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

Next-generation probiotics Alistipes onderdonkii enhances the efficacy of anti-PD-1 therapy in colorectal cancer

Despite significant breakthroughs of therapeutic antibodies targeting PD-1 in cancer treatment, most colorectal cancer (CRC) patients respond poorly to anti-PD-1 immunotherapy. The combination therapy strategies are used to overcome the limitations mentioned above. Alistipes (A.) onderdonkii has anti-cancer effects. This study aimed to examine A. onderdonkii's effects and the related mechanisms in the anti-PD-1 treatment for CRC. In this study, anti-PD-1 therapy notably affected gut microbiota community composition in mice, particularly upregulating A. onderdonkii abundance. A. onderdonkii supplementation markedly promoted anti-PD-1 therapy's effectiveness on CRC treatment, as manifested by the elevated CD8+ T cell infiltration, promoted intestinal barrier integrity, and affected serum metabolomics. A. onderdonkii showed similar effects to the identified next-generation probiotics (NGP) Akkermansia (A.) muciniphila. Additionally, the combination therapy of anti-PD-1 and probiotics supplementation reduced PD-1 level and elevated IL-2 level, indicating that anti-PD-1 combined with A. onderdonkii efficiently restored T cell functions by inhibiting suppressive checkpoints. In conclusion, anti-PD-1 plus A. onderdonkii supplementation could account for a potential method for CRC therapy. These results provide strong evidence for A. onderdonkii as a potential NGP.

Metabolomic signatures in liquid biopsy are associated with overall survival in metastatic melanoma patients treated with immune checkpoint inhibitor therapy

BACKGROUND

Immune checkpoint inhibitors (ICIs), such as anti-Cytotoxic T-Lymphocyte Antigen 4(CTLA-4) and anti-Programmed cell death protein 1 (PD-1) agents, have improved the prognosis of patients with metastatic melanoma. However, a proportion of patients develop resistance to these treatments, leading to a poor prognosis. Therefore, identifying potential non invasive and easy to measure biomarkers is crucial for guiding treatment strategies in patients with metastatic melanoma.

METHODS

A retrospective single-center study was conducted involving patients with metastatic stage IV melanoma who received first-line treatment with anti-CTL4 and/or anti-PD-1 agents. The patients were categorized into two groups on the basis of their 1-year overall survival (OS): those with good outcomes (long-term OS ≥ 1 year) and those with poor outcomes (short-term OS < 1 year). Peripheral metabolomics was performed using baseline sera from 132 patients via 600 MHz Nuclear Magnetic Resonance (NMR) spectroscopy. Enriched functional analysis was conducted to identify the metabolic pathways in which significant metabolites were involved.

RESULTS

Sparse partial least squares discriminant analysis (sPLS-DA) and loading plots obtained by analyzing the metabolomics profiles of samples collected before ICI treatment revealed significantly different levels of metabolites between the two groups (long-term OS vs. short-term OS). Specifically, lactate, tryptophan and valine significantly predicted the OS of the whole study population subjected to ICI immunotherapy; alanine, asparagine, glutathione, histidine, isoleucine and phenylalanine significantly predicted the OS of patients treated with ipilimumab; glucose, glutamine, histidine and proline significantly predicted the OS of patients treated with nivolumab; and lactate, lysine and proline significantly predicted the OS of patients treated with ipilimumab plus nivolumab. Notably, tryptophan levels were correlated with treatment response in the overall patient group, whereas histidine and lactate levels were associated with response in patients treated with ipilimumab and with ipilimumab plus nivolumab, respectively. Interestingly, higher pretreatment levels of histidine were commonly found in long-term OS subgroups of patients treated with ipilimumab, nivolumab or ipilimumab plus nivolumab. Interestingly, considering only those metabolites that predict OS after univariate analysis, higher histidine, and lower lactate and proline levels resulted as associated with favorable OS in at least two patient cohorts.

