Combination of host immune metabolic biomarkers for the PD-1 blockade cancer immunotherapy

Predictive biomarkers for immune checkpoint inhibitors therapy in lung cancer

Immune checkpoint inhibitors (ICIs) have changed the treatment mode of lung cancer, extending the survival time of patients unprecedentedly. Once patients respond to ICIs, the median duration of response is usually longer than that achieved with cytotoxic or targeted drugs. Unfortunately, there is still a large proportion of lung cancer patients do not respond to ICI. Effective biomarkers are crucial for identifying lung cancer patients who can benefit from them. The first predictive biomarker is programmed death-ligand 1 (PD-L1), but its predictive value is limited to specific populations. With the development of single-cell sequencing and spatial imaging technologies, as well as the use of deep learning and artificial intelligence, the identification of predictive biomarkers has been greatly expanded. In this review, we will dissect the biomarkers used to predict ICIs efficacy in lung cancer from the tumor-immune microenvironment and host perspectives, and describe cutting-edge technologies to further identify biomarkers.

Potential of natural products and gut microbiome in tumor immunotherapy

Immunotherapy is a novel treatment approach for malignant tumors, which has opened a new journey of anti-tumor therapy. Although some patients will show a positive response to immunotherapy, unfortunately, most patients and cancer types do not achieve an ideal response to immunotherapy. Therefore, it is urgent to search for the pathogenesis of sensitized immunotherapy. This review indicates that Fusobacterium nucleatum, Coprobacillus cateniformis, Akkermansia muciniphila, Bifidobacterium, among others, as well as intestinal microbial metabolites are closely associated with resistance to anti-tumor immunotherapy. While natural products of pectin, inulin, jujube, anthocyanins, ginseng polysaccharides, diosgenin, camu-camu, and Inonotus hispidus (Bull).Fr. P. Karst, Icariside I, Safflower yellow, Ganoderma lucidum, and Ginsenoside Rk3, and other Chinese native medicinal compound prescriptions to boost their efficacy of anti-tumor immunotherapy through the regulation of microbiota and microbiota metabolites. However, current research mainly focuses on intestinal, liver, and lung cancer. In the future, natural products could be a viable option for treating malignant tumors, such as pancreatic, esophageal, and gastric malignancies, via sensitizing immunotherapy. Besides, the application characteristics of different types, sources and efficacy of natural products in different immune resistance scenarios also need to be further clarified through the development of future immunotherapy-related studies.

Gut microbial metabolites in lung cancer development and immunotherapy: Novel insights into gut-lung axis

Metabolic derivatives of numerous microorganisms inhabiting the human gut can participate in regulating physiological activities and immune status of the lungs through the gut-lung axis. The current well-established microbial metabolites include short-chain fatty acids (SCFAs), tryptophan and its derivatives, polyamines (PAs), secondary bile acids (SBAs), etc. As the study continues to deepen, the critical function of microbial metabolites in the occurrence and treatment of lung cancer has gradually been revealed. Microbial derivates can enter the circulation system to modulate the immune microenvironment of lung cancer. Mechanistically, oncometabolites damage host DNA and promote the occurrence of lung cancer, while tumor-suppresive metabolites directly affect the immune system to combat the malignant properties of cancer cells and even show considerable application potential in improving the efficacy of lung cancer immunotherapy. Considering the crosstalk along the gut-lung axis, in-depth exploration of microbial metabolites in patients' feces or serum will provide novel guidance for lung cancer diagnosis and treatment selection strategies. In addition, targeted therapeutics on microbial metabolites are expected to overcome the bottleneck of lung cancer immunotherapy and alleviate adverse reactions, including fecal microbiota transplantation, microecological preparations, metabolite synthesis and drugs targeting metabolic pathways. In summary, this review provides novel insights and explanations on the intricate interplay between gut microbial metabolites and lung cancer development, and immunotherapy through the lens of the gut-lung axis, which further confirms the possible translational potential of the microbiome metabolome in lung cancer treatment.

Molecular characterization and clinical relevance of metabolic signature subtypes in gastric cancer

Metabolic reprogramming dictates tumor molecular attributes and therapeutic potentials. However, the comprehensive metabolic characteristics in gastric cancer (GC) remain obscure. Here, metabolic signature-based clustering analysis identifies three subtypes with distinct molecular and clinical features: MSC1 showed better prognosis and upregulation of the tricarboxylic acid (TCA) cycle and lipid metabolism, combined with frequent TP53 and RHOA mutation; MSC2 had moderate prognosis and elevated nucleotide and amino acid metabolism, enriched by intestinal histology and mismatch repair deficient (dMMR); and MSC3 exhibited poor prognosis and enhanced glycan and energy metabolism, accompanied by diffuse histology and frequent CDH1 mutation. The Shandong Provincial Hospital (SDPH) in-house dataset with matched transcriptomic, metabolomic, and spatial-metabolomic analysis also validated these findings. Further, we constructed the metabolic subtype-related prognosis gene (MSPG) scoring model to quantify the activity of individual tumors and found a positive correlation with cuproptosis signaling. In conclusion, comprehensive recognition of the metabolite signature can enhance the understanding of diversity and heterogeneity in GC.

Predictive capacity of immune-related adverse events and cytokine profiling in neoadjuvant immune checkpoint inhibitor trials for head and neck squamous cell carcinoma

OBJECTIVES

Certain low-level immune-related adverse events (irAEs) have been associated with survival benefits in patients with various solid tumors on immune checkpoint inhibitors (ICIs). We aimed to investigate the association between irAEs and response to neoadjuvant ICIs in patients with head and neck squamous cell carcinoma (HNSCC) and to identify differences in circulating cytokine levels based on irAE status.

METHODS

This was a retrospective cohort study including three neoadjuvant clinical trials from July 2017 to January 2022: NCT03238365 (nivolumab ± tadalafil), NCT03854032 (nivolumab ± BMS986205), NCT03618654 (durvalumab ± metformin). The presence and type of irAEs, pathologic treatment response, and survival were compared. Canonical linear discriminant analysis (LDA) was performed to identify combinations of circulating cytokines predictive of irAEs using plasma sample multiplex assay.

RESULTS

Of 113 participants meeting inclusion criteria, 32 (28.3%) developed irAEs during treatment or follow-up. Positive p16 status was associated with irAEs (odds ratio [OR] 2.489; 95% CI 1.069-6.119; p = 0.043). irAEs were associated with pathologic treatment response (OR 3.73; 95% CI 1.34-10.35; p = 0.011) and with higher OS in the combined cohort (HR 0.319; 95% CI 0.113-0.906; p = 0.032). Patients with irAEs within the nivolumab cohort had significant elevations of select cytokines pre-treatment. Canonical LDA identified key drivers of irAEs among all trials, which were highly predictive of future irAE status.

CONCLUSIONS

irAEs are associated with response to neoadjuvant ICI therapy in HNSCC and can serve as clinical indicators for improved clinical outcomes. irAEs can be predicted by concentrations of several circulating cytokines prior to treatment.

Impact of high-salt diet in health and diseases and its role in pursuit of cancer immunotherapy by modulating gut microbiome

Cancer chemotherapy remains an area of concern, as many of the therapies are uncomfortable involving side effects and unpleasant experiences. These factors could further reduce patient's quality of life, and even endanger their life. Many therapeutic strategies have been tried to reduce the unpleasant side effects and increase the treatment effectiveness; however, none have shown to have promising effects. One of the main hindrances to cancer therapy is the escape strategies by tumor cells to the immune attack. Promoting inflammation in the tumor microenvironment is the cornerstone and key therapeutic target in cancer chemotherapy. High-salt diet (HSD) intake, though it has deleterious effects on human health by promoting chronic inflammation, is found to be advantageous in the tumor microenvironment. Studies identified HSD favors an increased abundance of Bifidobacterium species in the tumor environment due to gut barrier alteration, which, in turn, promotes inflammation and favors improved response to cancer chemotherapy. A review of the literature was carried out to find out the effects of an HSD on health and diseases, with special mention of its effect on cancer chemotherapy. Studies emphasized HSD would block the myeloid-derived suppressor cells which will enhance the tumor immunity. Exploration of the precise mechanism of simple HSD regime/ingestion of specific bacterial species as probiotics will be effective and essential to formulate the game-changing cancer chemotherapy. With the modern era of healthcare moving toward precision medicine where the physician can choose the treatment option suitable for the individual, HSD regime/ingestion of specific bacterial species can be considered.

