots and future directions: A Web-of-Science based scientometric and visualization study.

OBJECTIVE: To identify new trends and potential hotspots in research on rheumatoid arthritis-associated interstitial lung disease (RA-ILD). MATERIALS AND METHODS: The Web of Science (WOS) database was used to search for RA-ILD-related literature published between August 31, 2002 and August 31, 2022. CiteSpace 6.1.R3, VOSviewer version 1.6.17, Scimago Graphica, and Pajek V2.0 visualization software were used to conduct a comprehensive analysis and network visualization mapping of the authors, countries, institutions, journals, cited references, and keywords. RESULTS: A total of 2412 articles were retrieved, and the number of articles published has grown annually since 2002. Eric L. Matteson was the most prolific author, and the Mayo Clinic and UNITED STATES have the highest publishing volume and influence. Clinical Rheumatology is the journal with the most papers published. Rheumatology was the most cited journal. The citation clusters and keywords concentrated on the mechanism, treatment, and predictive and prognostic factors. CONCLUSION: Pathogenesis, treatment, and predictive and prognostic factors were among the RA-ILD research directions and hotspots. Antirheumatoid drugs, especially biologics and small molecule inhibitors, were among the most actively researched treatment options. The results of this study provides an in-depth understanding of the development of RA-ILD publications, aids researchers in understanding hotspots and trends and provides a new perspective for future RA-ILD research.

Biomarkers for Outcome in Metastatic Melanoma in First Line Treatment with Immune Checkpoint Inhibitors.

INTRODUCTION: A high proportion of metastatic melanoma patients do not respond to immune checkpoint inhibitors (ICI), and until now, no validated biomarkers for response and survival have been known. METHODS: We performed a retrospective analysis of outcomes in patients with metastatic melanoma treated with first-line ICI at the Institute of Oncology Ljubljana from January 2018 to December 2020. The immune-related adverse events (irAEs) and serum immune-inflammation parameters (neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (LR), systemic immune-inflammation index (SII) and pan-immune-inflammation value (PIV)) were analyzed as potential biomarkers for response and survival. Survival rates were calculated using the Kaplan-Meier method and then compared with the log-rank test. Multivariate regression Cox analysis was used to determine independent prognostic factors for progression-free survival (PFS) and overall survival (OS). RESULTS: Median follow-up was 22.5 months. The estimated median progression-free survival (PFS) was 15 months (95% CI 3.3-26.2). The two-year survival rate (OS) was 66.6%. Among 129 treated patients, 24 (18.6%) achieved complete response, 28 (21.7%) achieved partial response, 26 (20.2%) had stable disease and 51 (39.5%) patients experienced a progressive disease. There was a higher response rate in patients with irAEs (p < 0.001) and high NLR before the second cycle of ICI (p = 0.052). Independent prognostic factors for PFS were irAE (HR 0.41 (95% CI 0.23-0.71)), SII before the first cycle of ICI (HR 1.94 (95% CI 1.09-3.45)) and PLR before the second cycle of ICI (HR 1.71 (95% CI 1.03-2.83)). The only independent prognostic factor for OS was SII before the first cycle of ICI (HR 2.60 (95% CI 0.91-7.50)). CONCLUSIONS: Patients with high pre-treatment levels of SII had a higher risk of progression and death; however, patients with irAEs in the high-SII group might respond well to ICI. Patients who develop irAEs and have high NLRs before the second ICI application have higher rates of CR and PR, which implicates their use as early biomarkers for responsiveness to ICI.

The Prognostic and Predictive Value of Human Gastrointestinal Microbiome and Exosomal mRNA Expression of PD-L1 and IFNγ for Immune Checkpoint Inhibitors Response in Metastatic Melanoma Patients: PROTOCOL TRIAL.

BACKGROUND: Immunotherapy has been successful in treating advanced melanoma, but a large proportion of patients do not respond to the treatment with immune checkpoint inhibitors (ICIs). Preclinical and small cohort studies suggest gastrointestinal microbiome composition and exosomal mRNA expression of PD-L1 and IFNγ from the primary tumor, stool and body fluids as potential biomarkers for response. METHODS: Patients treated with immune checkpoint inhibitors as a first line treatment for metastatic melanoma are recruted to this prospective study. Stool samples are submitted before the start of treatment, at the 12th (+/-2) week and 28th (+/-2) week, and at the occurrence of event (suspected disease progression/hyperprogression, immune-related adverse event (irAE), deterioration). Peripheral venous blood samples are taken additionally at the same time points for cytologic and molecular tests. Histological material from the tumor tissue is obtained before the start of immunotherapy treatment. Primary objectives are to determine whether the human gastrointestinal microbiome (bacterial and viral) and the exosomal mRNA expression of PD-L1 and IFNγ and its dynamics predicts the response to treatment with PD-1 and CTLA-4 inhibitors and its association with the occurrence of irAE. The response is evaluated radiologically with imaging methods in accordance with the irRECIST criteria. CONCLUSIONS: This is the first study to combine and investigate multiple potential predictive and prognostic biomarkers and their dynamics in first line ICI in metastatic melanoma patients.