CONCLUSIONS

Overall, this exploratory liquid biopsy study revealed a strong correlation between the pretreatment levels of some metabolites and the OS of patients with metastatic stage IV melanoma treated with anti-CTL4 and/or anti-PD-1 antibodies in the first-line setting and revealed the potential of these molecules to predict outcomes and define personalized management and treatment strategies.

Histological and genetic features and therapeutic responses of lung cancers explored via the global analysis of their metabolome profile

BACKGROUND

Lung cancer is the deadliest disease globally, with more than 120,000 diagnosed cases and more than 75,000 deaths annually in Japan. Several treatment options for advanced lung cancer are available, and the discovery of biomarkers will be useful for personalized medicine. Using metabolome analysis, we aimed to identify biomarkers for diagnosis and treatment response by examining the changes in metabolites associated with lung cancer progression.

METHODS

Plasma samples from patients with recurrent or metastatic non-small cell lung carcinomas diagnosed at Tohoku University Hospital between 2019 and 2024 were used in this study. Metabolomic analysis was performed using the Biocrates Life Sciences MxP Quant 500 kit. Multivariate, principal component, and orthogonal partial least squares discriminant analyses were performed.

RESULTS

The triglyceride and phosphatidylcholine concentrations were higher in the patients with early than in those with advanced lung adenocarcinomas. However, the cholesterol ester concentrations were higher for the patients with advanced lung cancer. The concentrations of hexosylceramide were higher in patients with early lung adenocarcinoma than in those with squamous cell carcinoma. Relative to epidermal growth factor receptor (EGFR)-mutation negative cases, the EGFR-mutation positive cases showed marked differences between the ceramide and triglyceride concentrations. For the best therapeutic effect of EGFR-TKI treatment, the hexosylceramide (HexCer) (d18:1/24:0), ceramide (Cer) (d18:2/22:0), and ceramide (Cer) (d18:2/24:0) concentrations were higher for the stable and progressive disease groups. The concentrations of phosphatidylcholine (PC) ae C42:2, sphingomyelin (SM) C24:1, and lysophosphatidylcholine (lysoPC) a C18:2 were higher in the partial response group treated with immune checkpoint inhibitors and chemotherapy.

CONCLUSION

Metabolomic analysis may be useful for the diagnosis and treatment of lung cancer and may provide clues for new therapeutic strategies. PC ae C42:2, SM C24:1, and lysoPC a C18:2 can serve as predictive biomarkers for monitoring the therapeutic effects of the combination of immune checkpoint inhibitors and chemotherapy.

Fuel for thought: targeting metabolism in lung cancer

For over a century, we have appreciated that the biochemical processes through which micro- and macronutrients are anabolized and catabolized-collectively referred to as "cellular metabolism"-are reprogrammed in malignancies. Cancer cells in lung tumors rewire pathways of nutrient acquisition and metabolism to meet the bioenergetic demands for unchecked proliferation. Advances in precision medicine have ushered in routine genotyping of patient lung tumors, enabling a deeper understanding of the contribution of altered metabolism to tumor biology and patient outcomes. This paradigm shift in thoracic oncology has spawned a new enthusiasm for dissecting oncogenotype-specific metabolic phenotypes and creates opportunity for selective targeting of essential tumor metabolic pathways. In this review, we discuss metabolic states across histologic and molecular subtypes of lung cancers and the additional changes in tumor metabolic pathways that occur during acquired therapeutic resistance. We summarize the clinical investigation of metabolism-specific therapies, addressing successes and limitations to guide the evaluation of these novel strategies in the clinic. Beyond changes in tumor metabolism, we also highlight how non-cellular autonomous processes merit particular consideration when manipulating metabolic processes systemically, such as efforts to disentangle how lung tumor cells influence immunometabolism. As the future of metabolic therapeutics hinges on use of models that faithfully recapitulate metabolic rewiring in lung cancer, we also discuss best practices for harmonizing workflows to capture patient specimens for translational metabolic analyses.

