A Pathologically Friendly Strategy for Determining the Organ-specific Spatial Tumor Microenvironment Topology in Lung Adenocarcinoma Through the Integration of snRandom-seq and Imaging Mass Cytometry.

Heterogeneous organ-specific responses to immunotherapy exist in lung cancer. Dissecting tumor microenvironment (TME) can provide new insights into the mechanisms of divergent responses, the process of which remains poor, partly due to the challenges associated with single-cell profiling using formalin-fixed paraffin-embedded (FFPE) materials. In this study, single-cell nuclei RNA sequencing and imaging mass cytometry (IMC) are used to dissect organ-specific cellular and spatial TME based on FFPE samples from paired primary lung adenocarcinoma (LUAD) and metastases. Single-cell analyses of 84 294 cells from sequencing and 250 600 cells from IMC reveal divergent organ-specific immune niches. For sites of LUAD responding well to immunotherapy, including primary LUAD and adrenal gland metastases, a significant enrichment of B, plasma, and T cells is detected. Spatially resolved maps reveal cellular neighborhoods recapitulating functional units of the tumor ecosystem and the spatial proximity of B and CD4+ T cells at immunogenic sites. Various organ-specific densities of tertiary lymphoid structures are observed. Immunosuppressive sites, including brain and liver metastases, are deposited with collagen I, and T cells at these sites highly express TIM-3. This study originally deciphers the single-cell landscape of the organ-specific TME at both cellular and spatial levels for LUAD, indicating the necessity for organ-specific treatment approaches.

Pan-Cancer Single-Cell and Spatial-Resolved Profiling Reveals the Immunosuppressive Role of APOE+ Macrophages in Immune Checkpoint Inhibitor Therapy.

The heterogeneity of macrophages influences the response to immune checkpoint inhibitor (ICI) therapy. However, few studies explore the impact of APOE+ macrophages on ICI therapy using single-cell RNA sequencing (scRNA-seq) and machine learning methods. The scRNA-seq and bulk RNA-seq data are Integrated to construct an M.Sig model for predicting ICI response based on the distinct molecular signatures of macrophage and machine learning algorithms. Comprehensive single-cell analysis as well as in vivo and in vitro experiments are applied to explore the potential mechanisms of the APOE+ macrophage in affecting ICI response. The M.Sig model shows clear advantages in predicting the efficacy and prognosis of ICI therapy in pan-cancer patients. The proportion of APOE+ macrophages is higher in ICI non-responders of triple-negative breast cancer compared with responders, and the interaction and longer distance between APOE+ macrophages and CD8+ exhausted T (Tex) cells affecting ICI response is confirmed by multiplex immunohistochemistry. In a 4T1 tumor-bearing mice model, the APOE inhibitor combined with ICI treatment shows the best efficacy. The M.Sig model using real-world immunotherapy data accurately predicts the ICI response of pan-cancer, which may be associated with the interaction between APOE+ macrophages and CD8+ Tex cells.

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2+ macrophages, exhausted CD8+ T cells, tolerant CD8+ T cells, exhausted CD4+ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2+ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.

Nano-enhanced immunotherapy: Targeting the immunosuppressive tumor microenvironment.

The tumor microenvironment (TME), which is mostly composed of tumor cells, immune cells, signaling molecules, stromal tissue, and the vascular system, is an integrated system that is conducive to the formation of tumors. TME heterogeneity makes the response to immunotherapy different in different tumors, such as "immune-cold" and "immune-hot" tumors. Tumor-associated macrophages, myeloid-derived suppressor cells, and regulatory T cells are the major suppressive immune cells and their different phenotypes interact and influence cancer cells by secreting different signaling factors, thus playing a key role in the formation of the TME as well as in the initiation, growth, and metastasis of cancer cells. Nanotechnology development has facilitated overcoming the obstacles that limit the further development of conventional immunotherapy, such as toxic side effects and lack of targeting. In this review, we focus on the role of three major suppressive immune cells in the TME as well as in tumor development, clinical trials of different drugs targeting immune cells, and different attempts to combine drugs with nanomaterials. The aim is to reveal the relationship between immunotherapy, immunosuppressive TME and nanomedicine, thus laying the foundation for further development of immunotherapy.