Distinct mesenchymal cell states mediate prostate cancer progression.

Alterations in tumor stroma influence prostate cancer progression and metastatic potential. However, the molecular underpinnings of this stromal-epithelial crosstalk are largely unknown. Here, we compare mesenchymal cells from four genetically engineered mouse models (GEMMs) of prostate cancer representing different stages of the disease to their wild-type (WT) counterparts by single-cell RNA sequencing (scRNA-seq) and, ultimately, to human tumors with comparable genotypes. We identified 8 transcriptionally and functionally distinct stromal populations responsible for common and GEMM-specific transcriptional programs. We show that stromal responses are conserved in mouse models and human prostate cancers with the same genomic alterations. We noted striking similarities between the transcriptional profiles of the stroma of murine models of advanced disease and those of of human prostate cancer bone metastases. These profiles were then used to build a robust gene signature that can predict metastatic progression in prostate cancer patients with localized disease and is also associated with progression-free survival independent of Gleason score. Taken together, this offers new evidence that stromal microenvironment mediates prostate cancer progression, further identifying tissue-based biomarkers and potential therapeutic targets of aggressive and metastatic disease.

Validation of Messenger Ribonucleic Acid Markers Differentiating Among Human Acute Respiratory Distress Syndrome Subgroups in an Ovine Model of Acute Respiratory Distress Syndrome Phenotypes.

Background: The discovery of biological subphenotypes in acute respiratory distress syndrome (ARDS) might offer a new approach to ARDS in general and possibly targeted treatment, but little is known about the underlying biology yet. To validate our recently described ovine ARDS phenotypes model, we compared a subset of messenger ribonucleic acid (mRNA) markers in leukocytes as reported before to display differential expression between human ARDS subphenotypes to the expression in lung tissue in our ovine ARDS phenotypes model (phenotype 1 (Ph1): hypoinflammatory; phenotype 2 (Ph2): hyperinflammatory). Methods: We studied 23 anesthetized sheep on mechanical ventilation with observation times between 6 and 24 h. They were randomly allocated to the two phenotypes (n = 14 to Ph1 and n = 9 to Ph2). At study end, lung tissue was harvested and preserved in RNAlater. After tissue homogenization in TRIzol, total RNA was extracted and custom capture and reporter probes designed by NanoString Technologies were used to measure the expression of 14 genes of interest and the 6 housekeeping genes on a nCounter SPRINT profiler. Results: Among the 14 mRNA markers, in all animals over all time points, 13 markers showed the same trend in ovine Ph2/Ph1 as previously reported in the MARS cohort: matrix metalloproteinase 8, olfactomedin 4, resistin, G protein-coupled receptor 84, lipocalin 2, ankyrin repeat domain 22, CD177 molecule, and transcobalamin 1 expression was higher in Ph2 and membrane metalloendopeptidase, adhesion G protein-coupled receptor E3, transforming growth factor beta induced, histidine ammonia-lyase, and sulfatase 2 expression was higher in Ph1. These expression patterns could be found when different sources of mRNA - such as blood leukocytes and lung tissue - were compared. Conclusion: In human and ovine ARDS subgroups, similar activated pathways might be involved (e.g., oxidative phosphorylation, NF-κB pathway) that result in specific phenotypes.

The oncogenic and clinical implications of lactate induced immunosuppression in the tumour microenvironment.

The tumour microenvironment is of critical importance in cancer development and progression and includes the surrounding stromal and immune cells, extracellular matrix, and the milieu of metabolites and signalling molecules in the intercellular space. To support sustained mitotic activity cancer cells must reconfigure their metabolic phenotype. Lactate is the major by-product of such metabolic alterations and consequently, accumulates in the tumour. Lactate actively contributes to immune evasion, a hallmark of cancer, by directly inhibiting immune cell cytotoxicity and proliferation. Furthermore, lactate can recruit and induce immunosuppressive cell types, such as regulatory T cells, tumour-associated macrophages, and myeloid-derived suppressor cells which further suppress anti-tumour immune responses. Given its roles in oncogenesis, measuring intratumoural and systemic lactate levels has shown promise as a both predictive and prognostic biomarker in several cancer types. The efficacies of many anti-cancer therapies are limited by an immunosuppressive TME in which lactate is a major contributor, therefore, targeting lactate metabolism is a priority. Developing inhibitors of key proteins in lactate metabolism such as GLUT1, hexokinase, LDH, MCT and HIF have shown promise in preclinical studies, however there is a corresponding lack of success in human trials so far. This may be explained by a weakness of preclinical models that fail to reproduce the complexities of metabolic interactions in natura. The future of these therapies may be as an adjunct to more conventional treatments.

LncRNA CARMN overexpression promotes prognosis and chemosensitivity of triple negative breast cancer via acting as miR143-3p host gene and inhibiting DNA replication.