Modulating gut microbiome in cancer immunotherapy: Harnessing microbes to enhance treatment efficacy

Immunotherapy has emerged as a robust approach against cancer, yet its efficacy has varied among individuals, accompanied by the occurrence of immune-related adverse events. As a result, the efficacy of immunotherapy is far from satisfactory, and enormous efforts have been invested to develop strategies to improve patient outcomes. The gut microbiome is now well acknowledged for its critical role in immunotherapy, with better understanding on host-microbes interaction in the context of cancer treatment. Also, an increasing number of trials have been conducted to evaluate the potential and feasibility of microbiome-targeting approaches to enhance efficacy of cancer treatment in patients. Here, the role of the gut microbiome and metabolites (e.g., short-chain fatty acids, tryptophan metabolites) in immunotherapy and the underlying mechanisms are explored. The application of microbiome-targeting approaches that aim to improve immunotherapy efficacy (e.g., fecal microbiota transplantation, probiotics, dietary intervention) is also elaborated, with further discussion on current challenges and suggestions for future research.

Soluble immune checkpoint factors reflect exhaustion of antitumor immunity and response to PD-1 blockade

BACKGROUNDPrecise stratification of patients with non-small cell lung cancer (NSCLC) is needed for appropriate application of PD-1/PD-L1 blockade therapy.METHODSWe measured soluble forms of the immune-checkpoint molecules PD-L1, PD-1, and CTLA-4 in plasma of patients with advanced NSCLC before PD-1/PD-L1 blockade. A prospective biomarker-finding trial (cohort A) included 50 previously treated patients who received nivolumab. A retrospective observational study was performed for patients treated with any PD-1/PD-L1 blockade therapy (cohorts B and C), cytotoxic chemotherapy (cohort D), or targeted therapy (cohort E). Plasma samples from all patients were assayed for soluble immune-checkpoint molecules with a highly sensitive chemiluminescence-based assay.RESULTSNonresponsiveness to PD-1/PD-L1 blockade therapy was associated with higher concentrations of these soluble immune factors among patients with immune-reactive (hot) tumors. Such an association was not apparent for patients treated with cytotoxic chemotherapy or targeted therapy. Integrative analysis of tumor size, PD-L1 expression in tumor tissue (tPD-L1), and gene expression in tumor tissue and peripheral CD8+ T cells revealed that high concentrations of the 3 soluble immune factors were associated with hyper or terminal exhaustion of antitumor immunity. The combination of soluble PD-L1 (sPD-L1) and sCTLA-4 efficiently discriminated responsiveness to PD-1/PD-L1 blockade among patients with immune-reactive tumors.CONCLUSIONCombinations of soluble immune factors might be able to identify patients unlikely to respond to PD-1/PD-L1 blockade as a result of terminal exhaustion of antitumor immunity. Our data suggest that such a combination better predicts, along with tPD-L1, for the response of patients with NSCLC.TRIAL REGISTRATIONUMIN000019674.FUNDINGThis study was funded by Ono Pharmaceutical Co. Ltd. and Sysmex Corporation.

The effect of redox bacteria on the programmed cell death-1 cancer immunotherapy

Background and purpose

Extracellular electron transferring (EET) or redox bacteria employ a shuttle of flavins to transfer electrons to the oxygen in the intestinal mucosa. Although clinical studies suggest that the gut microbiome modulates the efficiency of immune checkpoint therapy in patients with cancer, the modulation mechanisms have not been well-characterized yet.

Experimental approach

In the present study, the oral gavage administration of Shewanella oneidensis MR-1 as a prototypic EET bacteria was assayed in a mouse model of lung cancer to determine the effect of EET bacterium on the efficacy of the programmed cell death protein 1 (PD1)-immune checkpoint therapy.

Findings/Results

It was indicated that in vitro EET from S. oneidensis was mediated by riboflavins that were supplied through extrinsic sources. Co-administration of S. oneidensis and anti-PD 1 antibodies represent better tumor remission compared to the single-administration of each one; however, no statistically significant change was observed in the tumor volume.

Conclusion and implications

More detailed studies are needed to definitively confirm the therapeutic effects of electrogenic bacteria in patients with cancer. Given the findings of the present study, increasing flavin compounds or EET bacteria in the intestine may provide novel strategies for modulating cancer immunotherapy.

Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy

Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits a minority of patients, underscoring the importance of discovering reliable biomarkers that can be used to screen for potential beneficiaries and ultimately reduce the risk of overtreatment. Our comprehensive review focuses on the latest advancements in predictive biomarkers for ICI therapy, particularly emphasizing those that enhance the efficacy of programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors immunotherapies. We explore biomarkers derived from various sources, including tumor cells, the tumor immune microenvironment (TIME), body fluids, gut microbes, and metabolites. Among them, tumor cells-derived biomarkers include tumor mutational burden (TMB) biomarker, tumor neoantigen burden (TNB) biomarker, microsatellite instability (MSI) biomarker, PD-L1 expression biomarker, mutated gene biomarkers in pathways, and epigenetic biomarkers. TIME-derived biomarkers include immune landscape of TIME biomarkers, inhibitory checkpoints biomarkers, and immune repertoire biomarkers. We also discuss various techniques used to detect and assess these biomarkers, detailing their respective datasets, strengths, weaknesses, and evaluative metrics. Furthermore, we present a comprehensive review of computer models for predicting the response to ICI therapy. The computer models include knowledge-based mechanistic models and data-based machine learning (ML) models. Among the knowledge-based mechanistic models are pharmacokinetic/pharmacodynamic (PK/PD) models, partial differential equation (PDE) models, signal networks-based models, quantitative systems pharmacology (QSP) models, and agent-based models (ABMs). ML models include linear regression models, logistic regression models, support vector machine (SVM)/random forest/extra trees/k-nearest neighbors (KNN) models, artificial neural network (ANN) and deep learning models. Additionally, there are hybrid models of systems biology and ML. We summarized the details of these models, outlining the datasets they utilize, their evaluation methods/metrics, and their respective strengths and limitations. By summarizing the major advances in the research on predictive biomarkers and computer models for the therapeutic effect and clinical utility of tumor ICI, we aim to assist researchers in choosing appropriate biomarkers or computer models for research exploration and help clinicians conduct precision medicine by selecting the best biomarkers.

Bendamustine lymphodepletion before axicabtagene ciloleucel is safe and associates with reduced inflammatory cytokines

ABSTRACT

Lymphodepletion (LD) is an integral component of chimeric antigen receptor T-cell (CART) immunotherapies. In this study, we compared the safety and efficacy of bendamustine (Benda) to standard fludarabine/cyclophosphamide (Flu/Cy) LD before CD19-directed, CD28-costimulated CART axicabtagene ciloleucel (axi-cel) for patients with large B-cell lymphoma (LBCL) and follicular lymphoma (FL). We analyzed 59 patients diagnosed with LBCL (n = 48) and FL (n = 11) consecutively treated with axi-cel at the University of Pennsylvania. We also analyzed serum samples for cytokine levels and metabolomic changes before and after LD. Flu/Cy and Benda demonstrated similar efficacy, with complete remission rates of 51.4% and 50.0% (P = .981), respectively, and similar progression-free and overall survivals. Any-grade cytokine-release syndrome occurred in 91.9% of patients receiving Flu/Cy vs 72.7% of patients receiving Benda (P = .048); any-grade neurotoxicity after Flu/Cy occurred in 45.9% of patients and after Benda in 18.2% of patients (P = .031). In addition, Flu/Cy was associated with a higher incidence of grade ≥3 neutropenia (100% vs 54.5%; P < .001), infections (78.4% vs 27.3%; P < .001), and neutropenic fever (78.4% vs 13.6%; P < .001). These results were confirmed both in patients with LBCL and those with FL. Mechanistically, patients with Flu/Cy had a greater increase in inflammatory cytokines associated with neurotoxicity and reduced levels of metabolites critical for redox balance and biosynthesis. This study suggests that Benda LD may be a safe alternative to Flu/Cy for CD28-based CART CD19-directed immunotherapy with similar efficacy and reduced toxicities. Benda is associated with reduced levels of inflammatory cytokines and increased anabolic metabolites.

3D plasmonic hexaplex paper sensor for label-free human saliva sensing and machine learning-assisted early-stage lung cancer screening

A label-free detection method for noninvasive biofluids enables rapid on-site disease screening and early-stage cancer diagnosis by analyzing metabolic alterations. Herein, we develop three-dimensional plasmonic hexaplex nanostructures coated on a paper substrate (3D-PHP). This flexible and highly absorptive 3D-PHP sensor is integrated with commercial saliva collection tube to create an efficient on-site sensing platform for lung cancer screening via surface-enhanced Raman scattering (SERS) measurement of human saliva. The multispike hexaplex-shaped gold nanostructure enhances contact with saliva viscosity, enabling effective sampling and SERS enhancement. Through testing patient salivary samples, the 3D-PHP sensor demonstrates successful lung cancer detection and diagnosis. A logistic regression-based machine learning model successfully classifies benign and malignant patients, exhibiting high clinical sensitivity and specificity. Additionally, important Raman peak positions related to different lung cancer stages are investigated, suggesting insights for early-stage cancer diagnosis. Integrating 3D-PHP senor with the conventional saliva collection tube platform is expected to offer promising practicality for rapid on-site disease screening and diagnosis, and significant advancements in cancer detection and patient care.