The gut microbiota improves the efficacy of immune-checkpoint inhibitor immunotherapy against tumors: From association to cause and effect

Immune-checkpoint inhibitors (ICIs), including anti-PD-1/PD-L1 therapeutic antibodies, have markedly enhanced survival across numerous cancer types. However, the limited number of patients with durable benefits creates an urgent need to identify response biomarkers and to develop novel strategies so as to improve response. It is widely recognized that the gut microbiome is a key mediator in shaping immunity. Additionally, the gut microbiome shows significant potential in predicting the response to and enhancing the efficacy of ICI immunotherapy against cancer. Recent studies encompassing mechanistic analyses and clinical trials of microbiome-based therapy have shown a cause-and-effect relationship between the gut microbiome and the modulation of the ICI immunotherapeutic response, greatly contributing to the establishment of novel strategies that will improve response and overcome resistance to ICI treatment. In this review, we outline the current state of research advances and discuss the future directions of utilizing the gut microbiome to enhance the efficacy of ICI immunotherapy against tumors.

Proteomic Investigation of Immune Checkpoints and Some of Their Inhibitors

Immune checkpoints are crucial molecules for the maintenance of antitumor immune responses. The activation or inhibition of these molecules is dependent on the interactions between receptors and ligands; such interactions can provide inhibitory or stimulatory signals to the various components of the immune system. Over the last 10 years, the inhibition of immune checkpoints, such as cytotoxic T lymphocyte antigen-4, programmed cell death-1, and programmed cell death ligand-1, has taken a leading role in immune therapy. This relatively recent therapy regime is based on the use of checkpoint inhibitors, which enhance the immune response towards various forms of cancer. For a subset of patients with specific forms of cancer, these inhibitors can induce a durable response to therapy; however, the medium response rate to such therapy remains relatively poor. Recent research activities have demonstrated that the disease response to this highly promising therapy resembles the response of many forms of cancer to chemotherapy, where an encouraging initial response is followed by acquired resistance to treatment and progress of the disease. That said, these inhibitors are now used as single agents or in combination with chemotherapies as first or second lines of treatment for about 50 types of cancer. The prevailing opinion regarding immune therapy suggests that for this approach of therapy to deliver on its promise, a number of challenges have to be circumvented. These challenges include understanding the resistance mechanisms to immune checkpoint blockade, the identification of more efficient inhibitors, extending their therapeutic benefits to a wider audience of cancer patients, better management of immune-related adverse side effects, and, more urgently the identification of biomarkers, which would help treating oncologists in the identification of patients who are likely to respond positively to the immune therapies and, last but not least, the prices of therapy which can be afforded by the highest number of patients. Numerous studies have demonstrated that understanding the interaction between these checkpoints and the immune system is essential for the development of efficient checkpoint inhibitors and improved immune therapies. In the present text, we discuss some of these checkpoints, their inhibitors, and some works in which mass spectrometry-based proteomic analyses were applied.

Inflammatory factors and risk of lung adenocarcinoma: a Mendelian randomization study mediated by blood metabolites

Background

Lung adenocarcinoma (LUAD) is the most common type of lung cancer, and its pathogenesis remains not fully elucidated. Inflammation and metabolic dysregulation are considered to play crucial roles in LUAD development, but their causal relationships and specific mechanisms remain unclear.

Methods

This study employed a two-sample Mendelian randomization (MR) approach to systematically evaluate the causal associations between 91 circulating inflammatory factors, 1,400 serum metabolites, and LUAD. We utilized LUAD genome-wide association studies (GWAS) data from the FinnGen biobank and GWAS data of metabolites and inflammatory factors from the GWAS catalog to conduct two-sample MR analyses. For the identified key metabolites, we further used mediator MR to investigate their mediating effects in the influence of IL-17A on LUAD and explored potential mechanisms through protein-protein interaction and functional enrichment analyses.