Development of a whole-slide-level segmentation-based dMMR/pMMR deep learning detector for colorectal cancer.

To investigate whole-slide-level prediction in the field of artificial intelligence identification of dMMR/pMMR from hematoxylin and eosin (H&E) in colorectal cancer (CRC), we established a segmentation-based dMMR/pMMR deep learning detector (SPEED). Our model was approximately 1,700 times faster than that of the classification-based model. For the internal validation cohort, our model yielded an overall AUC of 0.989. For the external validation cohort, the model exhibited a high performance, with an AUC of 0.865. The human‒machine strategy further improved the model performance for external validation by an AUC up to 0.988. Our whole-slide-level prediction model provided an approach for dMMR/pMMR detection from H&E whole slide images with excellent predictive performance and less computer processing time in patients with CRC.

RUNX-3-expressing CAR T cells targeting glypican-3 in patients with heavily pretreated advanced hepatocellular carcinoma: a phase I trial.

Background: Glypican-3 (GPC3) is a well-characterized hepatocellular carcinoma (HCC)-associated antigen and a promising target for HCC treatment. CT017 CAR T cells were engineered to co-express CAR-GPC3 and runt-related transcription factor 3 (RUNX3), which triggers CD8+ T-cell infiltration into the cancer microenvironment. Methods: This single-center, single-arm, open-label, phase I clinical study enrolled heavily pretreated patients with GPC3-positive HCC between August 2019 and December 2020 (NCT03980288). Patients were treated with CT017 CAR T cells at a dose of 250 × 106 cells. The primary objective was to assess the safety and tolerability of this first-in-human product. Findings: Six patients received 7 infusions (one patient received 2 infusions) at the 250 × 106 cells dose. Three patients received CT017 monotherapy, and three patients received CT017-tyrosine kinase inhibitor (TKI) combination therapy at the first infusion. One patient received CT017-TKI combination therapy at the second infusion after CT017 monotherapy. All patients experienced cytokine release syndrome (CRS), with 50% (3/6) at Grade 2, 50% (3/6) at Grade 3, and all events resolved after treatment. No immune effector cell-associated neurotoxicity syndrome was observed. Dose escalation was not performed due to the investigator's decision regarding safety. Of six evaluable patients, one achieved partial response and two had stable disease for a 16.7% objective response rate, 50% disease control rate, 3.5-month median progression-free survival, 3.2-month median duration of disease control, and 7.9-month median overall survival (OS) with 7.87-month median follow-up. The longest OS was 18.2 months after CT017 infusion. Interpretation: Current preliminary phase I data showed a manageable safety profile and promising antitumor activities of CT017 for patients with advanced HCC. These results need to be confirmed in a robust clinical trial. Funding: This study was funded by CARsgen Therapeutics Co., Ltd.

Biocompatible Snowman-like Dimer Nanoparticles for Improved Cellular Uptake in Intrahepatic Cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (ICC) is one of the most aggressive types of human cancers. Although paclitaxel (PTX) was proven to exert potent anti-tumor effects against ICC, the delivery of PTX is still challenging due to its hydrophobic property. Nanoparticle (NP)-based carriers have been proven to be effective drug delivery vehicles. Among their physicochemical properties, the shape of NPs plays a crucial role in their performance of cellular internalization and thus anti-tumor efficacy of loaded drugs. In this study, dumbbell-like and snowman-like dimer NPs, composed of a polylactic acid (PLA) bulb and a shellac bulb, were designed and prepared as drug nanocarriers to enhance the efficiency of cellular uptake and anti-tumor performance. PLA/shellac dimer NPs prepared through rapid solvent exchange and controlled co-precipitation are biocompatible and their shape could flexibly be tuned by adjusting the concentration ratio of shellac to PLA. Drug-loaded snowman-like PLA/shellac dimer NPs with a sharp shape exhibit the highest cellular uptake and best cell-killing ability against cancer cells in an in vitro ICC model over traditional spherical NPs and dumbbell-like dimer NPs, as proven with the measurements of flow cytometry, fluorescent confocal microscopy, and the CCK8 assay. The underlying mechanism may be attributed to the lower surface energy required for the smaller bulbs of snowman-like PLA/shellac dimer NPs to make the initial contact with the cell membrane, which facilitates the subsequent penetration through the cellular membrane. Therefore, these dimer NPs provide a versatile platform to tune the shape of NPs and develop innovative drug nanocarriers that hold great promise to enhance cellular uptake and therapeutic efficacy.