Amino acid catabolite markers for early prognostication of pneumonia in patients with COVID-19

Effective early-stage markers for predicting which patients are at risk of developing SARS-CoV-2 infection have not been fully investigated. Here, we performed comprehensive serum metabolome analysis of a total of 83 patients from two cohorts to determine that the acceleration of amino acid catabolism within 5 days from disease onset correlated with future disease severity. Increased levels of de-aminated amino acid catabolites involved in the de novo nucleotide synthesis pathway were identified as early prognostic markers that correlated with the initial viral load. We further employed mice models of SARS-CoV2-MA10 and influenza infection to demonstrate that such de-amination of amino acids and de novo synthesis of nucleotides were associated with the abnormal proliferation of airway and vascular tissue cells in the lungs during the early stages of infection. Consequently, it can be concluded that lung parenchymal tissue remodeling in the early stages of respiratory viral infections induces systemic metabolic remodeling and that the associated key amino acid catabolites are valid predictors for excessive inflammatory response in later disease stages.

Impact of Different Treatment Regimens and Timeframes in the Plasmatic Metabolic Profiling of Patients with Lung Adenocarcinoma

In recent years, the treatment of advanced non-small cell lung cancer (NSCLC) has suffered a variety of alterations. Chemotherapy (CTX), immunotherapy (IT) and tyrosine kinase inhibitors (TKI) have shown remarkable results. However, not all patients with NSCLC respond to these drug treatments or receive durable benefits. In this framework, metabolomics has been applied to improve the diagnosis, treatment, and prognosis of lung cancer and particularly lung adenocarcinoma (AdC). In our study, metabolomics was used to analyze plasma samples from 18 patients with AdC treated with CTX or IT via 1H-NMR spectroscopy. Relevant clinical information was gathered, and several biochemical parameters were also evaluated throughout the treatments. During the follow-up of patients undergoing CTX or IT, imaging control is recommended in order to assess the effectiveness of the therapy. This evaluation is usually performed every three treatments. Based on this procedure, all the samples were collected before the beginning of the treatment and after three and six treatments. The identified and quantified metabolites in the analyzed plasma samples were the following: isoleucine, valine, alanine, acetate, lactate, glucose, tyrosine, and formate. Multivariate/univariate statistical analyses were performed. Our data are in accordance with previous published results, suggesting that the plasma glucose levels of patients under CTX become higher throughout the course of treatment, which we hypothesize could be related to the tumor response to the therapy. It was also found that alanine levels become lower during treatment with CTX regimens, a fact that could be associated with frailty. NMR spectra of long responders' profiles also showed similar results. Based on the results of the study, metabolomics can represent a potential option for future studies, in order to facilitate patient selection and the monitoring of therapy efficacy in treated patients with AdC. Further studies are needed to improve the prospective identification of predictive markers, particularly glucose and alanine levels, as well as confer guidance to NSCLC treatment and patient stratification, thus avoiding ineffective therapeutic strategies.

Methylglyoxal from gut microbes boosts radiosensitivity and radioimmunotherapy in rectal cancer by triggering endoplasmic reticulum stress and cGAS-STING activation

BACKGROUND

Preoperative radiation therapy (preRT) is a fundamental aspect of neoadjuvant treatment for rectal cancer (RC), but the response to this treatment remains unsatisfactory. The combination of radiation therapy (RT) and immunotherapy (iRT) presents a promising approach to cancer treatment, though the underlying mechanisms are not yet fully understood. The gut microbiota may influence the response to RT and immunotherapy. Therefore, we aimed to identify the metabolism of gut microbiota to reverse radioresistance and enhance the efficacy of iRT.

METHODS

Fecal and serum samples were prospectively collected from patients with locally advanced rectal cancer (LARC) who had undergone pre-RT treatment. Candidate gut microbiome-derived metabolites linked with radiosensitization were screened using 16s rRNA gene sequencing and ultrahigh-performance liquid chromatography-mass coupled with mass spectrometry. In vitro and in vivo studies were conducted to assess the radiosensitizing effects of the metabolites including the syngeneic CT26 tumor model and HCT116 xenograft tumor model, transcriptomics and immunofluorescence. The CT26 abscopal effect modeling was employed to evaluate the combined effects of metabolites on iRT.

RESULTS

We initially discovered the gut microbiota-associated metabolite, methylglyoxal (MG), which accurately predicts the response to preRT (Area Under Curve (AUC) value of 0.856) among patients with LARC. Subsequently, we observed that MG amplifies the RT response in RC by stimulating intracellular reactive oxygen species (ROS) and reducing hypoxia in the tumor in vitro and in vivo. Additionally, our study demonstrated that MG amplifies the RT-induced activation of the cyclic guanosine monophosphate AMP synthase-stimulator of interferon genes pathway by elevating DNA double-strand breaks. Moreover, it facilitates immunogenic cell death generated by ROS-mediated endoplasmic reticulum stress, consequently leading to an increase in CD8+ T and natural killer cells infiltrated in the tumor immune microenvironment. Lastly, we discovered that the combination of anti-programmed cell death protein 1 (anti-PD1) therapy produced long-lasting complete responses in all irradiated tumor sites and half of the non-irradiated ones.

CONCLUSIONS

Our research indicates that MG shows promise as a radiosensitizer and immunomodulator for RC. Furthermore, we propose that combining MG with iRT has great potential for clinical practice.

Insights from a 30-year journey: function, regulation and therapeutic modulation of PD1

PD1 was originally discovered in 1992 as a molecule associated with activation-induced cell death in T cells. Over the past 30 years, it was found that PD1 has a critical role in avoiding overactivation-induced cell death and autoimmunity, whereas its inhibition unleashes anticancer immunity. Here, we outline the journey from the discovery of PD1 to its role as a breakthrough target in cancer immunotherapy. We describe its regulation and function and examine how a mechanistic understanding of PD1 signalling suggests a central function in setting the T cell activation threshold, thereby controlling T cell proliferation, differentiation, exhaustion and metabolic status. This threshold theory, in combination with new insights into T cell metabolism and a better understanding of immune cell modulation by the microbiota, can provide guidance for the development of efficient combination therapies. Moreover, we discuss the mechanisms underlying immune-related adverse events after PD1-targeted therapy and their possible treatment.

Ultrahigh-performance liquid chromatography-high-resolution mass spectrometry-based plasma metabolomics study of thymoma and thymic hyperplasia

RATIONALE

Thymoma is a rare malignant tumor but it is the most common primary tumor of the anterior mediastinum. The current imaging methods for thymoma screening suffer from false positive rate problems, and thymoma pathogenesis remains elusive. Study of thymoma metabolic characteristics could provide clues for improving the diagnosis and understanding the pathogenesis of thymoma.

METHODS

Metabolic profiling of plasma from thymoma and thymic hyperplasia patients was performed using ultrahigh-performance liquid chromatography combined with high-resolution mass spectrometry in both positive and negative ionization modes. After pre- and post-processing, the dataset was divided into three age groups and statistical analysis was performed to select differential metabolites of thymoma. For feature identification, experimental tandem mass spectra were matched to those of databases and available chemical standards, and also manually annotated with plausible chemical structures to ensure high identification confidence.

RESULTS

A total of 47 differential metabolites were identified in thymoma. Significantly higher levels of histidine, sphinganine 1-phosphate, lactic acid dimer, phenylacetylglutamine, LPC (18:3) and LPC (16:1), and significantly lower levels of phenylalanine, indole-3-propionic acid (IPA), hippuric acid and mesobilirubinogen were associated with thymoma. Tryptophan level in thymoma-associated myasthenia gravis (TAMG) was significantly lower than that of the MG(-) group. IPA and hippuric acid abundances exhibited increasing trends from indolent to aggressive thymoma.

CONCLUSIONS

Our study revealed aberrant aromatic amino acid metabolism and fatty acid oxidation might be associated with thymoma. The identified unique metabolic characteristics of thymoma may provide valuable information for study of the molecular mechanism of thymoma pathogenesis, and improvement of diagnosis and discovery of new therapeutic strategies for thymoma.

