Identifying gene expression programs in single-cell RNA-seq data using linear correlation explanation.

OBJECTIVE: Gene expression analysis through single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of gene regulation in diverse cell types, tissues, and organisms. While existing methods primarily focus on identifying cell type-specific gene expression programs (GEPs), the characterization of GEPs associated with biological processes and stimuli responses remains limited. In this study, we aim to infer biologically meaningful GEPs that are associated with both cellular phenotypes and activity programs directly from scRNA-seq data. METHODS: We applied linear CorEx, a machine-learning-based approach, to infer GEPs by grouping genes based on total correlation optimization function in simulated and real-world scRNA-seq datasets. Additionally, we utilized a transfer learning approach to project CorEx-inferred GEPs to other scRNA-seq datasets. RESULTS: By leveraging total correlation optimization, linear CorEx groups genes and demonstrates superior performance in identifying cell types and activity programs compared to similar methods using simulated data. Furthermore, we apply this same approach to real-world scRNA-seq data from the mouse dentate gyrus and embryonic colon development, uncovering biologically relevant GEPs related to cell types, developmental ages, and cell cycle programs. We also demonstrate the potential for transfer learning by evaluating similar datasets, showcasing the cross-species sensitivity of linear CorEx. CONCLUSION: Our findings validate linear CorEx as a valuable tool for comprehensively analyzing complex signals in scRNA-seq data, leading to deeper insights into gene expression dynamics, cellular heterogeneity, and regulatory mechanisms.

Pigs: Large Animal Preclinical Cancer Models.

Pigs are playing an increasingly vital role as translational biomedical models for studying human pathophysiology. The annotation of the pig genome was a huge step forward in translatability of pigs as a biomedical model for various human diseases. Similarities between humans and pigs in terms of anatomy, physiology, genetics, and immunology have allowed pigs to become a comprehensive preclinical model for human diseases. With a diverse range, from craniofacial and ophthalmology to reproduction, wound healing, musculoskeletal, and cancer, pigs have provided a seminal understanding of human pathophysiology. This review focuses on the current research using pigs as preclinical models for cancer research and highlights the strengths and opportunities for studying various human cancers.

Circulating Tumor Cells: How Far Have We Come with Mining These Seeds of Metastasis?

Circulating tumor cells (CTCs) are cancer cells that slough off from the tumor and circulate in the peripheral blood and lymphatic system as micro metastases that eventually results in macro metastases. Through a simple blood draw, sensitive CTC detection from clinical samples has proven to be a useful tool for determining the prognosis of cancer. Recent technological developments now make it possible to detect CTCs reliably and repeatedly from a simple and straightforward blood test. Multicenter trials to assess the clinical value of CTCs have demonstrated the prognostic value of these cancer cells. Studies on CTCs have filled huge knowledge gap in understanding the process of metastasis since their identification in the late 19th century. However, these rare cancer cells have not been regularly used to tailor precision medicine and or identify novel druggable targets. In this review, we have attempted to summarize the milestones of CTC-based research from the time of identification to molecular characterization. Additionally, the need for a paradigm shift in dissecting these seeds of metastasis and the possible future avenues to improve CTC-based discoveries are also discussed.

Benefits and opportunities of the transgenic Oncopig cancer model.

Cancer remains a leading cause of morbidity and mortality, and a paradigm shift is needed to fundamentally revisit drug development efforts. Pigs share close similarities to humans and may serve as an alternative model. Recently, a transgenic 'Oncopig' line has been generated to induce solid tumors with organ specificity, opening the potential of Oncopigs as a platform for developing novel therapeutic regimens.

Red cabbage juice-mediated gut microbiota modulation improves intestinal epithelial homeostasis and ameliorates colitis.

