Targeting NTRK1 Enhances Immune Checkpoint Inhibitor Efficacy in NTRK1 Wild-type Non-Small Cell Lung Cancer.

Treatment of non-small cell lung cancer (NSCLC) has drastically changed in recent years owing to the robust anti-cancer effects of immune-checkpoint inhibitors (ICI). However, only 20% of NSCLC patients benefit from ICIs, highlighting the need to uncover the mechanisms mediating resistance. By analyzing the overall survival (OS) and mutational profiles of 424 NSCLC patients who received ICI treatments between 2015 and 2021, we determined that patients carrying a loss of function mutation in neurotrophic tyrosine kinase receptor 1 (NTRK1) had a prolonged OS compared to patients with wild-type NTRK1. Notably, suppression of the NTRK1 pathway by knockdown or Entrectinib treatment significantly enhanced ICI efficacy in mouse NSCLC models. Comprehensive T cell population analyses demonstrated that stem-like CD4+ T cells and effector CD4+ and CD8+ T cells were highly enriched in anti-PD-1 treated mice bearing tumors with decreased NTRK1 signaling. RNA sequencing revealed that suppression of NTRK1 signaling in tumor cells increased complement C3 expression, which enhanced the recruitment of T cells and myeloid cells and stimulated M1-like macrophage polarization in the tumor. Together, this study demonstrates a role for NTRK1 signaling in regulating crosstalk between tumor cells and immune cells in the tumor microenvironment and provides a potential therapeutic approach to overcomes immunotherapy resistance in NTRK1 wild-type NSCLC patients.

Mutations Associated With High-Grade irAEs in NSCLC Patients Receiving Immunotherapies.

OBJECTIVES: Compared to low-grade irAEs, high-grade irAEs are more often dose-limiting and can alter the long-term treatment options for a patient. Predicting the incidence of high-grade irAEs would help with treatment selection and therapeutic drug monitoring. MATERIALS AND METHODS: We performed a retrospective study of 430 stage III and IV patients with non-small cell lung cancer (NSCLC) who received an immune checkpoint inhibitor (ICI), either with or without chemotherapy, at a single comprehensive cancer center from 2015 to 2022. The study team retrieved sequencing data and complete clinical information, including detailed irAEs medical records. Fisher's exact test was used to determine the association between mutations and the presence or absence of high-grade irAEs. Patients were analyzed separately based on tumor subtypes and sequencing platforms. RESULTS: High-grade and low-grade irAEs occurred in 15.2% and 46.2% of patients, respectively. Respiratory and gastrointestinal irAEs were the 2 most common irAEs. The distribution of patients with or without irAEs was similar between ICI and ICI+chemotherapy-treated patients. By analyzing the mutation data, we identified 5 genes (MYC, TEK, FANCA, FAM123B, and MET) with mutations that were correlated with an increased risk of high-grade irAEs. For the adenocarcinoma subtype, mutations in TEK, MYC, FGF19, RET, and MET were associated with high-grade irAEs; while for the squamous subtype, ERBB2 mutations were associated with high-grade irAEs. CONCLUSION: This study is the first to demonstrate that specific tumor mutations correlate with the incidence of high-grade irAEs in patients with NSCLC treated with an ICI, providing molecular guidance for treatment selection and drug monitoring.

Epigenetic MLH1 silencing concurs with mismatch repair deficiency in sporadic, naturally occurring colorectal cancer in rhesus macaques.