Dietary Manipulation of Amino Acids for Cancer Therapy

Cancer cells cannot proliferate and survive unless they obtain sufficient levels of the 20 proteinogenic amino acids (AAs). Unlike normal cells, cancer cells have genetic and metabolic alterations that may limit their capacity to obtain adequate levels of the 20 AAs in challenging metabolic environments. However, since normal diets provide all AAs at relatively constant levels and ratios, these potentially lethal genetic and metabolic defects are eventually harmless to cancer cells. If we temporarily replace the normal diet of cancer patients with artificial diets in which the levels of specific AAs are manipulated, cancer cells may be unable to proliferate and survive. This article reviews in vivo studies that have evaluated the antitumor activity of diets restricted in or supplemented with the 20 proteinogenic AAs, individually and in combination. It also reviews our recent studies that show that manipulating the levels of several AAs simultaneously can lead to marked survival improvements in mice with metastatic cancers.

Microbial metabolites and immunotherapy: Basic rationale and clinical indications

Our microbiota has a critical role in shaping host immunity. Microbes that reside in the gut harbor a large metabolic arsenal to aid in physiological functions of the host. Microbial metabolites, which are products of microbial metabolism, such as short chain fatty acids (SCFA), purine metabolites, cyclic dinucleotides, tryptophan derivatives, and secondary bile acids, can tailor the host immune cell landscape in homeostasis and during cancer immunotherapy. The critical role of the microbiome in aiding immune checkpoint blockade therapies has become clearer over the past few years, with the most recent studies providing more detailed mechanistic insight on how microbes and their metabolites control the outcome of immunotherapy. This review summarizes recent studies on how microbial metabolites orchestrate immune responses during cancer immunotherapies.

Long-chain polyunsaturated lipids associated with responsiveness to anti-PD-1 therapy are colocalized with immune infiltrates in the tumor microenvironment

The programmed cell death protein-1 (PD-1) is highly expressed on the surface of antigen-specific exhausted T cells and, upon interaction with its ligand PD-L1, can result in inhibition of the immune response. Anti-PD-1 treatment has been shown to extend survival and result in durable responses in several cancers, yet only a subset of patients benefit from this therapy. Despite the implication of metabolic alteration following cancer immunotherapy, mechanistic associations between antitumor responses and metabolic changes remain unclear. Here, we used desorption electrospray ionization mass spectrometry imaging to examine the lipid profiles of tumor tissue from three syngeneic murine models with varying treatment sensitivity at the baseline and at three time points post-anti-PD-1 therapy. These imaging experiments revealed specific alterations in the lipid profiles associated with the degree of response to treatment and allowed us to identify a significant increase of long-chain polyunsaturated lipids within responsive tumors following anti-PD-1 therapy. Immunofluorescence imaging of tumor tissues also demonstrated that the altered lipid profile associated with treatment response is localized to dense regions of tumor immune infiltrates. Overall, these results indicate that effective anti-PD-1 therapy modulates lipid metabolism in tumor immune infiltrates, and we thereby propose that further investigation of the related immune-metabolic pathways may be useful for better understanding success and failure of anti-PD-1 therapy.

NMR-Based Metabolomics to Evaluate Individual Response to Treatments

The aim of this chapter is to highlight the various aspects of metabolomics in relation to health and diseases, starting from the definition of metabolic space and of how individuals tend to maintain their own position in this space. Physio-pathological stimuli may cause individuals to lose their position and then regain it, or move irreversibly to other positions. By way of examples, mostly selected from our own work using ¹H NMR on biological fluids, we describe the effects on the individual metabolomic fingerprint of mild external interventions, such as diet or probiotic administration. Then we move to pathologies (such as celiac disease, various types of cancer, viral infections, and other diseases), each characterized by a well-defined metabolomic fingerprint. We describe the effects of drugs on the disease fingerprint and on its reversal to a healthy metabolomic status. Drug toxicity can be also monitored by metabolomics. We also show how the individual metabolomic fingerprint at the onset of a disease may discriminate responders from non-responders to a given drug, or how it may be prognostic of e.g., cancer recurrence after many years. In parallel with fingerprinting, profiling (i.e., the identification and quantification of many metabolites and, in the case of selected biofluids, of the lipoprotein components that contribute to the ¹H NMR spectral features) can provide hints on the metabolic pathways that are altered by a disease and assess their restoration after treatment.

Combination bezafibrate and nivolumab treatment of patients with advanced non-small cell lung cancer

Despite the success of cancer immunotherapies such as programmed cell death-1 (PD-1) and PD-1 ligand 1 (PD-L1) inhibitors, patients often develop resistance. New combination therapies with PD-1/PD-L1 inhibitors are needed to overcome this issue. Bezafibrate, a ligand of peroxisome proliferator-activated receptor-γ coactivator 1α/peroxisome proliferator-activated receptor complexes, has shown a synergistic antitumor effect with PD-1 blockade in mice that is mediated by activation of mitochondria in T cells. We have therefore now performed a phase 1 trial (UMIN000017854) of bezafibrate with nivolumab in previously treated patients with advanced non-small cell lung cancer. The primary end point was the percentage of patients who experience dose-limiting toxicity, and this combination regimen was found to be well tolerated. Preplanned comprehensive analysis of plasma metabolites and gene expression in peripheral cytotoxic T cells indicated that bezafibrate promoted T cell function through up-regulation of mitochondrial metabolism including fatty acid oxidation and may thereby have prolonged the duration of response. This combination strategy targeting T cell metabolism thus has the potential to maintain antitumor activity of immune checkpoint inhibitors and warrants further validation.

Rechallenge of immune checkpoint inhibitors in a case with adverse events inducing myasthenia gravis

The mechanism(s) of immune checkpoint inhibitor (ICI)-induced myasthenia gravis (MG), an immune-related adverse event (irAE) that is fatal and limits subsequent ICI use, remain unexplored. Here, through comparative genomic analysis, we identified a pathogenic p.S467C germline variant in SLC22A5 in a thymoma case with ICI-induced MG, which was found to be associated with fatty acid oxidation through its regulation on L-carnitine levels. Remarkably, ICI rechallenge with L-carnitine pretreatment led to durable response without MG-related symptoms. Thus, we provide the first clinical evidence of genetic test-directed irAE management, which integrates individualized ICI treatment into the evolving paradigm of cancer management.

Cross-disease communication between cancer and heart failure provides a rational approach to prevention and treatment of both diseases

Accumulating clinical data have demonstrated a clear positive association between cancer and cardiac disorders, particularly chronic heart failure (CHF). These two diseases can be mutual drivers of each other, and hence frequently co-occur in patients. The immune system is the core mechanism that eliminates transformed cells from our bodies. However, immune cells often play distinct or even conflicting roles in cancer and CHF. Moreover, CHF alters the properties of immune cells, particularly those of regulatory T cells. Our previous study showed that the oxidative phosphorylation capacity of peripheral blood mononuclear cells is impaired in CHF, leading to the increased production of reactive oxygen species. Therefore, the co-occurrence of cancer and CHF becomes a serious problem, affecting the treatment of both diseases, and consequently negatively affecting patient survival rates. To date, few methods have been identified that effectively treat both diseases at the same time. Mitochondria activity may change in immune cells during their activation and exhaustion, and in CHF. Mitochondria activity is also largely affected in myocardia in CHF. We here focus on the mitochondrial abnormalities of immune cells in cancer and CHF, and discuss possible ways to treat cancer and CHF at the same time by targeting mitochondrial abnormalities. Many cancer cells are inevitably produced daily in our bodies, mostly owing to enzymatic nucleotide errors of DNA replication and repair. Therefore, the possibility of ways to prevent cancer by preventing the onset of heart failure will also be discussed.

Tumor immune microenvironment and systemic response in breast cancer

Cancer immunotherapies, particularly immune checkpoint inhibitors (ICIs) that target programmed cell death protein 1 (PD-1) or programmed cell death ligand 1 (PD-L1), have revolutionized cancer treatment. ICIs are effective against breast cancer, and their efficacy against triple-negative breast cancer (TNBC) has been reported. The efficacy of immunotherapy is related to the tumor immune microenvironment. In particular, tumor-infiltrating immune cells, hypoxia, and mitochondria in the tumor microenvironment are closely associated with anti-tumor immunity. Moreover, breast cancer (BC) tumors exhibit high heterogeneity; however, identification of effective biomarkers, via tissue biopsies, is limited owing to the invasiveness of the procedure. Therefore, it is crucial to develop non-invasive protocols (e.g., blood and fecal sampling) to identify components of the tumor immune microenvironment that reflect the systemic immune response, for the characterization of immunotherapy biomarkers. Herein, we review the relationship among systemic immune responses-via liquid biopsy analysis-the microbiome, and the tumor immune microenvironment in BC, while characterizing prospective biomarkers. Relationship between TIME and systemic response in breast cancer.

Immune and inflammation: related factor alterations as biomarkers for predicting prognosis and responsiveness to PD-1 monoclonal antibodies in cervical cancer

PURPOSE

We aimed to elucidate the potential mechanisms of effective responsiveness to PD-1 monoclonal antibody and evaluate more reliable biomarkers to improve the ability to predict the populations of cervical cancer (CC) suitable for immunotherapy.