Gut microbiota plays a crucial role in inflammatory bowel disease (IBD) and has therapeutic benefits. Thus, targeting the gut microbiota is a promising therapeutic approach for IBD treatment. We recently found that red cabbage juice (RCJ) ameliorates dextran sulfate sodium (DSS)-induced colitis in mice. However, the underlying mechanisms remain unknown. The current study investigated the modulation of gut microbiota in response to treatment with RCJ to ameliorate the DSS colitis. The initial results demonstrated that mice treated with DSS + RCJ showed increased body weight and decreased diarrhea and blood in feces compared to the DSS alone group. RCJ ameliorated colitis by regulating the intestinal barrier function by reducing the number of apoptotic cells, improving colonic protective mucin, and increasing tight junction protein in RCJ + DSS groups compared to the DSS group. Short-gun metagenomic analysis revealed significant enrichment of short-chain fatty acid (SCFAs)-producing bacteria (Butyrivibrio, Ruminococcaceae, Acetatifactor muris, Rosburia Sp. CAG:303 , Dorea Sp. 5-2) increased PPAR-© activation, leading to repression of the nuclear factor κB (NFκB) signaling pathway, thus decreasing the production of crucial inflammatory cytokines and chemokines in the RCJ + DSS groups compared to the DSS group. Pathway abundance analysis showed an increased abundance of the SCFA pathway, reduced histidine degradation ( Bacteroides sartorii, and Bacteroides caecimuris ), and LCFA production in the RCJ+DSS treated group, suggesting the promotion of good colonic health. Furthermore, increased T-reg (FOXP3+) cells in the colon were due to SCFAs produced by the gut microbiota, which was corroborated by an increase in IL-10, a vital anti-inflammatory cytokine. Thus, our study provides the first evidence that RCJ ameliorates colonic inflammation by modulating the gut microbiota.

Integrated "lab-on-a-chip" microfluidic systems for isolation, enrichment, and analysis of cancer biomarkers.

The liquid biopsy has garnered considerable attention as a complementary clinical tool for the early detection, molecular characterization and monitoring of cancer over the past decade. In contrast to traditional solid biopsy techniques, liquid biopsy offers a less invasive and safer alternative for routine cancer screening. Recent advances in microfluidic technologies have enabled handling of liquid biopsy-derived biomarkers with high sensitivity, throughput, and convenience. The integration of these multi-functional microfluidic technologies into a 'lab-on-a-chip' offers a powerful solution for processing and analyzing samples on a single platform, thereby reducing the complexity, bio-analyte loss and cross-contamination associated with multiple handling and transfer steps in more conventional benchtop workflows. This review critically addresses recent developments in integrated microfluidic technologies for cancer detection, highlighting isolation, enrichment, and analysis strategies for three important sub-types of cancer biomarkers: circulating tumor cells, circulating tumor DNA and exosomes. We first discuss the unique characteristics and advantages of the various lab-on-a-chip technologies developed to operate on each biomarker subtype. This is then followed by a discussion on the challenges and opportunities in the field of integrated systems for cancer detection. Ultimately, integrated microfluidic platforms form the core of a new class of point-of-care diagnostic tools by virtue of their ease-of-operation, portability and high sensitivity. Widespread availability of such tools could potentially result in more frequent and convenient screening for early signs of cancer at clinical labs or primary care offices.

Understanding common key indicators of successful and unsuccessful cancer drug trials using a contrast mining framework on ClinicalTrials.gov.

Clinical trials are essential to the process of new drug development. As clinical trials involve significant investments of time and money, it is crucial for trial designers to carefully investigate trial settings prior to designing a trial. Utilizing trial documents from ClinicalTrials.gov, we aim to understand the common characteristics of successful and unsuccessful cancer drug trials to provide insights about what to learn and what to avoid. In this research, we first computationally classified cancer drug trials into successful and unsuccessful cases and then utilized natural language processing to extract eligibility criteria information from the trial documents. To provide explainable and potentially modifiable recommendations for new trial design, contrast mining was applied to discoverhighly contrasted patterns with a significant difference in prevalence between successful (completion with advancement to the next phase) and unsuccessful (suspended, withdrawn, or terminated) groups. Our method identified contrast patterns consisting of combinations of drug categories, eligibility criteria, study organization, and study design for nine major cancers. In addition to a literature review for the qualitative validation of mined contrast patterns, we found that contrast-pattern-based classifiers using the top 200 contrast patterns as feature representations can achieve approximately 80% F1 score for eight out of ten cancer types in our experiments. In summary, aligning with the modernization efforts of ClinicalTrials.gov, our study demonstrates that understanding the contrast characteristics of successful and unsuccessful cancer trials may provide insights into the decision-making process for trial investigators and therefore facilitate improved cancer drug trial design.