Induction of Tumor Ferroptosis-Dependent Immunity via an Injectable Attractive Pickering Emulsion Gel.

The combination of ferroptosis inducers and immune checkpoint blockade can enhance antitumor effects. However, the efficacy in tumors with low immunogenicity requires further investigation. In this work, a water-in-oil Pickering emulsion gel is developed to deliver (1S, 3R)-RSL-3 (RSL-3), a ferroptosis inducer dissolved in iodized oil, and programmed death-1 (PD-1) antibody, the most commonly used immune checkpoint inhibitor dissolved in water, with optimal characteristics (RSL-3 + PD-1@gel). Tumor lipase degrades the continuous oil phase, which results in the slow release of RSL-3 and PD-1 antibody and a notable antitumor effect against low-immunogenic hepatocellular carcinoma and pancreatic cancer. Intriguingly, the RSL-3 + PD-1@gel induces ferroptosis of tumor cells, resulting in antitumor immune response via accumulation of helper T lymphocyte cells and cytotoxic T cells. Additionally, the single-cell sequence profiling analysis during tumor treatment reveals the induction of ferroptosis in tumor cells together with strong antitumor immune response in ascites.

An immunometabolism subtyping system identifies S100A9+ macrophage as an immune therapeutic target in colorectal cancer based on multiomics analysis.

Immunometabolism in the tumor microenvironment (TME) and its influence on the immunotherapy response remain uncertain in colorectal cancer (CRC). We perform immunometabolism subtyping (IMS) on CRC patients in the training and validation cohorts. Three IMS subtypes of CRC, namely, C1, C2, and C3, are identified with distinct immune phenotypes and metabolic properties. The C3 subtype exhibits the poorest prognosis in both the training cohort and the in-house validation cohort. The single-cell transcriptome reveals that a S100A9+ macrophage population contributes to the immunosuppressive TME in C3. The dysfunctional immunotherapy response in the C3 subtype can be reversed by combination treatment with PD-1 blockade and an S100A9 inhibitor tasquinimod. Taken together, we develop an IMS system and identify an immune tolerant C3 subtype that exhibits the poorest prognosis. A multiomics-guided combination strategy by PD-1 blockade and tasquinimod improves responses to immunotherapy by depleting S100A9+ macrophages in vivo.

Oxaliplatin plus irinotecan vs irinotecan as second-line treatment in pancreatic cancer patients: a randomized-controlled open-label Phase II study.

Background: Limited second-line therapeutic options are available for metastasis pancreatic cancer (mPC). We aimed to explore the efficacy and safety of oxaliplatin plus irinotecan (IROX) in mPC patients. Methods: This is an open-label, Phase 2, randomized study of mPC patients (aged 18-75 years) who failed when using gemcitabine plus S-1 as first-line therapy. Block randomization with a block size of four was used to randomly assign patients (1:1) between October 2015 and December 2017 to receive either IROX (oxaliplatin 85 mg/m2 and irinotecan 160 mg/m2) or irinotecan monotherapy (irinotecan 180 mg/m2) until disease progression, unacceptable adverse events, or consent withdrawal. The primary end point was overall survival, and the secondary end points were progression-free survival, overall response rate, and adverse event rate. Results: A total of 74 patients were enrolled in this study, including 44 males and 30 females, with an average age of 61 years. The median overall survival was 10.2 and 6.7 months (adjusted hazard ratio [HR], 0.7; 95% confidence interval [CI], 0.4-1.2; P = 0.20) and the median progression-free survival was 5.1 and 2.3 months (adjusted HR, 0.4; 95% CI, 0.2-0.6; P < 0.01) in the IROX group and irinotecan group, respectively. The overall response rates were 18.4% (7/38) in the IROX group and 5.5% (2/36) in the irinotecan group (P = 0.06). Grade 3-4 adverse events occurred in 34% (13/38) of patients in the IROX group and 19% (7/36) of patients in the irinotecan group (P = 0.15). Conclusions: IROX had no significant survival benefit over irinotecan monotherapy in our study. However, IROX reduced the risk of disease progression by 60%, with acceptable toxicity.