BACKGROUND: Naturally occurring colorectal cancers (CRC) in rhesus macaques share many features with their human counterparts and are useful models for cancer immunotherapy; but mechanistic data are lacking regarding the comparative molecular pathogenesis of these cancers. METHODS: We conducted state-of-the-art imaging including CT and PET, clinical assessments, and pathological review of 24 rhesus macaques with naturally occurring CRC. Additionally, we molecularly characterized these tumors utilizing immunohistochemistry (IHC), microsatellite instability assays, DNAseq, transcriptomics, and developed a DNA methylation-specific qPCR assay for MLH1, CACNA1G, CDKN2A, CRABP1, and NEUROG1, human markers for CpG island methylator phenotype (CIMP). We furthermore employed Monte-Carlo simulations to in-silico model alterations in DNA topology in transcription-factor binding site-rich promoter regions upon experimentally demonstrated DNA methylation. RESULTS: Similar cancer histology, progression patterns, and co-morbidities could be observed in rhesus as reported for human CRC patients. IHC identified loss of MLH1 and PMS2 in all cases, with functional microsatellite instability. DNA sequencing revealed the close genetic relatedness to human CRCs, including a similar mutational signature, chromosomal instability, and functionally-relevant mutations affecting KRAS (G12D), TP53 (R175H, R273*), APC, AMER1, ALK, and ARID1A. Interestingly, MLH1 mutations were rarely identified on a somatic or germline level. Transcriptomics not only corroborated the similarities of rhesus and human CRCs, but also demonstrated the significant downregulation of MLH1 but not MSH2, MSH6, or PMS2 in rhesus CRCs. Methylation-specific qPCR suggested CIMP-positivity in 9/16 rhesus CRCs, but all 16/16 exhibited significant MLH1 promoter hypermethylation. DNA hypermethylation was modelled to affect DNA topology, particularly propeller twist and roll profiles. Modelling the DNA topology of a transcription factor binding motif (TFAP2A) in the MLH1 promoter that overlapped with a methylation-specific probe, we observed significant differences in DNA topology upon experimentally shown DNA methylation. This suggests a role of transcription factor binding interference in epigenetic silencing of MLH1 in rhesus CRCs. CONCLUSIONS: These data indicate that epigenetic silencing suppresses MLH1 transcription, induces the loss of MLH1 protein, abrogates mismatch repair, and drives genomic instability in naturally occurring CRC in rhesus macaques. We consider this spontaneous, uninduced CRC in immunocompetent, treatment-naïve rhesus macaques to be a uniquely informative model for human CRC.

A community challenge to predict clinical outcomes after immune checkpoint blockade in non-small cell lung cancer.

BACKGROUND: Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. METHODS: Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. RESULTS: A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1. CONCLUSIONS: This DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICI clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICI efficacy. TRIAL REGISTRATION: CheckMate 026; NCT02041533, registered January 22, 2014. CheckMate 227; NCT02477826, registered June 23, 2015.

Single-cell sequencing reveals the landscape of the human brain metastatic microenvironment.

Brain metastases is the most common intracranial tumor and account for approximately 20% of all systematic cancer cases. It is a leading cause of death in advanced-stage cancer, resulting in a five-year overall survival rate below 10%. Therefore, there is a critical need to identify effective biomarkers that can support frequent surveillance and promote efficient drug guidance in brain metastasis. Recently, the remarkable breakthroughs in single-cell RNA-sequencing (scRNA-seq) technology have advanced our insights into the tumor microenvironment (TME) at single-cell resolution, which offers the potential to unravel the metastasis-related cellular crosstalk and provides the potential for improving therapeutic effects mediated by multifaceted cellular interactions within TME. In this study, we have applied scRNA-seq and profiled 10,896 cells collected from five brain tumor tissue samples originating from breast and lung cancers. Our analysis reveals the presence of various intratumoral components, including tumor cells, fibroblasts, myeloid cells, stromal cells expressing neural stem cell markers, as well as minor populations of oligodendrocytes and T cells. Interestingly, distinct cellular compositions are observed across different samples, indicating the influence of diverse cellular interactions on the infiltration patterns within the TME. Importantly, we identify tumor-associated fibroblasts in both our in-house dataset and external scRNA-seq datasets. These fibroblasts exhibit high expression of type I collagen genes, dominate cell-cell interactions within the TME via the type I collagen signaling axis, and facilitate the remodeling of the TME to a collagen-I-rich extracellular matrix similar to the original TME at primary sites. Additionally, we observe M1 activation in native microglial cells and infiltrated macrophages, which may contribute to a proinflammatory TME and the upregulation of collagen type I expression in fibroblasts. Furthermore, tumor cell-specific receptors exhibit a significant association with patient survival in both brain metastasis and native glioblastoma cases. Taken together, our comprehensive analyses identify type I collagen-secreting tumor-associated fibroblasts as key mediators in metastatic brain tumors and uncover tumor receptors that are potentially associated with patient survival. These discoveries provide potential biomarkers for effective therapeutic targets and intervention strategies.

c-Met Mediated Cytokine Network Promotes Brain Metastasis of Breast Cancer by Remodeling Neutrophil Activities.