Results

The MR analyses revealed that IL-17A (OR 0.78, 95%CI 0.62-0.99) was negatively associated with LUAD, while 71 metabolites were significantly associated with LUAD. Among them, ferulic acid 4-sulfate may play a crucial mediating role in the suppression of LUAD by IL-17A (OR 0.87, 95%CI 0.78-0.97). IL-17A may exert its anti-LUAD effects through extensive interactions with genes related to ferulic acid 4-sulfate metabolism (such as SULT1A1, CYP1A1, etc.), inhibiting oxidative stress and inflammatory responses, as well as downstream tumor-related pathways of ferulic acid 4-sulfate (such as MAPK, NF-κB, etc.).

Conclusion

This study discovered causal associations between IL-17A, multiple serum metabolites, and LUAD occurrence, revealing the key role of inflammatory and metabolic dysregulation in LUAD pathogenesis. Our findings provide new evidence-based medical support for specific inflammatory factors and metabolites as early predictive and risk assessment biomarkers for LUAD, offering important clues for subsequent mechanistic studies and precision medicine applications.

Metabolomics for searching validated biomarkers in cancer studies: a decade in review

INTRODUCTION

In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways.

AREAS COVERED

This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types.

EXPERT OPINION

Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.

Evaluating for Correlations between Specific Metabolites in Patients Receiving First-Line or Second-Line Immunotherapy for Metastatic or Recurrent NSCLC: An Exploratory Study Based on Two Cohorts

Immune checkpoint inhibitors (ICI) have displayed impressive clinical efficacy in the context of non-small cell lung cancer (NSCLC). However, most patients do not achieve long-term survival. Minimally invasive collected samples are attracting significant interest as new fields of biomarker study, and metabolomics is one of these growing fields. We concentrated on the augmented value of the metabolomic profile in differentiating long-term survival from short-term survival in patients with NSCLC subjected to ICIs. We prospectively recruited 97 patients with stage IV NSCLC who were treated with anti-PD-1 inhibitor, including patients treated with monoimmunotherapy as second-line treatment (Cohort 1), and patients treated with combination immunotherapy as first-line treatment (Cohort 2). Each cohort was divided into long-term and short-term survival groups. All blood samples were collected before beginning immunotherapy. Serum metabolomic profiling was performed by UHPLC-Q-TOF MS analysis. Pareto-scaled principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis were performed. In Cohort 1, the mPFS and mOS of long-survival patients are 27.05 and NR months, respectively, and those of short-survival patients are 2.79 and 10.59 months. In Cohort 2, the mPFS and mOS of long-survival patients are 27.35 and NR months, respectively, and those of short-survival patients are 3.77 and 12.17 months. A total of 41 unique metabolites in Cohort 1 and 47 in Cohort 2 were screened. In Cohorts 1 and 2, there are 6 differential metabolites each that are significantly associated with both progression-free survival and overall survival. The AUC values for all groups ranged from 0.73 to 0.95. In cohort 1, the top 3 enriched KEGG pathways, as determined through significant different metabolic pathway analysis, were primary bile acid biosynthesis, African trypanosomiasis, and choline metabolism in cancer. In Cohort 2, the top 3 enriched KEGG pathways were the citrate cycle (TCA cycle), PPAR signaling pathway, and primary bile acid biosynthesis. The primary bile acid synthesis pathway had significant differences in the long-term and short-term survival groups in both Cohorts 1 and 2. Our study suggests that peripheral blood metabolomic analysis is critical for identifying metabolic biomarkers and pathways responsible for the patients with NSCLC treated with ICIs.

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.

Dietary Lactobacillus rhamnosus GG extracellular vesicles enhance antiprogrammed cell death 1 (anti-PD-1) immunotherapy efficacy against colorectal cancer