Posttreatment with dexmedetomidine aggravates LPS-induced myocardial dysfunction partly via activating cardiac endothelial α2A-AR in mice.

BACKGROUND: Dexmedetomidine (DEX) administered before or at 30 min after sepsis induction was reported to alleviate septic cardiomyopathy in experimental models. However, sepsis is a life-threatening organ dysfunction due to infection-induced dysregulated host response, whether DEX treatment in the presence of organ dysfunction affects septic cardiomyopathy is unknown. This study investigated the effect of DEX posttreatment on septic cardiomyopathy. METHODS: Male wild-type and α2A-adrenergic receptor (AR) knockout mice were exposed to lipopolysaccharide (LPS) or cecal ligation puncture (CLP), and cultured cardiac endothelial cells were used. Mouse survival, myocardial function, inflammatory response and related signaling pathways were determined. RESULTS: DEX treatment at 6, 9 h after LPS challenge significantly reduced survival rate of LPS-challenged mice, especially at 9 h. DEX administered at 9 h after LPS injection or CLP significantly reduced survival in LPS or CLP-induced sepsis in wild-type mice, but not in α2A-AR knockout mice. LPS treatment for 20 h decreased the left ventricle + dp/dt, increased myocardial interleukin (IL)-1ß and IL-6 concentrations as well as cardiac endothelial tumor necrosis factor (TNF)-α, vascular cell adhesion molecule-1 (VCAM-1) and ICAM-1 expression, which were enhanced by DEX treated at 9 h after LPS injection in wild-type mice, but not in α2A-AR knockout mice. Furthermore, DEX posttreatment increased p38 phosphorylation, c-Fos nuclear translocation and VCAM-1 expression in LPS-treated cardiac endothelial cells, which were eliminated by α2A-AR knockout or PKC inhibitor. CONCLUSIONS: DEX posttreatment aggravates LPS-induced cardiac inflammation and myocardial dysfunction, at least in part, via activating cardiac endothelial α2A-AR-mediated PKC signal pathway.

Development and validation of a meta-learning-based multi-modal deep learning algorithm for detection of peritoneal metastasis.

PURPOSE: The existing medical imaging tools have a detection accuracy of 97% for peritoneal metastasis(PM) bigger than 0.5 cm, but only 29% for that smaller than 0.5 cm, the early detection of PM is still a difficult problem. This study is aiming at constructing a deep convolution neural network classifier based on meta-learning to predict PM. METHOD: Peritoneal metastases are delineated on enhanced CT. The model is trained based on meta-learning, and features are extracted using multi-modal deep Convolutional Neural Network(CNN) with enhanced CT to classify PM. Besides, we evaluate the performance on the test dataset, and compare it with other PM prediction algorithm. RESULTS: The training datasets are consisted of 9574 images from 43 patients with PM and 67 patients without PM. The testing datasets are consisted of 1834 images from 21 testing patients. To increase the accuracy of the prediction, we combine the multi-modal inputs of plain scan phase, portal venous phase and arterial phase to build a meta-learning-based multi-modal PM predictor. The classifier shows an accuracy of 87.5% with Area Under Curve(AUC) of 0.877, sensitivity of 73.4%, specificity of 95.2% on the testing datasets. The performance is superior to routine PM classify based on logistic regression (AUC: 0.795), a deep learning method named ResNet3D (AUC: 0.827), and a domain generalization (DG) method named MADDG (AUC: 0.834). CONCLUSIONS: we proposed a novel training strategy based on meta-learning to improve the model's robustness to "unseen" samples. The experiments shows that our meta-learning-based multi-modal PM predicting classifier obtain more competitive results in synchronous PM prediction compared to existing algorithms and the model's improvements of generalization ability even with limited data.

Molecular Subgroups of Intrahepatic Cholangiocarcinoma Discovered by Single-Cell RNA Sequencing-Assisted Multiomics Analysis.