METHODS

Peripheral blood samples of CC patients undergoing anti-PD-1 therapy were collected before and after treatment. Differentially expressed genes (DEGs) were analyzed between partial response (PR) and progressive disease (PD) patients. A novel prognostic inflammation and immune-related response gene (IRRG) model was constructed and its prognostic role, correlation with tumor immunity and tumor mutation were evaluated.

RESULTS

DEGs in PR patient after treatment could predict the response to PD-1 monoclonal antibodies. Among PR-specific pathways, tumor immunity, leukocyte migration, and cytokine activities were prominently enriched. Additionally, an IRRG signature comprising CTLA4, AZU1, C5, LAT, CXCL2, GDF7, MPL, PPARG and CELA1 was established and validated to predict the prognosis of CC with great accuracy and specificity. This signature could reflect the tumor microenvironment (TME) and tumor mutational burden (TMB). We also found stimulated adaptive immunity and downregulated inflammation at baseline in patients with sensitive responses to PD-1 monoclonal antibody.

CONCLUSION

We developed an IRRG signature and verified that it was an independent prognostic factor for predicting survival and could reflect a sensitive response to PD-1 monoclonal antibody, which plays a nonnegligible role in the TME of CC. Further investigations are warranted to confirm that patients with stimulated adaptive immunity and downregulated inflammation at baseline could achieve a better survival benefit from PD-1 monoclonal antibody.

Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer

Simple Summary

Women diagnosed with ovarian cancer have 5-year survival rates below 45%. Prediction of patient’s outcome and the onset of drug resistance are still major challenges. The patient’s drug response is influenced by the environment that surrounds the tumor cells. We previously showed that patient-derived tumor tissue can be kept in the lab, alive and retaining aspects of that environment. In this study, we exposed tumor tissue derived from ovarian cancer patients to the chemotherapy patients receive and identified metabolites released by the tumor tissue after treatment (metabolic footprint). Using machine learning, we uncovered metabolic signatures that discriminate tumor tissues with higher vs. lower drug sensitivity. We propose potential biomarkers involved in the production of specific building blocks of cells and energy generation processes. Overall, we established a platform to explore metabolic features of the complex environment of each patient’s tumor that can underpin the discovery of biomarkers of drug response.

Abstract

Predicting patient response to treatment and the onset of chemoresistance are still major challenges in oncology. Chemoresistance is deeply influenced by the complex cellular interactions occurring within the tumor microenvironment (TME), including metabolic crosstalk. We have previously shown that ex vivo tumor tissue cultures derived from ovarian carcinoma (OvC) resections retain the TME components for at least four weeks of culture and implemented assays for assessment of drug response. Here, we explored ex vivo patient-derived tumor tissue cultures to uncover metabolic signatures of chemosensitivity and/or resistance. Tissue cultures derived from nine OvC cases were challenged with carboplatin and paclitaxel, the standard-of-care chemotherapeutics, and the metabolic footprints were characterized by LC-MS. Partial least-squares discriminant analysis (PLS-DA) revealed metabolic signatures that discriminated high-responder from low-responder tissue cultures to ex vivo drug exposure. As a proof-of-concept, a set of potential metabolic biomarkers of drug response was identified based on the receiver operating characteristics (ROC) curve, comprising amino acids, fatty acids, pyrimidine, glutathione, and TCA cycle pathways. Overall, this work establishes an analytical and computational platform to explore metabolic features of the TME associated with response to treatment, which can leverage the discovery of biomarkers of drug response and resistance in OvC.

Effect of Gut Microbiota-Derived Metabolites on Immune Checkpoint Inhibitor Therapy: Enemy or Friend?

The human gut is inhabited by hundreds of billions of commensal microbiota that collectively produce thousands of small molecules and metabolites with local and systemic effects on the physiology of the host. Much evidence from preclinical to clinical studies has gradually confirmed that the gut microbiota can regulate anti-tumor immunity and affect the efficacy of cancer immune checkpoint inhibitors (ICIs) therapy. In particular, one of the main modes of gut microbiota regulating anti-tumor immunity is through metabolites, which are small molecules that can be transported in the body and act on local and systemic anti-tumor immune responses to promote ICIs immunotherapy efficacy. We discuss the functions of microbial metabolites in humans, focusing on the effects and mechanisms of microbial metabolites on immunotherapy, and analyze their potential applications as immune adjuvants and therapeutic targets to regulate immunity and enhance ICIs. In summary, this review provides the basis for the rational design of microbiota and microbial metabolite-based strategies of enhancing ICIs.

Inhibition of stearoyl-CoA desaturase 1 (SCD1) enhances the antitumor T cell response through regulating β-catenin signaling in cancer cells and ER stress in T cells and synergizes with anti-PD-1 antibody

Background

Understanding the mechanisms of non-T cell inflamed tumor microenvironment (TME) and their modulation are important to improve cancer immunotherapies such as immune checkpoint inhibitors. The involvement of various immunometabolisms has recently been indicated in the formation of immunosuppressive TME. In this study, we investigated the immunological roles of stearoyl-CoA desaturase 1 (SCD1), which is essential for fatty acid metabolism, in the cancer immune response.

Methods

We investigated the roles of SCD1 by inhibition with the chemical inhibitor or genetic manipulation in antitumor T cell responses and the therapeutic effect of anti-programmed cell death protein 1 (anti-PD-1) antibody using various mouse tumor models, and their cellular and molecular mechanisms. The roles of SCD1 in human cancers were also investigated by gene expression analyses of colon cancer tissues and by evaluating the related free fatty acids in sera obtained from patients with non-small cell lung cancer who were treated with anti-PD-1 antibody.

Results

Systemic administration of a SCD1 inhibitor in mouse tumor models enhanced production of CCL4 by cancer cells through reduction of Wnt/β-catenin signaling and by CD8⁺ effector T cells through reduction of endoplasmic reticulum stress. It in turn promoted recruitment of dendritic cells (DCs) into the tumors and enhanced the subsequent induction and tumor accumulation of antitumor CD8⁺ T cells. SCD1 inhibitor was also found to directly stimulate DCs and CD8⁺ T cells. Administration of SCD1 inhibitor or SCD1 knockout in mice synergized with an anti-PD-1 antibody for its antitumor effects in mouse tumor models. High SCD1 expression was observed in one of the non-T cell-inflamed subtypes in human colon cancer, and serum SCD1 related fatty acids were correlated with response rates and prognosis of patients with non-small lung cancer following anti-PD-1 antibody treatment.

Conclusions

SCD1 expressed in cancer cells and immune cells causes immunoresistant conditions, and its inhibition augments antitumor T cells and therapeutic effects of anti-PD-1 antibody. Therefore, SCD1 is an attractive target for the development of new diagnostic and therapeutic strategies to improve current cancer immunotherapies including immune checkpoint inhibitors.

'Know thyself' - host factors influencing cancer response to immune checkpoint inhibitors

Immune checkpoint inhibitors (ICIs) have revolutionised oncology and are now standard-of-care for the treatment of a wide variety of solid neoplasms. However, tumour responses remain unpredictable, experienced by only a minority of ICI recipients across malignancy types. Therefore, there is an urgent need for better predictive biomarkers to identify a priori the patients most likely to benefit from these therapies. Despite considerable efforts, only three such biomarkers are FDA-approved for clinical use, and all rely on the availability of tumour tissue for immunohistochemical staining or genomic assays. There is emerging evidence that host factors - for example, genetic, metabolic, and immune factors, as well as the composition of one's gut microbiota - influence the response of a patient's cancer to ICIs. Tantalisingly, some of these factors are modifiable, paving the way for co-therapies that may enhance the therapeutic index of these treatments. Herein, we review key host factors that are of potential biomarker value for response to ICI therapy, with a particular focus on the proposed mechanisms for these influences. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Immuno-reactive cancer organoid model to assess effects of the microbiome on cancer immunotherapy

Immune checkpoint blockade (ICB) therapy has demonstrated good efficacy in many cancer types. In cancers such as non-resectable advanced or metastatic triple-negative breast cancer (TNBC), it has recently been approved as a promising treatment. However, clinical data shows overall response rates (ORRs) from ~ 3-40% in breast cancer patients, depending on subtype, previous treatments, and mutation status. Composition of the host-microbiome has a significant role in cancer development and therapeutic responsiveness. Some bacterial families are conducive to oncogenesis and progression, while others aid innate and therapeutically induced anti-tumor immunity. Modeling microbiome effects on anti-tumor immunity in ex vivo systems is challenging, forcing the use of in vivo models, making it difficult to dissect direct effects on immune cells from combined effects on tumor and immune cells. We developed a novel immune-enhanced tumor organoid (iTO) system to study factors affecting ICB response. Using the 4T1 TNBC murine cell line and matched splenocytes, we demonstrated ICB-induced response. Further administration of bacterial-derived metabolites from species found in the immunomodulatory host-microbiome significantly increased ICB-induced apoptosis of tumor cells and altered immune cell receptor expression. These outcomes represent a method to isolate individual factors that alter ICB response and streamline the study of microbiome effects on ICB efficacy.