The brain is one of the most common metastatic sites among breast cancer patients, especially in those who have Her2-positive or triple-negative tumors. The brain microenvironment has been considered immune privileged, and the exact mechanisms of how immune cells in the brain microenvironment contribute to brain metastasis remain elusive. In this study, we found that neutrophils are recruited and influenced by c-Met high brain metastatic cells in the metastatic sites, and depletion of neutrophils significantly suppressed brain metastasis in animal models. Overexpression of c-Met in tumor cells enhances the secretion of a group of cytokines, including CXCL1/2, G-CSF, and GM-CSF, which play critical roles in neutrophil attraction, granulopoiesis, and homeostasis. Meanwhile, our transcriptomic analysis demonstrated that conditioned media from c-Met high cells significantly induced the secretion of lipocalin 2 (LCN2) from neutrophils, which in turn promotes the self-renewal of cancer stem cells. Our study unveiled the molecular and pathogenic mechanisms of how crosstalk between innate immune cells and tumor cells facilitates tumor progression in the brain, which provides novel therapeutic targets for treating brain metastasis.

An integrated tumor, immune and microbiome atlas of colon cancer.

The lack of multi-omics cancer datasets with extensive follow-up information hinders the identification of accurate biomarkers of clinical outcome. In this cohort study, we performed comprehensive genomic analyses on fresh-frozen samples from 348 patients affected by primary colon cancer, encompassing RNA, whole-exome, deep T cell receptor and 16S bacterial rRNA gene sequencing on tumor and matched healthy colon tissue, complemented with tumor whole-genome sequencing for further microbiome characterization. A type 1 helper T cell, cytotoxic, gene expression signature, called Immunologic Constant of Rejection, captured the presence of clonally expanded, tumor-enriched T cell clones and outperformed conventional prognostic molecular biomarkers, such as the consensus molecular subtype and the microsatellite instability classifications. Quantification of genetic immunoediting, defined as a lower number of neoantigens than expected, further refined its prognostic value. We identified a microbiome signature, driven by Ruminococcus bromii, associated with a favorable outcome. By combining microbiome signature and Immunologic Constant of Rejection, we developed and validated a composite score (mICRoScore), which identifies a group of patients with excellent survival probability. The publicly available multi-omics dataset provides a resource for better understanding colon cancer biology that could facilitate the discovery of personalized therapeutic approaches.

Prognostic Mutational Signatures of NSCLC Patients treated with chemotherapy, immunotherapy and chemoimmunotherapy.

Different types of therapy are currently being used to treat non-small cell lung cancer (NSCLC) depending on the stage of tumor and the presence of potentially druggable mutations. However, few biomarkers are available to guide clinicians in selecting the most effective therapy for all patients with various genetic backgrounds. To examine whether patients' mutation profiles are associated with the response to a specific treatment, we collected comprehensive clinical characteristics and sequencing data from 524 patients with stage III and IV NSCLC treated at Atrium Health Wake Forest Baptist. Overall survival based Cox-proportional hazard regression models were applied to identify mutations that were "beneficial" (HR < 1) or "detrimental" (HR > 1) for patients treated with chemotherapy (chemo), immune checkpoint inhibitor (ICI) and chemo+ICI combination therapy (Chemo+ICI) followed by the generation of mutation composite scores (MCS) for each treatment. We also found that MCS is highly treatment specific that MCS derived from one treatment group failed to predict the response in others. Receiver operating characteristics (ROC) analyses showed a superior predictive power of MCS compared to TMB and PD-L1 status for immune therapy-treated patients. Mutation interaction analysis also identified novel co-occurring and mutually exclusive mutations in each treatment group. Our work highlights how patients' sequencing data facilitates the clinical selection of optimized treatment strategies.