Preclinical models to study patient-derived circulating tumor cells and metastasis.

Circulating tumor cells (CTCs) that are detached from the tumor can be precursors of metastasis. The majority of studies focus on enumeration of CTCs from patient blood to predict recurrence and therapy outcomes. Very few studies have managed to expand CTCs to investigate their functional dynamics with respect to genetic changes, tumorigenic potential, and response to drug treatment. A growing amount of evidence based on successful CTC expansion has revealed novel therapeutic targets that are associated with the process of metastasis. In this review, we summarize the successes, challenges, and limitations that collectively contribute to the better understanding of metastasis using patient-derived CTCs as blood-borne seeds of metastasis. The roadblocks and future avenues to move CTC-based scientific discoveries forward are also discussed.

Western diet contributes to the pathogenesis of non-alcoholic steatohepatitis in male mice via remodeling gut microbiota and increasing production of 2-oleoylglycerol.

The interplay between western diet and gut microbiota drives the development of non-alcoholic fatty liver disease and its progression to non-alcoholic steatohepatitis. However, the specific microbial and metabolic mediators contributing to non-alcoholic steatohepatitis remain to be identified. Here, a choline-low high-fat and high-sugar diet, representing a typical western diet, named CL-HFS, successfully induces male mouse non-alcoholic steatohepatitis with some features of the human disease, such as hepatic inflammation, steatosis, and fibrosis. Metataxonomic and metabolomic studies identify Blautia producta and 2-oleoylglycerol as clinically relevant bacterial and metabolic mediators contributing to CL-HFS-induced non-alcoholic steatohepatitis. In vivo studies validate that both Blautia producta and 2-oleoylglycerol promote liver inflammation and hepatic fibrosis in normal diet- or CL-HFS-fed mice. Cellular and molecular studies reveal that the GPR119/TAK1/NF-κB/TGF-ß1 signaling pathway mediates 2-oleoylglycerol-induced macrophage priming and subsequent hepatic stellate cell activation. These findings advance our understanding of non-alcoholic steatohepatitis pathogenesis and provide targets for developing microbiome/metabolite-based therapeutic strategies against non-alcoholic steatohepatitis.

Red Cabbage Juice-Mediated Gut Microbiota Modulation Improves Intestinal Epithelial Homeostasis and Ameliorates Colitis.

Gut microbiota plays a crucial role in inflammatory bowel diseases (IBD) and can potentially prevent IBD through microbial-derived metabolites, making it a promising therapeutic avenue. Recent evidence suggests that despite an unclear underlying mechanism, red cabbage juice (RCJ) alleviates Dextran Sodium Sulfate (DSS)-induced colitis in mice. Thus, the study aims to unravel the molecular mechanism by which RCJ modulates the gut microbiota to alleviate DSS-induced colitis in mice. Using C57BL/6J mice, we evaluated RCJ's protective role in DSS-induced colitis through two cycles of 3% DSS. Mice were daily gavaged with PBS or RCJ until the endpoint, and gut microbiota composition was analyzed via shotgun metagenomics. RCJ treatment significantly improved body weight (p ≤ 0.001), survival in mice (p < 0.001) and reduced disease activity index (DAI) scores. Further, RCJ improved colonic barrier integrity by enhancing the expression of protective colonic mucins (p < 0.001) and tight junction proteins (p ≤ 0.01) in RCJ + DSS-treated mice compared to the DSS group. Shotgun metagenomic analysis revealed an enrichment of short-chain fatty acids (SCFAs)-producing bacteria (p < 0.05), leading to increased Peroxisome Proliferator-Activated Receptor Gamma (PPAR-γ) activation (p ≤ 0.001). This, in turn, resulted in repression of the nuclear factor κB (NFκB) signaling pathway, causing decreased production of inflammatory cytokines and chemokines. Our study demonstrates colitis remission in a DSS-induced mouse model, showcasing RCJ as a potential modulator for gut microbiota and metabolites, with promising implications for IBD prevention and treatment.