Intrahepatic cholangiocarcinoma (ICC) is a relatively rare but highly aggressive tumor type that responds poorly to chemotherapy and immunotherapy. Comprehensive molecular characterization of ICC is essential for the development of novel therapeutics. Here, we constructed two independent cohorts from two clinic centers. A comprehensive multiomics analysis of ICC via proteomic, whole-exome sequencing (WES), and single-cell RNA sequencing (scRNA-seq) was performed. Novel ICC tumor subtypes were derived in the training cohort (n = 110) using proteomic signatures and their associated activated pathways, which were further validated in a validation cohort (n = 41). Three molecular subtypes, chromatin remodeling, metabolism, and chronic inflammation, with distinct prognoses in ICC were identified. The chronic inflammation subtype was associated with a poor prognosis. Our random forest algorithm revealed that mutation of lysine methyltransferase 2D (KMT2D) frequently occurred in the metabolism subtype and was associated with lower inflammatory activity. scRNA-seq further identified an APOE+C1QB+ macrophage subtype, which showed the capacity to reshape the chronic inflammation subtype and contribute to a poor prognosis in ICC. Altogether, with single-cell transcriptome-assisted multiomics analysis, we identified novel molecular subtypes of ICC and validated APOE+C1QB+ tumor-associated macrophages as potential immunotherapy targets against ICC.

Microparticles: biogenesis, characteristics and intervention therapy for cancers in preclinical and clinical research.

Extracellular vesicles (EVs), spherical biological vesicles, mainly contain nucleic acids, proteins, lipids and metabolites for biological information transfer between cells. Microparticles (MPs), a subtype of EVs, directly emerge from plasma membranes, and have gained interest in recent years. Specific cell stimulation conditions, such as ultraviolet and X-rays irradiation, can induce the release of MPs, which are endowed with unique antitumor functionalities, either for therapeutic vaccines or as direct antitumor agents. Moreover, the size of MPs (100-1000 nm) and their spherical structures surrounded by a lipid bilayer membrane allow MPs to function as delivery vectors for bioactive antitumor compounds, with favorable phamacokinetic behavior, immunostimulatory activity and biological function, without inherent carrier-specific toxic side effects. In this review, the mechanisms underlying MP biogenesis, factors that influence MP production, properties of MP membranes, size, composition and isolation methods of MPs are discussed. Additionally, the applications and mechanisms of action of MPs, as well as the main hurdles for their applications in cancer management, are introduced.

Construction of TME and Identification of crosstalk between malignant cells and macrophages by SPP1 in hepatocellular carcinoma.

Liver cancer accounts for 6% of all malignancies causing death worldwide, and hepatocellular carcinoma (HCC) is the most common histological type. HCC is a heterogeneous cancer, but how the tumour microenvironment (TME) of HCC contributes to the progression of HCC remains unclear. In this study, we investigated the immune microenvironment by multiomics analysis. The tumour immune infiltration characteristics of HCC were determined at the genomic, epigenetic, bulk transcriptome and single-cell levels by data from The Cancer Genome Atlas portal and the Gene Expression Omnibus (GEO). An epigenetic immune-related scoring system (EIRS) was developed to stratify patients with poor prognosis. SPP1, one gene in the EIRS system, was identified as an immune-related predictor of poor survival in HCC patients. Through receptor-ligand pair analysis in single-cell RNA-seq, SPP1 was indicated to mediate the crosstalk between HCC cells and macrophages via SPP1-CD44 and SPP1-PTGER4 association. In vitro experiments further validate SPP1 can trigger the polarization of macrophages to M2-phenotype tumour-associated macrophages (TAMs).

Targeting senescence-like fibroblasts radiosensitizes non-small cell lung cancer and reduces radiation-induced pulmonary fibrosis.