Immunometabolic Markers in a Small Patient Cohort Undergoing Immunotherapy

Although the discovery of immune checkpoints was hailed as a major breakthrough in cancer therapy, generating a sufficient response to immunotherapy is still limited. Thus, the objective of this exploratory, hypothesis-generating study was to identify potentially novel peripheral biomarkers and discuss the possible predictive relevance of combining scarcely investigated metabolic and hormonal markers with immune subsets. Sixteen markers that differed significantly between responders and non-responders were identified. In a further step, the correlation with progression-free survival (PFS) and false discovery correction (Benjamini and Hochberg) revealed potential predictive roles for the immune subset absolute lymphocyte count (rs = 0.51; p = 0.0224 *), absolute basophil count (rs = 0.43; p = 0.04 *), PD-1+ monocytes (rs = −0.49; p = 0.04 *), hemoglobin (rs = 0.44; p = 0.04 *), metabolic markers LDL (rs = 0.53; p = 0.0224 *), free androgen index (rs = 0.57; p = 0.0224 *) and CRP (rs = −0.46; p = 0.0352 *). The absolute lymphocyte count, LDL and free androgen index were the most significant individual markers, and combining the immune subsets with the metabolic markers into a biomarker ratio enhanced correlation with PFS (rs = −0.74; p ≤ 0.0001 ****). In summary, in addition to well-established markers, we identified PD-1+ monocytes and the free androgen index as potentially novel peripheral markers in the context of immunotherapy. Furthermore, the combination of immune subsets with metabolic and hormonal markers may have the potential to enhance the power of future predictive scores and should, therefore, be investigated further in larger trials.

Clinical significance of plasma-free amino acids and tryptophan metabolites in patients with non-small cell lung cancer receiving PD-1 inhibitor: a pilot cohort study for developing a prognostic multivariate model

Background

Amino acid metabolism is essential for tumor cell proliferation and regulation of immune cell function. However, the clinical significance of free amino acids (plasma-free amino acids (PFAAs)) and tryptophan-related metabolites in plasma has not been fully understood in patients with non-small cell lung cancer (NSCLC) who receive immune checkpoint inhibitors.

Methods

We conducted a single cohort observational study. Peripheral blood samples were collected from 53 patients with NSCLC before treatment with PD-1 (Programmed cell death-1) inhibitors. The plasma concentrations of 21 PFAAs, 14 metabolites, and neopterin were measured by liquid chromatography–mass spectrometry. Using Cox hazard analysis with these variables, a multivariate model was established to stratify patient overall survival (OS). Gene expression in peripheral blood mononuclear cells (PBMCs) was compared between the high-risk and low-risk patients by this multivariate model.

Results

On Cox proportional hazard analysis, higher concentrations of seven PFAAs (glycine, histidine, threonine, alanine, citrulline, arginine, and tryptophan) as well as lower concentrations of three metabolites (3h-kynurenine, anthranilic acid, and quinolinic acid) and neopterin in plasma were significantly correlated with better OS (p<0.05). In particular, the multivariate model, composed of a combination of serine, glycine, arginine, and quinolinic acid, could most efficiently stratify patient OS (concordance index=0.775, HR=3.23, 95% CI 2.04 to 5.26). From the transcriptome analysis in PBMCs, this multivariate model was significantly correlated with the gene signatures related to immune responses, such as CD8 T-cell activation/proliferation and proinflammatory immune responses, and 12 amino acid-related genes were differentially expressed between the high-risk and low-risk groups.

Conclusions

The multivariate model with PFAAs and metabolites in plasma might be useful for stratifying patients who will benefit from PD-1 inhibitors.

Effects of PD-1 Signaling on Immunometabolic Reprogramming

Programmed Death-1 (PD-1; CD279) is an inhibitory receptor induced in several activated immune cells and, after engagement with its ligands PD-L1 and PD-L2, serves as a key mediator of peripheral tolerance. However, PD-1 signaling also has detrimental effects on T cell function by posing breaks on antitumor and antiviral immunity. PD-1 blocking immunotherapy either alone or in combination with other therapeutic modalities has shown great promise in cancer treatment. However, it is unclear why only a small fraction of patients responds to this type of therapy. For this reason, efforts to better understand the mechanisms of PD-1 function have recently been intensified, with the goal to reveal new strategies to overcome current limitations. The signaling pathways that are inhibited by PD-1 impact key regulators of metabolism. Here, we provide an overview of the current knowledge about the effects of PD-1 on metabolic reprogramming of immune cells and their consequences on systemic metabolism.

A high OXPHOS CD8 T cell subset is predictive of immunotherapy resistance in melanoma patients

Immune checkpoint inhibitor (ICI) therapy continues to revolutionize melanoma treatment, but only a subset of patients respond. Major efforts are underway to develop minimally invasive predictive assays of ICI response. Using single-cell transcriptomics, we discovered a unique CD8 T cell blood/tumor-shared subpopulation in melanoma patients with high levels of oxidative phosphorylation (OXPHOS), the ectonucleotidases CD38 and CD39, and both exhaustion and cytotoxicity markers. We called this population with high levels of OXPHOS "CD8+ TOXPHOS cells." We validated that higher levels of OXPHOS in tumor- and peripheral blood-derived CD8+ TOXPHOS cells correlated with ICI resistance in melanoma patients. We then developed an ICI therapy response predictive model using a transcriptomic profile of CD8+ TOXPHOS cells. This model is capable of discerning responders from nonresponders using either tumor or peripheral blood CD8 T cells with high accuracy in multiple validation cohorts. In sum, CD8+ TOXPHOS cells represent a critical immune population to assess ICI response with the potential to be a new target to improve outcomes in melanoma patients.

Machine Learning for Prediction of Immunotherapy Efficacy in Non-Small Cell Lung Cancer from Simple Clinical and Biological Data

BACKGROUND

Immune checkpoint inhibitors (ICIs) are now a therapeutic standard in advanced non-small cell lung cancer (NSCLC), but strong predictive markers for ICIs efficacy are still lacking. We evaluated machine learning models built on simple clinical and biological data to individually predict response to ICIs.

METHODS

Patients with metastatic NSCLC who received ICI in second line or later were included. We collected clinical and hematological data and studied the association of this data with disease control rate (DCR), progression free survival (PFS) and overall survival (OS). Multiple machine learning (ML) algorithms were assessed for their ability to predict response.

RESULTS

Overall, 298 patients were enrolled. The overall response rate and DCR were 15.3% and 53%, respectively. Median PFS and OS were 3.3 and 11.4 months, respectively. In multivariable analysis, DCR was significantly associated with performance status (PS) and hemoglobin level (OR 0.58, p < 0.0001; OR 1.8, p < 0.001). These variables were also associated with PFS and OS and ranked top in random forest-based feature importance. Neutrophil-to-lymphocyte ratio was also associated with DCR, PFS and OS. The best ML algorithm was a random forest. It could predict DCR with satisfactory efficacy based on these three variables. Ten-fold cross-validated performances were: accuracy 0.68 ± 0.04, sensitivity 0.58 ± 0.08; specificity 0.78 ± 0.06; positive predictive value 0.70 ± 0.08; negative predictive value 0.68 ± 0.06; AUC 0.74 ± 0.03.

CONCLUSION

Combination of simple clinical and biological data could accurately predict disease control rate at the individual level.

Development of computational models using omics data for the identification of effective cancer metabolic biomarkers

Identification of novel biomarkers has been an active area of study for the effective diagnosis, prognosis and treatment of cancers. Among various types of cancer biomarkers, metabolic biomarkers, including enzymes, metabolites and metabolic genes, deserve attention as they can serve as a reliable source for diagnosis, prognosis and treatment of cancers. In particular, efforts to identify novel biomarkers have been greatly facilitated by a rapid increase in the volume of multiple omics data generated for a range of cancer cells. These omics data in turn serve as ingredients for developing computational models that can help derive deeper insights into the biology of cancer cells, and identify metabolic biomarkers. In this review, we provide an overview of omics data generated for cancer cells, and discuss recent studies on computational models that were developed using omics data in order to identify effective cancer metabolic biomarkers.