Immune-Related Gene Signatures to Predict the Effectiveness of Chemoimmunotherapy in Triple-Negative Breast Cancer Using Exploratory Subgroup Discovery.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited therapeutic options. Although immunotherapy has shown potential in TNBC patients, clinical studies have only demonstrated a modest response. Therefore, the exploration of immunotherapy in combination with chemotherapy is warranted. In this project we identified immune-related gene signatures for TNBC patients that may explain differences in patients' outcomes after anti-PD-L1+chemotherapy treatment. First, we ran the exploratory subgroup discovery algorithm on the TNBC dataset comprised of 422 patients across 24 studies. Secondly, we narrowed down the search to twelve homogenous subgroups based on tumor mutational burden (TMB, low or high), relapse status (disease-free or recurred), tumor cellularity (high, low and moderate), menopausal status (pre- or post) and tumor stage (I, II and III). For each subgroup we identified a union of the top 10% of genotypic patterns. Furthermore, we employed a multinomial regression model to predict significant genotypic patterns that would be linked to partial remission after anti-PD-L1+chemotherapy treatment. Finally, we uncovered distinct immune cell populations (T-cells, B-cells, Myeloid, NK-cells) for TNBC patients with various treatment outcomes. CD4-Tn-LEF1 and CD4-CXCL13 T-cells were linked to partial remission on anti-PD-L1+chemotherapy treatment. Our informatics pipeline may help to select better responders to chemoimmunotherapy, as well as pinpoint the underlying mechanisms of drug resistance in TNBC patients at single-cell resolution.

TBX21 Methylation as a Potential Regulator of Immune Suppression in CMS1 Subtype Colorectal Cancer.

Cytotoxic T lymphocyte (CTL) infiltration is associated with survival, recurrence, and therapeutic response in colorectal cancer (CRC). Immune checkpoint inhibitor (ICI) therapy, which requires CTLs for response, does not work for most CRC patients. Therefore, it is critical to improve our understanding of immune resistance in this disease. We utilized 2391 CRC patients and 7 omics datasets, integrating clinical and genomic data to determine how DNA methylation may impact survival and CTL function in CRC. Using comprehensive molecular subtype (CMS) 1 patients as reference, we found TBX21 to be the only gene with altered expression and methylation that was associated with CTL infiltration. We found that CMS1 patients with high TBX21 expression and low methylation had a significant survival advantage. To confirm the role of Tbx21 in CTL function, we utilized scRNAseq data, demonstrating the association of TBX21 with markers of enhanced CTL function. Further analysis using pathway enrichment found that the genes TBX21, MX1, and SP140 had altered expression and methylation, suggesting that the TP53/P53 pathway may modify TBX21 methylation to upregulate TBX21 expression. Together, this suggests that targeting epigenetic modification more specifically for therapy and patient stratification may provide improved outcomes in CRC.

Identification of Immuno-Targeted Combination Therapies Using Explanatory Subgroup Discovery for Cancer Patients with EGFR Wild-Type Gene.

(1) Background: Phenotypic and genotypic heterogeneity are characteristic features of cancer patients. To tackle patients' heterogeneity, immune checkpoint inhibitors (ICIs) represent some the most promising therapeutic approaches. However, approximately 50% of cancer patients that are eligible for treatment with ICIs do not respond well, especially patients with no targetable mutations. Over the years, multiple patient stratification techniques have been developed to identify homogenous patient subgroups, although matching a patient subgroup to a treatment option that can improve patients' health outcomes remains a challenging task. (2) Methods: We extended our Subgroup Discovery algorithm to identify patient subpopulations that could potentially benefit from immuno-targeted combination therapies in four cancer types: head and neck squamous carcinoma (HNSC), lung adenocarcinoma (LUAD), lung squamous carcinoma (LUSC), and skin cutaneous melanoma (SKCM). We employed the proportional odds model to identify significant drug targets and the corresponding compounds that increased the likelihood of stable disease versus progressive disease in cancer patients with the EGFR wild-type (WT) gene. (3) Results: Our pipeline identified six significant drug targets and thirteen specific compounds for cancer patients with the EGFR WT gene. Three out of six drug targets-FCGR2B, IGF1R, and KIT-substantially increased the odds of having stable disease versus progressive disease. Progression-free survival (PFS) of more than 6 months was a common feature among the investigated subgroups. (4) Conclusions: Our approach could help to better select responders for immuno-targeted combination therapies and improve health outcomes for cancer patients with no targetable mutations.