There is a need to explore combination therapy to improve the efficacy of immunotherapy for colorectal cancer through food probiotics. In this study, extracellular vesicles (EV) derived from Lactobacillus rhamnosus GG (LGG-EV) were successfully isolated. Adjusting the culture temperature to 30 °C led to an elevated LGG-EV yield, and the addition of penicillin resulted in a decrease in particle size. In addition, LGG-EV have better gastrointestinal tract stability in a Ca2+ environment in vivo and in vitro. Oral administration of LGG-EV synergistically improved anti-PD-1 immunotherapy efficacy against colorectal cancer. Mechanistically, LGG-EV modulated intestinal immunity by increasing the CD8+ T/CD4+ T cell ratio in mesenteric lymph nodes and enhancing the ratio of MHC II+ DC cells, CD4+ T cells, and CD8+ T cells in tumor tissues. Meanwhile, the diversity of the gut microbiota and the abundance of beneficial bacteria, such as Lactobacillus, increased in the combined-treatment mice. In addition, there were significant changes in the levels of serum metabolites associated with the microbiota and anti-tumor effects, including uridine, which was elevated by the combination of anti-PD-1 and LGG-EV treatment. Our findings provide theoretical and mechanistic insights into the development of LGG-EV as postbiotics in combination with immune checkpoint inhibitors for cancer therapy.

Increasing brain N-acetylneuraminic acid alleviates hydrocephalus-induced neurological deficits

AIMS

This metabolomic study aimed to evaluate the role of N-acetylneuraminic acid (Neu5Ac) in the neurological deficits of normal pressure hydrocephalus (NPH) and its potential therapeutic effect.

METHODS

We analyzed the metabolic profiles of NPH using cerebrospinal fluid with multivariate and univariate statistical analyses in a set of 42 NPH patients and 38 controls. We further correlated the levels of differential metabolites with severity-related clinical parameters, including the normal pressure hydrocephalus grading scale (NPHGS). We then established kaolin-induced hydrocephalus in mice and treated them using N-acetylmannosamine (ManNAc), a precursor of Neu5Ac. We examined brain Neu5Ac, astrocyte polarization, demyelination, and neurobehavioral outcomes to explore its therapeutic effect.

RESULTS

Three metabolites were significantly altered in NPH patients. Only decreased Neu5Ac levels were correlated with NPHGS scores. Decreased brain Neu5Ac levels have been observed in hydrocephalic mice. Increasing brain Neu5Ac by ManNAc suppressed the activation of astrocytes and promoted their transition from A1 to A2 polarization. ManNAc also attenuated the periventricular white matter demyelination and improved neurobehavioral outcomes in hydrocephalic mice.

CONCLUSION

Increasing brain Neu5Ac improved the neurological outcomes associated with the regulation of astrocyte polarization and the suppression of demyelination in hydrocephalic mice, which may be a potential therapeutic strategy for NPH.

Targeting cancer metabolic pathways for improving chemotherapy and immunotherapy

Recent discoveries in cancer metabolism have revealed promising metabolic targets to modulate cancer progression, drug response, and anti-cancer immunity. Combination therapy, consisting of metabolic inhibitors and chemotherapeutic or immunotherapeutic agents, offers new opportunities for improved cancer therapy. However, it also presents challenges due to the complexity of cancer metabolic pathways and the metabolic interactions between tumor cells and immune cells. Many studies have been published demonstrating potential synergy between novel inhibitors of metabolism and chemo/immunotherapy, yet our understanding of the underlying mechanisms remains limited. Here, we review the current strategies of altering the metabolic pathways of cancer to improve the anti-cancer effects of chemo/immunotherapy. We also note the need to differentiate the effect of metabolic inhibition on cancer cells and immune cells and highlight nanotechnology as an emerging solution. Improving our understanding of the complexity of the metabolic pathways in different cell populations and the anti-cancer effects of chemo/immunotherapy will aid in the discovery of novel strategies that effectively restrict cancer growth and augment the anti-cancer effects of chemo/immunotherapy.

Serum metabolomics of treatment response in myasthenia gravis

OBJECTIVE

High-dose prednisone use, lasting several months or longer, is the primary initial therapy for myasthenia gravis (MG). Upwards of a third of patients do not respond to treatment. Currently no biomarkers can predict clinical responsiveness to corticosteroid treatment. We conducted a discovery-based study to identify treatment responsive biomarkers in MG using sera obtained at study entry to the thymectomy clinical trial (MGTX), an NIH-sponsored randomized, controlled study of thymectomy plus prednisone versus prednisone alone.