Cancer cell radioresistance is the primary cause of the decreased curability of non-small cell lung cancer (NSCLC) observed in patients receiving definitive radiotherapy (RT). Following RT, a set of microenvironmental stress responses is triggered, including cell senescence. However, cell senescence is often ignored in designing effective strategies to resolve cancer cell radioresistance. Herein, we identify the senescence-like characteristics of cancer-associated fibroblasts (CAFs) after RT and clarify the formidable ability of senescence-like CAFs in promoting NSCLC cell proliferation and radioresistance through the JAK/STAT pathway. Specific induction of senescence-like CAF apoptosis using FOXO4-DRI, a FOXO4-p53-interfering peptide, resulted in remarkable effects on radiosensitizing NSCLC cells in vitro and in vivo. In addition, in this study, we also uncovered an obvious therapeutic effect of FOXO4-DRI on alleviating radiation-induced pulmonary fibrosis (RIPF) by targeting senescence-like fibroblasts in vivo. In conclusion, by targeting senescence, we offer a strategy that simultaneously decreases radioresistance of NSCLC and the incidence of RIPF.

The Long-term Effect of Dobutamine on Intrinsic Myocardial Function and Myocardial Injury in Septic Rats with Myocardial Dysfunction.

ABSTRACT: Dobutamine (DOB) is recommended as an inotrope for septic patients with low cardiac output, but its long-term impact on sepsis-induced cardiomyopathy remains unclear. This study investigated the long-term effect of DOB on septic myocardial dysfunction and injury. Rats were exposed to cecal ligation and puncture (CLP), the intrinsic myocardial function, other organ functions, hemodynamics, inflammatory response, serum myocardial injury biomarkers, myocardial apoptosis, and vascular permeability were determined. At 6 h after CLP, the left ventricular ±dP/dt were significantly depressed, cardiac tumor necrosis factor-α and vascular cell adhesion molecule-1 expression were increased, but not serum cardiac troponin I (cTnI), N-terminal pro-brain natriuretic peptide (NT-proBNP), heart-type fatty acid-binding protein (H-FABP), creatinine, and urea nitrogen concentrations in CLP group compared with controls. At 9 h after CLP, hepatic dysfunction was present in CLP rats compared with controls. At 6 h after CLP, DOB treatment did not affect hemodynamics, the left ventricular ±dP/dt, cytokine levels in serum and myocardium, as well as cardiomyocyte apoptosis and cardiac vascular hyperpermeability at 20 h after CLP. However, DOB (10.0 µg/kg) increased serum IL-10 level and improved survival in septic rats. These results indicate that the intrinsic myocardial depression occurs earlier than hepatic and renal dysfunction in sepsis and serum cTnI, NT-proBNP, and H-FABP are not suitable as early biomarkers for sepsis-induced myocardial dysfunction. Although DOB treatment (10.0 µg/kg) in the presence of myocardial dysfunction improves survival in septic rats, it neither improves myocardial function and hemodynamics nor attenuates myocardial injury at the later stage of sepsis.

Immunotherapy for targeting cancer stem cells in hepatocellular carcinoma.

The rapid development and remarkable success of checkpoint inhibitors have provided significant breakthroughs in cancer treatment, including hepatocellular carcinoma (HCC). However, only 15-20% of HCC patients can benefit from checkpoint inhibitors. Cancer stem cells (CSCs) are responsible for recurrence, metastasis, and local and systemic therapy resistance in HCC. Accumulating evidence has suggested that HCC CSCs can create an immunosuppressive microenvironment through certain intrinsic and extrinsic mechanisms, resulting in immune evasion. Intrinsic evasion mechanisms mainly include activation of immune-related CSC signaling pathways, low-level expression of antigen presenting molecules, and high-level expression of immunosuppressive molecules. External evasion mechanisms are mainly related to HBV/HCV infection, alcoholic/nonalcoholic steatohepatitis, hypoxia stimulation, abnormal angiogenesis, and crosstalk between CSCs and immune cells. A better understanding of the complex mechanisms of CSCs involved in immune evasion will contribute to therapies for HCC. Here we will outline the detailed mechanisms of immune evasion for CSCs, and provide an overview of the current immunotherapies targeting CSCs in HCC.

Analysis of the molecular nature associated with microsatellite status in colon cancer identifies clinical implications for immunotherapy.