Plasma Exosome Gene Signature Differentiates Colon Cancer from Healthy Controls.

BACKGROUND: Liquid biopsies have become an integral part of cancer management as minimally invasive options to detect molecular and genetic changes. However, current options show poor sensitivity in peritoneal carcinomatosis (PC). Novel exosome-based liquid biopsies may provide critical information on these challenging tumors. In this initial feasibility analysis, we identified an exosome gene signature of 445 genes (ExoSig445) from colon cancer patients, including those with PC, that is distinct from healthy controls. METHODS: Plasma exosomes from 42 patients with metastatic and non-metastatic colon cancer and 10 healthy controls were isolated and verified. RNAseq analysis of exosomal RNA was performed and differentially expressed genes (DEGs) were identified by the DESeq2 algorithm. The ability of RNA transcripts to discriminate control and cancer cases was assessed by principal component analysis (PCA) and Bayesian compound covariate predictor classification. An exosomal gene signature was compared with tumor expression profiles of The Cancer Genome Atlas. RESULTS: Unsupervised PCA using exosomal genes with greatest expression variance showed stark separation between controls and patient samples. Using separate training and test sets, gene classifiers were constructed capable of discriminating control and patient samples with 100% accuracy. Using a stringent statistical threshold, 445 DEGs fully delineated control from cancer samples. Furthermore, 58 of these exosomal DEGs were found to be overexpressed in colon tumors. CONCLUSIONS: Plasma exosomal RNAs can robustly discriminate colon cancer patients, including patients with PC, from healthy controls. ExoSig445 can potentially be developed as a highly sensitive liquid biopsy test in colon cancer.

Collagen deposition within brain metastases is associated with leptomeningeal failure after cavity-directed radiosurgery.

Background: Leptomeningeal failure (LMF) represents a devastating progression of disease following resection of brain metastases (BrM). We sought to identify a biomarker at time of BrM resection that predicts for LMF using mass spectrometry-based proteomic analysis of resected BrM and to translate this finding with histochemical assays. Methods: We retrospectively reviewed 39 patients with proteomic data available from resected BrM. We performed an unsupervised analysis with false discovery rate adjustment (FDR) to compare proteomic signature of BrM from patients that developed LMF versus those that did not. Based on proteomic analysis, we applied trichrome stain to a total of 55 patients who specifically underwent resection and adjuvant radiosurgery. We used competing risks regression to assess predictors of LMF. Results: Of 39 patients with proteomic data, FDR revealed type I collagen-alpha-1 (COL1A1, P = .045) was associated with LMF. The degree of trichrome stain in each block correlated with COL1A1 expression (ß = 1.849, P = .001). In a cohort of 55 patients, a higher degree of trichrome staining was associated with an increased hazard of LMF in resected BrM (Hazard Ratio 1.58, 95% CI 1.11-2.26, P = .01). Conclusion: The degree of trichrome staining correlated with COL1A1 and portended a higher risk of LMF in patients with resected brain metastases treated with adjuvant radiosurgery. Collagen deposition and degree of fibrosis may be able to serve as a biomarker for LMF.

Exosomal proteins as a source of biomarkers in colon cancer-derived peritoneal carcinomatosis - A pilot study.

PURPOSE: Peritoneal carcinomatosis (PC), metastasized from colorectal cancer (CRC), remains a highly lethal disease. Outcomes of PC is significantly influenced by the amount of intra-abdominal tumor burden and therefore diagnostic tests that facilitate earlier diagnosis could improve PC treatment and patient outcomes. EXPERIMENTAL DESIGN: Using mass-spectrometry-based proteomics, we characterized the protein features of circulating exosomes in the context of CRC PC, CRC with liver metastasis, and primary CRC limited to the colon. We profiled exosomes isolated from patient plasma to identify exosome-associated protein cargoes released by these cancer types. RESULTS: Analysis of the resulting data identified metastasis-specific exosome protein signatures. Bioinformatic analyses confirmed enrichment of proteins annotated to vesicle-associated processes and intracellular compartments, as well as representation of cancer hallmark functions and processes. CONCLUSION AND CLINICAL RELEVANCE: This research yielded distinct protein profiles for the CRC patient groups and suggests the utility of plasma exosome proteomic analysis for a better understanding of PC development and metastasis.