METHODS

We applied ultra-performance liquid chromatography coupled with electro-spray quadrupole time of flight mass spectrometry to obtain comparative serum metabolomic and lipidomic profiles at study entry to correlate with treatment response at 6 months. Treatment response was assessed using validated outcome measures of minimal manifestation status (MMS), MG-Activities of Daily Living (MG-ADL), Quantitative MG (QMG) score, or a strictly defined composite measure of response.

RESULTS

Increased serum levels of phospholipids were associated with treatment response as assessed by QMG, MMS, and the Responders classification, but all measures showed limited overlap in metabolomic profiles, in particular the MG-ADL. A panel including histidine, free fatty acid (13:0), γ-cholestenol and guanosine was highly predictive of the strictly defined treatment response measure. The AUC in Responders' prediction for these markers was 0.90 irrespective of gender, age, thymectomy or baseline prednisone use. Pathway analysis suggests that xenobiotic metabolism could play a major role in treatment resistance. There was no association with outcome and gender, age, thymectomy or baseline prednisone use.

INTERPRETATION

We have defined a metabolomic and lipidomic profile that can now undergo validation as a treatment predictive marker for MG patients undergoing corticosteroid therapy. Metabolomic profiles of outcome measures had limited overlap consistent with their assessing distinct aspects of treatment response and supporting unique biological underpinning for each outcome measure. Interindividual variation in prednisone metabolism may be a determinate of how well patients respond to treatment.

Gut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy

Oncogenesis is associated with intestinal dysbiosis, and stool shotgun metagenomic sequencing in individuals with this condition might constitute a non-invasive approach for the early diagnosis of several cancer types. The prognostic relevance of antibiotic intake and gut microbiota composition urged investigators to develop tools for the detection of intestinal dysbiosis to enable patient stratification and microbiota-centred clinical interventions. Moreover, since the advent of immune-checkpoint inhibitors (ICIs) in oncology, the identification of biomarkers for predicting their efficacy before starting treatment has been an unmet medical need. Many previous studies addressing this question, including a meta-analysis described herein, have led to the description of Gut OncoMicrobiome Signatures (GOMS). In this Review, we discuss how patients with cancer across various subtypes share several GOMS with individuals with seemingly unrelated chronic inflammatory disorders who, in turn, tend to have GOMS different from those of healthy individuals. We discuss findings from the aforementioned meta-analysis of GOMS patterns associated with clinical benefit from or resistance to ICIs across different cancer types (in 808 patients), with a focus on metabolic and immunological surrogate markers of intestinal dysbiosis, and propose practical guidelines to incorporate GOMS in decision-making for prospective clinical trials in immuno-oncology.

Cutaneous immune-related adverse events to immune checkpoint inhibitors: from underlying immunological mechanisms to multi-omics prediction

The development of immune checkpoint inhibitors (ICIs) has dramatically altered the landscape of therapy for multiple malignancies, including urothelial carcinoma, non-small cell lung cancer, melanoma and gastric cancer. As part of their anti-tumor properties, ICIs can enhance susceptibility to inflammatory side effects known as immune-related adverse events (irAEs), in which the skin is one of the most commonly and rapidly affected organs. Although numerous questions still remain unanswered, multi-omics technologies have shed light into immunological mechanisms, as well as the correlation between ICI-induced activation of immune systems and the incidence of cirAE (cutaneous irAEs). Therefore, we reviewed integrated biological layers of omics studies combined with clinical data for the prediction biomarkers of cirAEs based on skin pathogenesis. Here, we provide an overview of a spectrum of dermatological irAEs, discuss the pathogenesis of this "off-tumor toxicity" during ICI treatment, and summarize recently investigated biomarkers that may have predictive value for cirAEs via multi-omics approach. Finally, we demonstrate the prognostic significance of cirAEs for immune checkpoint blockades.