BACKGROUND: Microsatellite instability in colon cancer implies favorable therapeutic outcomes after checkpoint blockade immunotherapy. However, the molecular nature of microsatellite instability is not well elucidated. METHODS: We examined the immune microenvironment of colon cancer using assessments of the bulk transcriptome and the single-cell transcriptome focusing on molecular nature of microsatellite stability (MSS) and microsatellite instability (MSI) in colorectal cancer from a public database. The association of the mutation pattern and microsatellite status was analyzed by a random forest algorithm in The Cancer Genome Atlas (TCGA) and validated by our in-house dataset (39 tumor mutational burden (TMB)-low MSS colon cancer, 10 TMB-high MSS colon cancer, 15 MSI colon cancer). A prognostic model was constructed to predict the survival potential and stratify microsatellite status by a neural network. RESULTS: Despite the hostile CD8+ cytotoxic T lymphocyte (CTL)/Th1 microenvironment in MSI colon cancer, a high percentage of exhausted CD8+ T cells and upregulated expression of immune checkpoints were identified in MSI colon cancer at the single-cell level, indicating the potential neutralizing effect of cytotoxic T-cell activity by exhausted T-cell status. A more homogeneous highly expressed pattern of PD1 was observed in CD8+ T cells from MSI colon cancer; however, a small subgroup of CD8+ T cells with high expression of checkpoint molecules was identified in MSS patients. A random forest algorithm predicted important mutations that were associated with MSI status in the TCGA colon cancer cohort, and our in-house cohort validated higher frequencies of BRAF, ARID1A, RNF43, and KM2B mutations in MSI colon cancer. A robust microsatellite status-related gene signature was built to predict the prognosis and differentiate between MSI and MSS tumors. A neural network using the expression profile of the microsatellite status-related gene signature was constructed. A receiver operating characteristic curve was used to evaluate the accuracy rate of neural network, reaching 100%. CONCLUSION: Our analysis unraveled the difference in the molecular nature and genomic variance in MSI and MSS colon cancer. The microsatellite status-related gene signature is better at predicting the prognosis of patients with colon cancer and response to the combination of immune checkpoint inhibitor-based immunotherapy and anti-VEGF therapy.

USP7 targeting modulates anti-tumor immune response by reprogramming Tumor-associated Macrophages in Lung Cancer.

Background: Tumor associated macrophages (TAMs) have strong plasticity and if reprogrammed, can clear tumor cells and regulate the adaptive immune system for cancer immunotherapy. Deubiquitinating enzymes (DUBs), which can remove ubiquitin (Ub) from Ub-modified substrates, have been associated with oncogenic metabolism but are not well-known for regulating TAMs repolarization. Methods: The expression of DUB related genes in macrophages (MΦs) was detected by reverse transcription-PCR. Flow cytometry and immunofluorescence were used to detect the changes of immune cells in the tumor microenvironment and spleen, including M1 (CD11b+F4/80+CD86+CD206-), and M2 (CD11b+F4/80+CD86-CD206+) MΦs, and IFN-γ+CD8+T cells. A proliferation assay was used to determine the effect of M2 MΦs treated with a USP7 inhibitor on T cell proliferation. Western blotting was used to detect the expression of USP7 and the activation of the MAPK pathway. The TGCA database was used to assess the role of USP7 in the immune microenvironment of human lung adenocarcinoma (LUAD). Results: 51 DUB genes were screened and USP7 was identified as a highly expressed gene in M2 but not M1 MΦs. Specific silencing of USP7 using siRNA or USP7 inhibitors led to phenotypical and functional changes in M2 MΦs, favoring CD8+T cells proliferation in vitro. USP7 inhibitors delayed tumor growth in mice with Lewis lung carcinoma, and promoted tumor infiltration of M1 MΦs and IFN-γ+CD8+T cells. Depletion of TAMs attenuated these therapeutic effects. USP7 inhibition was shown to mediate MΦs reprogramming by activating the p38 MAPK pathway. Administration of USP7 inhibitors increased the expression of programmed cell death ligand 1 (PD-L1) in tumors, while blocking programmed cell death protein 1 (PD-1) provided an effective anti-tumor response. Clinical databases suggest that high expression of USP7 in LUAD was negatively correlated with innate and adaptive immunity. Conclusions: Taken together, these results provide evidence to suggest that therapeutic approaches targeting USP7, in combination with immunotherapy, should be considered for lung cancer treatment.