Targeting the CD47/thrombospondin-1 signaling axis regulates immune cell bioenergetics in the tumor microenvironment to potentiate antitumor immune response.

BACKGROUND: CD47 is an integral membrane protein that alters adaptive immunosurveillance when bound to the matricellular glycoprotein thrombospondin-1 (TSP1). We examined the impact of the CD47/TSP1 signaling axis on melanoma patient response to anti-PD-1 therapy due to alterations in T cell activation, proliferation, effector function, and bioenergetics. METHODS: A syngeneic B16 mouse melanoma model was performed to determine if targeting CD47 as monotherapy or in combination with anti-PD-1 impacted tumor burden. Cytotoxic (CD8+) T cells from Pmel-1 transgenic mice were used for T cell activation, cytotoxic T lymphocyte, and cellular bioenergetic assays. Single-cell RNA-sequencing, ELISA, and flow cytometry was performed on peripheral blood mononuclear cells and plasma of melanoma patients receiving anti-PD-1 therapy to examine CD47/TSP1 expression. RESULTS: Human malignant melanoma tissue had increased CD47 and TSP1 expression within the tumor microenvironment compared with benign tissue. Due to the negative implications CD47/TSP1 can have on antitumor immune responses, we targeted CD47 in a melanoma model and observed a decrease in tumor burden due to increased tumor oxygen saturation and granzyme B secreting CD8+ T cells compared with wild-type tumors. Additionally, Pmel-1 CD8+ T cells exposed to TSP1 had reduced activation, proliferation, and effector function against B16 melanoma cells. Targeting CD47 allowed CD8+ T cells to overcome this TSP1 interaction to sustain these functions. TSP1 exposed CD8+ T cells have a decreased rate of glycolysis; however, targeting CD47 restored glycolysis when CD8+ T cells were exposed to TSP1, suggesting CD47 mediated metabolic reprogramming of T cells. Additionally, non-responding patients to anti-PD-1 therapy had increased T cells expressing CD47 and circulating levels of TSP1 compared with responding patients. Since CD47/TSP1 signaling axis negatively impacts CD8+ T cells and non-responding patients to anti-PD-1 therapy have increased CD47/TSP1 expression, we targeted CD47 in combination with anti-PD-1 in a melanoma model. Targeting CD47 in combination with anti-PD-1 treatment further decreased tumor burden compared with monotherapy and control. CONCLUSION: CD47/TSP1 expression could serve as a marker to predict patient response to immune checkpoint blockade treatment, and targeting this pathway may preserve T cell activation, proliferation, effector function, and bioenergetics to reduce tumor burden as a monotherapy or in combination with anti-PD-1.

Prognostic attributes of immune signatures in soft tissue sarcomas show differential dependencies on tumor mutational burden.