Identification of metabolic biomarkers for diagnosis of epithelial ovarian cancer using internal extraction electrospray ionization mass spectrometry (iEESI-MS)

BACKGROUND

Epithelial ovarian cancer (EOC) is the leading cause of death from gynecologic malignancies. The poor prognosis of EOC is mainly due to its asymptomatic early stage, lack of effective screening methods, and a late diagnosis in the advanced stages of the disease.

OBJECTIVE

This study investigated metabolomic abnormalities in epithelial ovarian cancers.

METHODS

Our study developed a novel strategy to rapidly identify the metabolic biomarkers in the plasma of the EOC patients using Internal Extraction Electrospray Ionization Mass Spectrometry (IEESI-MS) and Liquid Chromatography-mass Spectrometry (HPLC-MS), which could distinguish the differential metabolites in between plasma samples collected from 98 patients with epithelial ovarian cancer, including 78 cases with original (P), and 20 cases with self-configuration (ZP), as well as 60 healthy subjects, including 30 cases in the original sample (H), 30 cases in self-configuration (ZH), and 6 cases in a blind sample (B).

RESULTS

Our study detected 880 metabolites based on criteria variable importance in projection (VIP) > 1, among which 26 metabolites were selected for further identification. They are mainly metabolism-related lipids, amino acids, nucleic acids, and others. The metabolic pathways associated with the differential metabolites were explored by the KEGG analysis, a comprehensive database that integrates genome, chemistry, and system function information. The abnormal metabolites of EOC patients identified by IEESI-MS and HPLC-MS included Lysophosphatidylcholine (16:0) [Lyso PC (16:0)], L-Phenylalanine, L-Leucine, Phenylpyruvic acid, L-Tryptophan, and L-Histidine.

CONCLUSIONS

Identifying the abnormal metabolites of EOC patients through metabolomics analyses could provide a new strategy to identify valuable potential biomarkers for the screening and early diagnosis of EOC.

To metabolomics and beyond: a technological portfolio to investigate cancer metabolism

Tumour cells have exquisite flexibility in reprogramming their metabolism in order to support tumour initiation, progression, metastasis and resistance to therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic and redox status to sustain the increased energetic demand of the cells. Over the last decades, the cancer metabolism field has seen an explosion of new biochemical technologies giving more tools than ever before to navigate this complexity. Within a cell or a tissue, the metabolites constitute the direct signature of the molecular phenotype and thus their profiling has concrete clinical applications in oncology. Metabolomics and fluxomics, are key technological approaches that mainly revolutionized the field enabling researchers to have both a qualitative and mechanistic model of the biochemical activities in cancer. Furthermore, the upgrade from bulk to single-cell analysis technologies provided unprecedented opportunity to investigate cancer biology at cellular resolution allowing an in depth quantitative analysis of complex and heterogenous diseases. More recently, the advent of functional genomic screening allowed the identification of molecular pathways, cellular processes, biomarkers and novel therapeutic targets that in concert with other technologies allow patient stratification and identification of new treatment regimens. This review is intended to be a guide for researchers to cancer metabolism, highlighting current and emerging technologies, emphasizing advantages, disadvantages and applications with the potential of leading the development of innovative anti-cancer therapies.

Cell adhesion molecules and immunotherapy in advanced non-small cell lung cancer: Current process and potential application

Advanced non-small cell lung cancer (NSCLC) is a severe disease and still has high mortality rate after conventional treatment (e.g., surgical resection, chemotherapy, radiotherapy and targeted therapy). In NSCLC patients, cancer cells can induce immunosuppression, growth and metastasis by modulating cell adhesion molecules of both cancer cells and immune cells. Therefore, immunotherapy is increasingly concerned due to its promising anti-tumor effect and broader indication, which targets cell adhesion molecules to reverse the process. Among these therapies, immune checkpoint inhibitors (mainly anti-PD-(L)1 and anti-CTLA-4) are most successful and have been adapted as first or second line therapy in advanced NSCLC. However, drug resistance and immune-related adverse reactions restrict its further application. Further understanding of mechanism, adequate biomarkers and novel therapies are necessary to improve therapeutic effect and alleviate adverse effect.