Somatic mutation variant analysis in rural, resectable non-small cell lung carcinoma patients.

Rural non-small cell lung cancer (NSCLC) patients do worse, largely related to lack of access to care. In this study, the mutational characteristics and potential for targeted therapy in rural, resectable NSCLC patients using whole exome sequencing (WES) were analyzed. WES was performed on tumor-adjacent normal pairs from rural patients undergoing resection for NSCLC. Sequencing alignment, variant-calling, annotation, and tumor mutational burden (TMB) calculations were performed using standard methods. cBioportal and OncoKB were used for comparisons of mutational frequencies and actionable targets. Thirty-four NSCLC patients underwent WES after surgical resection. The gene most frequently containing somatic variants was TP53. The median number of somatic variants was 188 (Range 11-1056), and median TMB was 3.30 (0.33-18.56) nonsynonymous mutations per Mb. Tumor stage and survival were not associated with number of variants, TMB or TP53 mutational status. Significant concordance among the most common mutations when cross-referenced to cBioportal (R = 0.78, p < 0.0001) was observed. 24% of patients had variants in actionable genes based on OncoKB annotation. In summary, we demonstrate baseline mutational frequency and establish foundations for targeted adjuvant trials in rural NSCLC patients with specific differences. Future studies must ensure to include rural patients to improve NSCLC patient outcomes.

Single Circulating-Tumor-Cell-Targeted Sequencing to Identify Somatic Variants in Liquid Biopsies in Non-Small-Cell Lung Cancer Patients.

Non-small-cell lung cancer (NSCLC) accounts for most cancer-related deaths worldwide. Liquid biopsy by a blood draw to detect circulating tumor cells (CTCs) is a tool for molecular profiling of cancer using single-cell and next-generation sequencing (NGS) technologies. The aim of the study was to identify somatic variants in single CTCs isolated from NSCLC patients by targeted NGS. Thirty-one subjects (20 NSCLC patients, 11 smokers without cancer) were enrolled for blood draws (7.5 mL). CTCs were identified by immunofluorescence, individually retrieved, and DNA-extracted. Targeted NGS was performed to detect somatic variants (single-nucleotide variants (SNVs) and insertions/deletions (Indels)) across 65 oncogenes and tumor suppressor genes. Cancer-associated variants were classified using OncoKB database. NSCLC patients had significantly higher CTC counts than control smokers (p = 0.0132; Mann-Whitney test). Analyzing 23 CTCs and 13 white blood cells across seven patients revealed a total of 644 somatic variants that occurred in all CTCs within the same subject, ranging from 1 to 137 per patient. The highest number of variants detected in ≥1 CTC within a patient was 441. A total of 18/65 (27.7%) genes were highly mutated. Mutations with oncogenic impact were identified in functional domains of seven oncogenes/tumor suppressor genes (NF1, PTCH1, TP53, SMARCB1, SMAD4, KRAS, and ERBB2). Single CTC-targeted NGS detects heterogeneous and shared mutational signatures within and between NSCLC patients. CTC single-cell genomics have potential for integration in NSCLC precision oncology.

Circulating Tumor-Macrophage Fusion Cells and Circulating Tumor Cells Complement Non-Small-Cell Lung Cancer Screening in Patients With Suspicious Lung-RADS 4 Nodules.