Generation of systemic antitumour immunity via the in situ modulation of the gut microbiome by an orally administered inulin gel

The performance of immune-checkpoint inhibitors, which benefit only a subset of patients and can cause serious immune-related adverse events, underscores the need for strategies that induce T-cell immunity with minimal toxicity. The gut microbiota has been implicated in the outcomes of patients following cancer immunotherapy, yet manipulating the gut microbiome to achieve systemic antitumour immunity is challenging. Here we show in multiple murine tumour models that inulin-a widely consumed dietary fibre-formulated as a 'colon-retentive' orally administered gel can effectively modulate the gut microbiome in situ, induce systemic memory-T-cell responses and amplify the antitumour activity of the checkpoint inhibitor anti-programmed cell death protein-1 (α-PD-1). Orally delivered inulin-gel treatments increased the relative abundances of key commensal microorganisms and their short-chain-fatty-acid metabolites, and led to enhanced recall responses for interferon-γ+CD8+ T cells as well as to the establishment of stem-like T-cell factor-1+PD-1+CD8+ T cells within the tumour microenvironment. Gels for the in situ modulation of the gut microbiome may be applicable more broadly to treat pathologies associated with a dysregulated gut microbiome.

Urinary Metabolic Markers of Bladder Cancer: A Reflection of the Tumor or the Response of the Body?

This work will review the metabolic information that various studies have obtained in recent years on bladder cancer, with particular attention to discovering biomarkers in urine for the diagnosis and prognosis of this disease. In principle, they would be capable of complementing cystoscopy, an invasive but nowadays irreplaceable technique or, in the best case, of replacing it. We will evaluate the degree of reproducibility that the different experiments have shown in the indication of biomarkers, and a synthesis will be attempted to obtain a consensus list that is more likely to become a guideline for clinical practice. In further analysis, we will inquire into the origin of these dysregulated metabolites in patients with bladder cancer. For this purpose, it will be helpful to compare the imbalances measured in urine with those known inside tumor cells or tissues. Although the urine analysis is sometimes considered a liquid biopsy because of its direct contact with the tumor in the bladder wall, it contains metabolites from all organs and tissues of the body, and the tumor is separated from urine by the most impermeable barrier found in mammals. The distinction between the specific and systemic responses can help understand the disease and its consequences in more depth.

Development and validation of a host-dependent, PDL1-independent, biomarker to predict 6-month progression-free survival in metastatic non-small cell lung cancer (mNSCLC) patients treated with anti-PD1 immune checkpoint inhibitors (ICI) in the CERTIM Cohort: The ELY study

Background

Immune checkpoint inhibitors (ICI) are dramatically active in a minority of non-small cell lung cancer (NSCLC) patients. We studied here the relationship between patients's metabolism and outcome under ICI.

Methods

Metastatic NSCLC patients underwent a nutritional assessment prior to initiating immunotherapy. Resting energy expenditure (REE) was measured (mREE) using ambulatory indirect calorimetry and compared with the theoretical value (tREE) provided by the Harris and Benedict formula. The primary endpoint was 6-month progression-free survival (PFS). Secondary endpoints included objective response rate (ORR) and disease control rate (DCR) based on investigator review per RECIST v1.1. and overall survival (OS). The association of patient's metabolism with 6-month PFS was first explored in a single-center training cohort to estimate the effect size. The relationship between patient's metabolism and 6-month PFS was then tested in an independent non interventional observational prospective cohort (ELY) of 100 patients recruited in two tertiary university centers.

Findings

In the entire cohort, the ORR was 14% for the hypermetabolic group (n = 10/74) vs 38% for the normometabolic group (n = 26/68), respectively (estimated difference 25%, 95CI 9–40%, p = 0.001). The DCR was 28% for the hypermetabolic group (n = 21/74) vs 53% for the normometabolic group (n = 36/68), respectively (estimated difference 25%, 95CI 7–42%, p = 0.005). In the validation cohort (100 patients, 2 centers), normometabolic patients (defined as mREE/tREE < 110%) had increased 6-month PFS (57% versus 22%; odds ratio: 4.76; IC95 [1.87 – 12.89]; p<0.001) and improved overall survival (HR 2.20; IC95: 1.41–3.44; p<0.001). The positive and negative predictive values of normometabolism to identify non-progressive patients at 6 months, were 57% and 78% respectively, sensitivity was 72% and specificity was 66%. In multivariate analysis including PD-L1 tumor status, basal metabolism was an independent predictive factor for 6-month PFS.

Interpretation

Normometabolism is a new independent parameter to identify mNSCLC patients who will benefit from ICI, with both improved tumor response, 6-month PFS, and survival.

Funding

This work was supported by Baxter (04012016).

Targeted epigenetic induction of mitochondrial biogenesis enhances antitumor immunity in mouse model

Considering the potential of combinatorial therapies in overcoming existing limitations of cancer immunotherapy, there is an increasing need to identify small-molecule modulators of immune cells capable of augmenting the effect of programmed cell death protein 1 (PD-1) blockade, leading to better cancer treatment. Although epigenetic drugs showed potential in combination therapy, the lack of sequence specificity is a major concern. Here, we identify and develop a DNA-based epigenetic activator with tri-arginine vector called EnPGC-1 that can trigger the targeted induction of the peroxisome proliferator-activated receptor-gamma coactivator 1 alpha/beta (PGC-1α/β), a regulator of mitochondrial biogenesis. EnPGC-1 enhances mitochondrial activation, energy metabolism, proliferation of CD8⁺ T cells in vitro, and, in particular, enhances oxidative phosphorylation, a feature of long-lived memory T cells. Genome-wide gene analysis suggests that EnPGC-1 and not the control compounds can regulate T cell activation as a major biological process. EnPGC-1 also synergizes with PD-1 blockade to enhance antitumor immunity and improved host survival.

High-salt diet mediates interplay between NK cells and gut microbiota to induce potent tumor immunity

High-salt diet (HSD) modulates effector and regulatory T cell functions and promotes tissue inflammation in autoimmune diseases. However, effects of HSD and its association with gut microbiota in tumor immunity remain undefined. Here, we report that HSD induces natural killer (NK) cell–mediated tumor immunity by inhibiting PD-1 expression while enhancing IFNγ and serum hippurate. Salt enhanced tumor immunity when combined with a suboptimal dose of anti-PD1 antibody. While HSD-induced tumor immunity was blunted upon gut microbiota depletion, fecal microbiota transplantation (FMT) from HSD mice restored the tumor immunity associated with NK cell functions. HSD increased the abundance of Bifidobacterium and caused increased gut permeability leading to intratumor localization of Bifidobacterium, which enhanced NK cell functions and tumor regression. Intratumoral injections of Bifidobacterium activated NK cells, which inhibited tumor growth. These results indicate that HSD modulates gut microbiome that induces NK cell–dependent tumor immunity with a potential translational perspective.

The Interaction Between the Microbiome and Tumors

Cancer is a significant global health problem and is characterized by a consistent increase in incidence and mortality rate. Deciphering the etiology and risk factors are essential parts of cancer research. Recently, the altered microbiome has been identified within the tumor microenvironment, tumor tissue, and even nonadjacent environments, which indicates a strong correlation between the microbiome and tumor development. However, the causation and mechanisms of this correlation remain unclear. Herein, we summarized and discussed the interaction between the microbiome and tumor progression. Firstly, the microbiome, which can be located in the tumor microenvironment, inside tumor tissues and in the nonadjacent environment, is different between cancer patients and healthy individuals. Secondly, the tumor can remodel microbial profiles by creating a more beneficial condition for the shifted microbiome. Third, the microbiome can promote tumorigenesis through a direct pathogenic process, including the establishment of an inflammatory environment and its effect on host immunity. The interactions between the microbiome and tumors can promote an understanding of the carcinogenesis and provide novel therapeutic strategies for cancers.

Evaluation of the roles and regulatory mechanisms of PD-1 target molecules in NSCLC progression

Background

Targeted programmed cell death protein 1 (PD-1) therapy could effectively improve the long-term prognosis of patients with non-small cell lung cancer (NSCLC). The role of PD-1 targets in the progression of NSCLC has not been fully revealed.

Methods

The differentially expressed genes (DEGs) in patients’ blood after NSCLC treatment with PD-1 blocker nivolumab in the GSE141479 dataset were analyzed by GEO2R and identified in the TCGA database. The mechanism of action involved in the PD-1 target molecules via the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein-protein interaction (PPI) network shows the relationship between PD-1 target molecules. The factors affecting the prognosis of NSCLC patients were identified via the COX regression analysis and survival analysis to build the risk model and nomogram.