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.

Current advances in antibody-based serum biomarker studies: From protein microarray to phage display

PURPOSE

This review aims to summarize the technological advances in the field of antibody-based biomarker studies by proteome microarray and phage display. In addition, the possible development directions of this field are also discussed.

EXPERIMENTAL DESIGN

We have focused on the antibody profiling by proteome microarray and phage display, including the technological advances, the tools/resources constructed, and the characteristics of both platforms.

RESULTS

With the help of tools/resources and technological advances in proteome microarray and phage display, the efficiency of profiling antibody-based biomarkers in serum samples has been greatly improved.

CONCLUSIONS

In the past few years, proteome microarray and phage display, especially the latter one, have already demonstrated their capacity and efficiency for biomarker identification. In the near future, we believe that more antibody-based biomarkers could be identified, and some of them could eventually be developed into real clinical applications.

CD8+ T Cell-Based Molecular Classification With Heterogeneous Immunogenomic Landscapes and Clinical Significance of Clear Cell Renal Cell Carcinoma

The tumor microenvironment (TME) exerts a high impact on tumor biology and immunotherapy. The heterogeneous phenotypes and the clinical significance of CD8⁺ T cells in TME have not been fully elucidated. Here, a comprehensive immunogenomic analysis based on multi-omics data was performed to investigate the clinical significance and tumor heterogeneity between CD8⁺ T cell-related molecular clusters. We identified two distinct molecular clusters of ccRCC (C1 and C2) in TCGA and validated in E-MTAB-1980 cohorts. The C1 cluster was characterized by unfavorable prognosis, increased expression levels of CD8⁺ T cell exhaustion markers, high immune infiltration levels as well as more immune escape mechanisms. The C2 cluster was featured by favorable prognosis, elevated expression levels of CD8⁺ T cell effector markers, low load of copy number loss and low frequency of 9p21.3 deletion. Moreover, the effect of molecular classifications on Nivolumab therapeutic efficacy in the CheckMate 025 cohort was examined, and the C2 cluster exhibited a better prognosis. Taken together, we determine two CD8⁺ T cell-related molecular clusters in ccRCC, and provide new insights for evaluating the functions of CD8⁺ T cells. Our molecular classification is a potential strategy for prognostic prediction and immunotherapeutic guidance for ccRCC patients.

Predictable Roles of Peripheral IgM Memory B Cells for the Responses to Anti-PD-1 Monotherapy Against Advanced Non-Small Cell Lung Cancer

Tumor-infiltrating B cells and tertiary lymphoid structures have been identified to predict the responses to immune checkpoint inhibitors (ICIs) in cancer immunotherapy. Considering the feasibility of sample collection, whether peripheral B cell signatures are associated with the responses to ICI therapy remains unclear. Herein, we have defined peripheral B cell signatures in advanced non-small cell lung cancer (NSCLC) patients receiving anti-PD-1 monotherapy and investigated their associations with clinical efficacy. It was found that the percentages of B cells before the treatment (baseline) were significantly higher (P = 0.004) in responder (R, n = 17) than those in non-responder (NonR, n = 33) NSCLC patients in a discovery cohort. Moreover, the percentages of baseline IgM⁺ memory B cells were higher (P < 0.001) in R group than those in NonR group, and associated with a longer progression free survival (PFS) (P = 0.003). By logistic regression analysis peripheral baseline IgM⁺ memory B cells were identified as an independent prognostic factor (P = 0.002) for the prediction of the responses to anti-PD-1 monotherapy with the AUC value of 0.791, which was further validated in another anti-PD-1 monotherapy cohort (P = 0.011, n = 70) whereas no significance was observed in patients receiving anti-PD-L1 monotherapy (P = 0.135, n = 30). Therefore, our data suggest the roles of peripheral IgM⁺ memory B cells in predicting the responses to anti-PD-1 treatment in Chinese advanced NSCLC patients.