PURPOSE: Low-dose computed tomography (LDCT) screening of high-risk patients decreases lung cancer-related mortality. However, high false-positive rates associated with LDCT result in unnecessary interventions. To distinguish non-small-cell lung cancer (NSCLC) from benign nodules, in the present study, we integrated cellular liquid biomarkers in patients with suspicious lung nodules (lung cancer screening reporting and data system [Lung-RADS] 4). METHODS: Prospectively, 7.5 mL of blood was collected from 221 individuals (training set: 90 nonscreened NSCLC patients, 74 high-risk screening patients with no/benign nodules [Lung-RADS 1-3], and 20 never smokers; validation set: 37 patients with suspicious nodules [Lung-RADS 4]). Circulating tumor cells (CTCs), CTC clusters, and tumor-macrophage fusion (TMF) cells were identified by blinded analyses. Screening patients underwent a median of two LDCTs (range, 1-4) with a median surveillance time of 30 (range, 11-50) months. RESULTS: In the validation set of 37 Lung-RADS 4 patients, all circulating cellular biomarker counts (P < .005; Wilcoxon test) and positivity rates were significantly higher in 23 biopsy-proven NSCLC patients (CTCs: 23 of 23 [100%], CTC clusters: 6 of 23 [26.1%], and TMF cells: 15 of 23 [65.2%]) than in 14 patients with biopsy-proven benign nodules (6 of 14 [42.9%], 0 of 14 [0%], and 2 of 14 [14.3%]). On the basis of cutoff values from the training set, logistic regression with receiver operating characteristic and area under the curve analyses demonstrated that CTCs (sensitivity: 0.870, specificity: 1.0, and area under the curve: 0.989) and TMF cells (0.652; 0.880; 0.790) complement LDCT in diagnosing NSCLC in Lung-RADS 4 patients. CONCLUSION: Cellular liquid biomarkers have a potential to complement LDCT interpretation of suspicious Lung-RADS 4 nodules to distinguish NSCLC from benign lung nodules. A future prospective, large-scale, multicenter clinical trial should validate the role of cellular liquid biomarkers in improving diagnostic accuracy in high-risk patients with Lung-RADS 4 nodules.

Tumorigenic circulating tumor cells from xenograft mouse models of non-metastatic NSCLC patients reveal distinct single cell heterogeneity and drug responses.

BACKGROUND: Circulating tumor cells (CTCs) are liquid biopsies that represent micrometastatic disease and may offer unique insights into future recurrences in non-small cell lung cancer (NSCLC). Due to CTC rarity and limited stability, no stable CTC-derived xenograft (CDX) models have ever been generated from non-metastatic NSCLC patients directly. Alternative strategies are needed to molecularly characterize CTCs and means of potential future metastases in this potentially curable patient group. METHODS: Surgically resected NSCLC primary tumor tissues from non-metastatic patients were implanted subcutaneously in immunodeficient mice to establish primary tumor patient-derived xenograft (ptPDX) models. CTCs were isolated as liquid biopsies from the blood of ptPDX mice and re-implanted subcutaneously into naïve immunodeficient mice to generate liquid biopsy CTC-derived xenograft (CDX) tumor models. Single cell RNA sequencing was performed and validated in an external dataset of non-xenografted human NSCLC primary tumor and metastases tissues. Drug response testing in CDX models was performed with standard of care chemotherapy (carboplatin/paclitaxel). Blockade of MYC, which has a known role in drug resistance, was performed with a MYC/MAX dimerization inhibitor (10058-F4). RESULTS: Out of ten ptPDX, two (20%) stable liquid biopsy CDX mouse models were generated. Single cell RNA sequencing analysis revealed an additional regenerative alveolar epithelial type II (AT2)-like cell population in CDX tumors that was also identified in non-xenografted NSCLC patients' metastases tissues. Drug testing using these CDX models revealed different treatment responses to carboplatin/paclitaxel. MYC target genes and c-MYC protein were upregulated in the chemoresistant CDX model, while MYC/MAX dimerization blocking could overcome chemoresistance to carboplatin/paclitaxel. CONCLUSIONS: To overcome the lack of liquid biopsy CDX models from non-metastatic NSCLC patients, CDX models can be generated with CTCs from ptPDX models that were originally established from patients' primary tumors. Single cell analyses can identify distinct drug responses and cell heterogeneities in CDX tumors that can be validated in NSCLC metastases tissues. CDX models deserve further development and study to discover personalized strategies against micrometastases in non-metastatic NSCLC patients.