BACKGROUND: Triple negative breast cancer (TNBC) is a subtype of breast cancer with poor prognosis and lack of effective treatment target. Here we screened differentially expressed lncRNAs through bioinformatics analysis and identified CARMN as a downregulated lncRNA which is lowest expressed in TNBC. We aimed to identify the potential role and molecular mechanisms of CARMN in TNBC. METHODS: Predictive value of CARMN was explored in breast cancer cohorts. TNBC cell lines with CARMN overexpression or CARMN silence and were used for in vitro and in vivo experiments. RNA-seq of CARMN overexpressed cells was performed for exploring downstream of CARMN. RESULTS: CARMN is downregulated at different phase of malignant transformation of breast tissue. CARMN can predict both better prognosis and higher response rate of cisplatin-based neoadjuvant chemotherapy in breast cancer. A nomogram is built to predict cisplatin-based chemotherapy response in breast cancer. Through in vitro and in vivo studies, we confirmed CARMN can also inhibit tumorigenesis and enhance sensitivity to cisplatin in TNBC cells. RNA-seq and further experiments revealed CARMN can inhibit DNA replication. MCM5, an important DNA replication initiation factor, is the most downregulated gene in DNA replication pathway following CARMN overexpression. We confirmed CARMN can produce miR143-3p from its exon5 which is DROSHA and DICER dependent, resulting binding and decrease of MCM5. Moreover, suppressing miR143-3p can weaken function of CARMN in suppressing tumorigenesis and promoting chemosensitivity. CONCLUSIONS: Our results indicated lncRNA CARMN is a predictive biomarker of better prognosis and enhanced cisplatin sensitivity in TNBC. CARMN is the host gene of miR143-3p which downregulates MCM5, causing inhibited DNA replication.

The discovery of biological subphenotypes in ARDS: a novel approach to targeted medicine?

The acute respiratory distress syndrome (ARDS) is a severe lung disorder with a high morbidity and mortality which affects all age groups. Despite active research with intense, ongoing attempts in developing pharmacological agents to treat ARDS, its mortality rate remains unaltered high and treatment is still only supportive. Over the years, there have been many attempts to identify meaningful subgroups likely to react differently to treatment among the heterogenous ARDS population, most of them unsuccessful. Only recently, analysis of large ARDS cohorts from randomized controlled trials have identified the presence of distinct biological subphenotypes among ARDS patients: a hypoinflammatory (or uninflamed; named P1) and a hyperinflammatory (or reactive; named P2) subphenotype have been proposed and corroborated with existing retrospective data. The hyperinflammatory subphenotyope was clearly associated with shock state, metabolic acidosis, and worse clinical outcomes. Core features of the respective subphenotypes were identified consistently in all assessed cohorts, independently of the studied population, the geographical location, the study design, or the analysis method. Additionally and clinically even more relevant treatment efficacies, as assessed retrospectively, appeared to be highly dependent on the respective subphenotype. This discovery launches a promising new approach to targeted medicine in ARDS. Even though it is now widely accepted that each ARDS subphenotype has distinct functional, biological, and mechanistic differences, there are crucial gaps in our knowledge, hindering the translation to bedside application. First of all, the underlying driving biological factors are still largely unknown, and secondly, there is currently no option for fast and easy identification of ARDS subphenotypes. This narrative review aims to summarize the evidence in biological subphenotyping in ARDS and tries to point out the current issues that will need addressing before translation of biological subohenotypes into clinical practice will be possible.

Prognostic and predictive factors in pancreatic cancer.

Pancreatic cancer is one of the leading causes of cancer death worldwide. Its high mortality rate has remained unchanged for years. Radiotherapy and surgery are considered standard treatments in early and locally advanced stages. Chemotherapy is the only option for metastatic patients. Two treatment regimens, i. e. the association of 5-fluorouracil- irinotecan-oxaliplatin (FOLFIRINOX) and the association of nab-paclitaxel with gemcitabine, have been shown to improve outcomes for metastatic pancreatic adenocarcinoma patients. However, there are not standardized predictive biomarkers able to identify patients who benefit most from treatments. CA19-9 is the most studied prognostic biomarker, its predictive role remains unclear. Other clinical, histological and molecular biomarkers are emerging in prognostic and predictive settings. The aim of this review is to provide an overview of prognostic and predictive markers used in clinical practice and to explore the most promising fields of research in terms of treatment selection and tailored therapy in pancreatic cancer.

Prognostic and Predictive Immunohistochemistry-Based Biomarkers in Cancer and Immunotherapy.

Immunotherapy has drastically improved the prognosis of many patients with cancer, but it can also lead to severe immune-related adverse events. Biomarkers, which are molecular markers that indicate a patient's disease outcome or a patient's response to treatment, are therefore crucial to helping clinicians weigh the potential benefits of immunotherapy against its potential toxicities. Immunohistochemistry (IHC) has thus far been a powerful technique for discovery and use of biomarkers such as CD8+ tumor-infiltrating lymphocytes. However, IHC has limited reproducibility. Thus, if more IHC-based biomarkers are to reach the clinic, refinement of the technique using multiplexing or automation is key.