Results

There were 64 DEGs in patients’ blood after nivolumab treatment and 48 DEGs in NSCLC tissues. The PD-1 target molecules involved cell proliferation, DNA replication, cell cycle, lung cancer, and other cellular processes. The prognostic factors CCNA2, CHEK1, DLGAP5, E2F8, FOXM1, HIST1H2BH, HJURP, MKI67, PLK1, TPX2, and TYMS, and the independent factors HIST1H2BH and PLK1, influenced the prognosis of NSCLC patients. HIST1H2BH and PLK1 were overexpressed in LUAD and LUSC tissues. The elevated expression levels of HIST1H2BH and PLK1 were related to the overall survival (OS) and the progression-free survival of NSCLC patients. High-risk NSCLC patients had a poor prognosis and were an independent factor influencing the poor prognosis of NSCLC patients. The high-risk model group was enriched with signaling mechanisms such as cell cycle, DNA replication, and homologous recombination.

Conclusions

The risk model based on PD-1 target molecules was helpful to assess the prognosis of NSCLC patients. HIST1H2BH and PLK1 might become prognostic biomarkers of NSCLC patients.

History and emerging trends in chemotherapy for gastric cancer

Chemotherapy is indispensable for gastric cancer. For unresectable and/or recurrent gastric cancer, first-line chemotherapy consists of multidrug regimens including oral 5-FU agents such as S1/Xeloda and platinum preparations, as well as Trastuzumab, which is effective in HER2-positive cases. Second- and third-line chemotherapy regimens include taxanes, Ramucirumab (R-mab), and Nivolumab (N-mab), which have different mechanisms of action from first-line chemotherapy. R-mab is molecularly targeted to vascular endothelial growth factor receptor 2 in the host cells, but its indication is not conditional. For resectable gastric cancer, in Eastern countries, postoperative adjuvant chemotherapy has been successful, including S1, Docetaxel/S1 (DS), and Xeloda/Oxaliplatin (Xelox) regimens, whereas, in Western countries, the 5-FU/Leucovorin/Oxaliplatin/Docetaxel (FLOT) regimen was recently shown to be effective in the perioperative chemotherapy setting. Most recently, however, in Eastern countries, perioperative SOX was demonstrated to be effective in specific advanced gastric cancer. For stage IV gastric cancer, new therapeutic strategies have been proposed such as neoadjuvant chemotherapy and conversion surgery, and cures can be conditionally obtained. Recent genomic understanding of gastric cancer proposed a diversity of molecular targets by molecular profiling. Such optimized chemotherapy regimens, according to the specific clinical situations, have been rigorously established for the best survival of advanced gastric cancer.

ALDH2 polymorphism rs671 is a predictor of PD-1/PD-L1 inhibitor efficacy against thoracic malignancies

Background

Aldehyde dehydrogenase 2 (ALDH2) plays an important role in the endogenous aldehyde detoxification of various types of cells. ALDH2*2, a variant allele of the ALDH2 polymorphism rs671, leads to decreased enzymatic activity. ALDH2*2 may enhance tumor antigen presentation due to aldehyde-induced DNA damage while suppressing peripheral blood T cell counts and T cell activation.

Methods

On the basis of our hypothesis that rs671 affects the sensitivity of immune checkpoint inhibitors (ICIs), we evaluated the effects of rs671 on patients with thoracic malignancies who started ICI therapy in 2016–2019. The cohort consisted of 105 cases, including 64 cases with adenocarcinoma and 30 cases with squamous cell carcinoma, 49 of whom were ALDH2*2 carriers. The first ICI was PD-1/PD-L1 inhibitor (Nivolumab, Pembrolizumab, or Atezolizumab) in all cases.

Results

The best response to anti-PD-1/PD-L1 therapy (partial response/stable disease/progressive disease) was 36%/50%/14% in the rs671(−) cases; however, the response was relatively poor in the rs671(+) cases (27%/29%/45%, respectively) (p = 0.002). The hazard ratio (95% confidence interval) of disease progression within the observation period of 6 months for the rs671(+) cases was estimated to be 5.0 (2.5–10) after the adjustment for covariates, including sex, Brinkman index, treatment line, tumor tissue programmed death-ligand 1 positivity rate, tumor tissue EGFR mutation. This association was also maintained in a stratified analysis, suggesting that ALDH2*2 is an independent negative predictive factor for the short-term prognosis of anti-PD-1/PD-L1 therapy. Thus, the progression-free survival (PFS) ratio of the rs671(+) cases decreased rapidly after ICI initiation but was eventually higher than that of the rs671(−) cases (restricted mean survival time in 12 months from 2 to 3 years afterward was 1.3 times that of the rs671(−) cases). Moreover, the highest PFS ratio after 2 years among sub-groups was found in the first-line treatment sub-group of rs671(+) group (40%).

Conclusions

Our study suggests that rs671 may be an accurate and cost-effective predictor of PD-1/PD-L1 inhibitor treatment, in which optimal case selection is an important issue.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08329-y.

Serum Metabolite Biomarkers Predictive of Response to PD-1 Blockade Therapy in Non-Small Cell Lung Cancer

Background: Despite remarkable success of immunotherapies with checkpoint blockade antibodies targeting programmed cell death protein 1 (PD-1), the majority of patients with non-small-cell lung cancer (NSCLC) have yet to receive durable benefits. We used the metabolomic profiling of early on-treatment serum to explore predictors of clinical outcomes of anti-PD-1 treatment in patients with advanced NSCLC. Methods: We recruited 74 Chinese patients who had stage IIIB/IV NSCLC-proven tumor progression and were treated with PD-1 inhibitor. The study was comprised of a discovery cohort of patients treated with nivolumab and two validation cohorts of patients receiving tislelizumab or nivolumab. Serum samples were collected 2-3 weeks after the first infusion of PD-1 inhibitor. Metabolomic profiling of serum was performed using ultrahigh performance lipid chromatograph-mass spectrometry. The serum metabolite biomarkers were identified using an integral workflow of nontargeted metabolomic data analysis. Results: A serum metabolite panel consisting of hypoxanthine and histidine was identified and validated as a predictor of response to PD-1 blockade treatment in patients with advanced NSCLC. High levels of both hypoxanthine and histidine in early on-treatment serum were associated with improved progression-free survival [hazard ratio (HR) = 0.078, 95% confidence interval (CI), 0.027-0.221, p < 0.001] and overall survival (HR = 0.124, 95% CI, 0.039-0.397, p < 0.001) in the discovery cohort. The serum metabolite panel showed a high sensitivity and specificity in distinguishing responders and non-responders in the validation cohorts 1 and 2, with an area under the receiver-operating characteristic curve of 0.933 and 1.000, respectively. High levels of serum hypoxanthine and histidine were correlated with improved progression-free survival in the validation cohort 1 (HR = 0.137, 95% CI, 0.040-0.467, p = 0.001) and in the validation cohort 2 (HR = 0.084, 95% CI, 0.009-0.762, p = 0.028). Conclusion: Our results revealed that hypoxanthine and histidine in early on-treatment serum are predictive biomarkers of response to PD-1 blockade therapy in patients with advanced NSCLC. The serum biomarker panel would enable early identification of NSCLC patients who may benefit from PD-1 blockade therapy.

Diagnosis of cancer at early stages based on the multiplex detection of tumor markers using metal nanoclusters

Traditional cancer diagnosis strategies are not considered by most people until the last resort, which delays many cancer treatments leading to advanced stages. Tumor marker sensors show great potential for detecting cancer because of its cost-effective and harmless checking procedures. Normally, one tumor marker is detected each time by using one type of sensor, but the accuracy to declare cancer is not always satisfied. Metal nanoclusters are ultra-small nanomaterials with low toxicity, distinct optical properties, catalytic activities, and cost-effective performance. Some metal nanoclusters have been designed to detect more than one tumor marker in a single step. The consideration of combined parameters using such facile sensing strategies has the potential to simplify the test procedure, and increase the diagnostic accuracy of early cancer. Therefore, various sensing strategies for the multiplex detection of tumor markers using metal nanoclusters are summarized.

Immunometabolism in the Tumor Microenvironment

Advances in immunotherapy have underscored the importance of antitumor immune responses in controlling cancer. However, the tumor microenvironment (TME) imposes several obstacles to the proper function of immune cells, including a metabolically challenging and immunosuppressive microenvironment. The increased metabolic activity of tumor cells can lead to the depletion of key nutrients required by immune cells and the accumulation of byproducts that hamper antitumor immunity. Furthermore, the presence of suppressive immune cells, such as regulatory T cells and myeloid-derived suppressor cells, and the expression of immune inhibitory receptors can negatively impact immune cell metabolism and function. This review summarizes the metabolic reprogramming that is characteristic of various immune cell subsets, discusses how the metabolism and function of immune cells are shaped by the TME, and highlights how therapeutic interventions aimed at improving the metabolic fitness of immune cells and alleviating the metabolic constraints in the TME can boost antitumor immunity.