Nanoliposome C6-Ceramide in combination with anti-CTLA4 antibody improves anti-tumor immunity in hepatocellular cancer.

Combination therapy represents an effective therapeutic approach to overcome hepatocellular cancer (HCC) resistance to immune checkpoint blockade (ICB). Based upon previous work demonstrating that nanoliposome C6-ceramide (LipC6) not only induces HCC apoptosis but also prevents HCC-induced immune tolerance, we now investigate the potential of LipC6 in combination with ICB in HCC treatment. We generated orthotopic HCC-bearing mice, which have typical features in common with human patients, and then treated them with LipC6 in combination with the antibodies (Abs) for programmed cell death protein 1 (PD-1) or cytotoxic T-lymphocyte antigen 4 (CTLA4). The tumor growth was monitored by magnetic resonance imaging (MRI) and the intrahepatic immune profiles were checked by flow cytometry in response to the treatments. Realtime PCR (qPCR) was used to detect the expression of target genes. The results show that LipC6 in combination with anti-CTLA4 Ab, but not anti-PD-1 Ab, significantly slowed tumor growth, enhanced tumor-infiltrating CD8+ T cells, and suppressed tumor-resident CD4+ CD25+ FoxP3+ Tregs. Further molecular investigation indicates that the combinational treatment suppressed transcriptional factor Krüppel-like Factor 2 (KLF2), forkhead box protein P3 (FoxP3), and CTLA4. Our studies suggest that LipC6 in combination with anti-CTLA4 Ab represents a novel therapeutic approach with significant potential in activating anti-HCC immune response and suppressing HCC growth.

Single-cell RNA sequencing to characterize the response of pancreatic cancer to anti-PD-1 immunotherapy.

Pancreatic cancer (PaC) is resistant to immune checkpoint therapy, but the underlying mechanisms are largely unknown. In this study, we have established four orthotopic PaC murine models with different PaC cell lines by intra-pancreatic inoculation. Therapeutic examinations demonstrate that only tumors induced with Panc02-H7 cells respond to αPD-1 antibody treatment, leading to significantly reduced tumor growth and increased survival in the recipient mice. Transcriptomic profiling at a single-cell resolution characterizes the molecular activity of different cells within tumors. Comparative analysis and validated experiments demonstrate that αPD-1-sensitive and -resistant tumors differently shape the immune landscape in the tumor microenvironment (TME) and markedly altering effector CD8+ T cells and tumor-associated macrophages (TAMs) in their number, frequency, and gene profile. More exhausted effector CD8+ T cells and increased M2-like TAMs with a reduced capacity of antigen presentation are detected in resistant Panc02-formed tumors versus responsive Panc02-H7-formed tumors. Together, our data highlight the correlation of tumor-induced imbalance of macrophages with the fate of tumor-resident effector CD8+ T cells and PaC response to αPD-1 immunotherapy. TAMs as a critical regulator of tumor immunity and immunotherapy contribute to PaC resistance to immune checkpoint blockade.

Epigenetic Regulation of Cancer Immune Cells.

The epigenetic regulation of immune response involves reversible and heritable changes that do not alter the DNA sequence. Though there have been extensive studies accomplished relating to epigenetic changes in cancer cells, recent focus has been shifted on epigenetic-mediated changes in the immune cells including T cells, Macrophages, Natural Killer cells and anti-tumor immune responses. This review compiles the most relevant and recent literature related to the role of epigenetic mechanisms including DNA methylation and histone modifications in immune cells of wide range of cancers. We also include recent research with respect to role of the most relevant transcription factors that epigenetically control the anti-tumor immune response. Finally, a statement of future direction that promises to look forward for strategies to improve immunotherapy in cancer.