BACKGROUND: Cellular and intrinsic markers of sarcoma immunogenicity are poorly understood. To gain insight into whether tumor-immune interactions correlate with clinical aggressiveness, the authors examined the prognostic significance of immune gene signatures in combination with tumor mutational burden (TMB) and cancer-testis antigen (CTA) expression. METHODS: RNA sequencing and clinical data of 259 soft tissue sarcomas from The Cancer Genome Atlas project were used to investigate associations between published immune gene signatures and patient overall survival (OS) in the contexts of TMB, as computed from whole-exome sequencing data, and CTA gene expression. Multivariate Cox proportional hazards regression models and log-rank tests were used to assess survival associations. RESULTS: Immune signature scores that reflected in part the intratumoral abundance of cytotoxic T cells showed significant positive associations with OS. However, the prognostic power of the T-cell signatures was highly dependent on TMB-high status, consistent with protective effects of tumor-infiltrating T cells in tumors with elevated antigenicity. In TMB-low tumors, a signature of infiltrating plasma B cells was significantly and positively associated with OS, independent of T-cell signature status. Although tumor subtypes based on differential expression patterns of CTA genes showed different survival associations within leiomyosarcoma and myxofibrosarcoma histologies, neither CTA nor histologic subtype interacted with the T-cell-survival association. CONCLUSIONS: Signatures of T-cell and plasma B-cell infiltrates were associated with a survival benefit in soft tissue sarcomas. TMB, but not CTA expression, influenced the prognostic power of T-cell-associated, but not plasma B-cell-associated, survival. LAY SUMMARY: Clinical data and RNA analysis of 259 soft tissue sarcomas from The Cancer Genome Atlas project were used to investigate associations between five published gene immune cell expression signatures and survival in the context of tumor mutations. Activated T cells had a significant positive association with patient survival. Although high tumor mutation burden was associated with good survival, the prognostic power of T-cell signatures was highly dependent on tumor mutational status, consistent with protective effects of tumor-infiltrating T cells in tumors with high levels of antigens. In low tumor mutation-bearing tumors, plasma B cells were positively associated with survival.

Circulating Immune Bioenergetic, Metabolic, and Genetic Signatures Predict Melanoma Patients' Response to Anti-PD-1 Immune Checkpoint Blockade.

PURPOSE: Immunotherapy with checkpoint inhibitors is improving the outcomes of several cancers. However, only a subset of patients respond. Therefore, predictive biomarkers are critically needed to guide treatment decisions and develop approaches to the treatment of therapeutic resistance. EXPERIMENTAL DESIGN: We compared bioenergetics of circulating immune cells and metabolomic profiles of plasma obtained at baseline from patients with melanoma treated with anti-PD-1 therapy. We also performed single-cell RNA sequencing (scRNAseq) to correlate transcriptional changes associated with metabolic changes observed in peripheral blood mononuclear cells (PBMC) and patient plasma. RESULTS: Pretreatment PBMC from responders had a higher reserve respiratory capacity and higher basal glycolytic activity compared with nonresponders. Metabolomic analysis revealed that responder and nonresponder patient samples cluster differently, suggesting differences in metabolic signatures at baseline. Differential levels of specific lipid, amino acid, and glycolytic pathway metabolites were observed by response. Further, scRNAseq analysis revealed upregulation of T-cell genes regulating glycolysis. Our analysis showed that SLC2A14 (Glut-14; a glucose transporter) was the most significant gene upregulated in responder patients' T-cell population. Flow cytometry analysis confirmed significantly elevated cell surface expression of the Glut-14 in CD3+, CD8+, and CD4+ circulating populations in responder patients. Moreover, LDHC was also upregulated in the responder population. CONCLUSIONS: Our results suggest a glycolytic signature characterizes checkpoint inhibitor responders; consistently, both ECAR and lactate-to-pyruvate ratio were significantly associated with overall survival. Together, these findings support the use of blood bioenergetics and metabolomics as predictive biomarkers of patient response to immune checkpoint inhibitor therapy.

Phase II trial of cytarabine and mitoxantrone with devimistat in acute myeloid leukemia.

Devimistat is a TCA cycle inhibitor. A previously completed phase I study of devimistat in combination with cytarabine and mitoxantrone in patients with relapsed or refractory AML showed promising response rates. Here we report the results of a single arm phase II study (NCT02484391). The primary outcome of feasibility of maintenance devimistat following induction and consolidation with devimistat in combination with high dose cytarabine and mitoxantrone was not met, as maintenance devimistat was only administered in 2 of 21 responders. The secondary outcomes of response (CR + CRi) and median survival were 44% (21/48) and 5.9 months respectively. There were no unexpected toxicities observed. An unplanned, post-hoc analysis of the phase I and II datasets suggests a trend of a dose response in older but not younger patients. RNA sequencing data from patient samples reveals an age-related decline in mitochondrial gene sets. Devimistat impairs ATP synthesis and we find a correlation between mitochondrial membrane potential and sensitivity to chemotherapy. Devimistat also induces mitochondrial reactive oxygen species and turnover consistent with mitophagy. We find that pharmacological or genetic inhibition of mitochondrial fission or autophagy sensitizes cells to devimistat. These findings suggest that an age related decline in mitochondrial quality and autophagy may be associated with response to devimistat however this needs to be confirmed in larger cohorts with proper trial design.

hDirect-MAP: projection-free single-cell modeling of response to checkpoint immunotherapy.

There is a lack of robust generalizable predictive biomarkers of response to immune checkpoint blockade in multiple types of cancer. We develop hDirect-MAP, an algorithm that maps T cells into a shared high-dimensional (HD) expression space of diverse T cell functional signatures in which cells group by the common T cell phenotypes rather than dimensional reduced features or a distorted view of these features. Using projection-free single-cell modeling, hDirect-MAP first removed a large group of cells that did not contribute to response and then clearly distinguished T cells into response-specific subpopulations that were defined by critical T cell functional markers of strong differential expression patterns. We found that these grouped cells cannot be distinguished by dimensional-reduction algorithms but are blended by diluted expression patterns. Moreover, these identified response-specific T cell subpopulations enabled a generalizable prediction by their HD metrics. Tested using five single-cell RNA-seq or mass cytometry datasets from basal cell carcinoma, squamous cell carcinoma and melanoma, hDirect-MAP demonstrated common response-specific T cell phenotypes that defined a generalizable and accurate predictive biomarker.

Intrapleural nano-immunotherapy promotes innate and adaptive immune responses to enhance anti-PD-L1 therapy for malignant pleural effusion.

Malignant pleural effusion (MPE) is indicative of terminal malignancy with a uniformly fatal prognosis. Often, two distinct compartments of tumour microenvironment, the effusion and disseminated pleural tumours, co-exist in the pleural cavity, presenting a major challenge for therapeutic interventions and drug delivery. Clinical evidence suggests that MPE comprises abundant tumour-associated myeloid cells with the tumour-promoting phenotype, impairing antitumour immunity. Here we developed a liposomal nanoparticle loaded with cyclic dinucleotide (LNP-CDN) for targeted activation of stimulators of interferon genes signalling in macrophages and dendritic cells and showed that, on intrapleural administration, they induce drastic changes in the transcriptional landscape in MPE, mitigating the immune cold MPE in both effusion and pleural tumours. Moreover, combination immunotherapy with blockade of programmed death ligand 1 potently reduced MPE volume and inhibited tumour growth not only in the pleural cavity but also in the lung parenchyma, conferring significantly prolonged survival of MPE-bearing mice. Furthermore, the LNP-CDN-induced immunological effects were also observed with clinical MPE samples, suggesting the potential of intrapleural LNP-CDN for clinical MPE immunotherapy.

Comprehensive gene cluster analysis of head and neck squamous cell carcinoma TCGA RNA-seq data defines B cell immunity-related genes as a robust survival predictor.

BACKGROUND: The authors aimed to define novel gene expression signatures that are associated with patients' survival with head and neck squamous cell carcinoma (HNSCC). METHODS: TCGA RNA-seq data were used for gene expression clusters extraction from 499 tumor samples by the "EPIG" method. Tumor samples were then partitioned into lower and higher than median level groups for survival relevant analysis by Kaplan-Meier estimator. RESULTS: We found that two gene clusters (_1, _2) are favorably, while two (_3, _4) are unfavorably, associated with patients' survival with HNSCC. Notably, most genes on the top lists of cluster_2 are associated with B cells. A gene expression signature with combined genes from cluster_2 and _4 was further determined to be associated with HNSCC survival rate. CONCLUSION: Our work strongly supported a favorable role of B cells in patients' survival with HNSCC and identified a novel coexpressed gene signature as prognostic biomarker for patients' survival with HNSCC estimation.