AZGP1 deficiency promotes angiogenesis in prostate cancer.

BACKGROUND: Loss of AZGP1 expression is a biomarker associated with progression to castration resistance, development of metastasis, and poor disease-specific survival in prostate cancer. However, high expression of AZGP1 cells in prostate cancer has been reported to increase proliferation and invasion. The exact role of AZGP1 in prostate cancer progression remains elusive. METHOD: AZGP1 knockout and overexpressing prostate cancer cells were generated using a lentiviral system. The effects of AZGP1 under- or over-expression in prostate cancer cells were evaluated by in vitro cell proliferation, migration, and invasion assays. Heterozygous AZGP1± mice were obtained from European Mouse Mutant Archive (EMMA), and prostate tissues from homozygous knockout male mice were collected at 2, 6 and 10 months for histological analysis. In vivo xenografts generated from AZGP1 under- or over-expressing prostate cancer cells were used to determine the role of AZGP1 in prostate cancer tumor growth, and subsequent proteomics analysis was conducted to elucidate the mechanisms of AZGP1 action in prostate cancer progression. AZGP1 expression and microvessel density were measured in human prostate cancer samples on a tissue microarray of 215 independent patient samples. RESULT: Neither the knockout nor overexpression of AZGP1 exhibited significant effects on prostate cancer cell proliferation, clonal growth, migration, or invasion in vitro. The prostates of AZGP1-/- mice initially appeared to have grossly normal morphology; however, we observed fibrosis in the periglandular stroma and higher blood vessel density in the mouse prostate by 6 months. In PC3 and DU145 mouse xenografts, over-expression of AZGP1 did not affect tumor growth. Instead, these tumors displayed decreased microvessel density compared to xenografts derived from PC3 and DU145 control cells, suggesting that AZGP1 functions to inhibit angiogenesis in prostate cancer. Proteomics profiling further indicated that, compared to control xenografts, AZGP1 overexpressing PC3 xenografts are enriched with angiogenesis pathway proteins, including YWHAZ, EPHA2, SERPINE1, and PDCD6, MMP9, GPX1, HSPB1, COL18A1, RNH1, and ANXA1. In vitro functional studies show that AZGP1 inhibits human umbilical vein endothelial cell proliferation, migration, tubular formation and branching. Additionally, tumor microarray analysis shows that AZGP1 expression is negatively correlated with blood vessel density in human prostate cancer tissues. CONCLUSION: AZGP1 is a negative regulator of angiogenesis, such that loss of AZGP1 promotes angiogenesis in prostate cancer. AZGP1 likely exerts heterotypical effects on cells in the tumor microenvironment, such as stromal and endothelial cells. This study sheds light on the anti-angiogenic characteristics of AZGP1 in the prostate and provides a rationale to target AZGP1 to inhibit prostate cancer progression.

Antiseptic Functions of CGK012 against HMGB1-Mediated Septic Responses.

High mobility group box 1 (HMGB1), a protein with important functions, has been recognized as a potential therapeutic target for the treatment of sepsis. One possible mechanism for this is that inhibiting HMGB1 secretion can exert antiseptic effects, which can restore the integrity of the vascular barrier. (7S)-(+)-cyclopentyl carbamic acid 8,8-dimethyl-2-oxo-6,7-dihydro-2H,8H-pyrano[3,2-g]chromen-7-yl-ester (CGK012) is a newly synthesized pyranocoumarin compound that could function as a novel small-molecule inhibitor of the Wnt/ß-catenin signaling pathway. However, no studies have yet determined the effects of CGK012 on sepsis. We investigated the potential of CGK012 to attenuate the excessive permeability induced by HMGB1 and enhance survival rates in a mouse model of sepsis with reduced HMGB1 levels following lipopolysaccharide (LPS) treatment. In both LPS-stimulated human endothelial cells and a mouse model exhibiting septic symptoms due to cecal ligation and puncture (CLP), we assessed proinflammatory protein levels and tissue damage biomarkers as indicators of reduced vascular permeability. CGK012 was applied after induction in human endothelial cells exposed to LPS and the CLP-induced mouse model of sepsis. CGK012 effectively mitigated excessive permeability and suppressed HMGB1 release, resulting in improved vascular stability, decreased mortality, and enhanced histological conditions in the mouse model of CLP-induced sepsis. In conclusion, our findings indicate that CGK012 treatment in mice with CLP-induced sepsis diminished HMGB1 release and increased the survival rate, suggesting its potential as a pharmaceutical intervention for sepsis.

Spatial Effects of Infiltrating T cells on Neighbouring Cancer Cells and Prognosis in Stage III CRC patients.

Colorectal cancer (CRC) is one of the most frequently occurring cancers, but prognostic biomarkers identifying patients at risk of recurrence are still lacking. In this study, we aimed to investigate in more detail the spatial relationship between intratumoural T cells, cancer cells, and cancer cell hallmarks, as prognostic biomarkers in stage III colorectal cancer patients. We conducted multiplexed imaging of 56 protein markers at single cell resolution on resected fixed tissue from stage III CRC patients who received adjuvant 5-fluorouracil-based chemotherapy. Images underwent segmentation for tumour, stroma and immune cells, and cancer cell 'state' protein marker expression was quantified at a cellular level. We developed a Python package for estimation of spatial proximity, nearest neighbour analysis focusing on cancer cell - T cell interactions at single-cell level. In our discovery cohort (MSK), we processed 462 core samples (total number of cells: 1,669,228) from 221 adjuvant 5FU-treated stage III patients. The validation cohort (HV) consisted of 272 samples (total number of cells: 853,398) from 98 stage III CRC patients. While there were trends for an association between percentage of cytotoxic T cells (across the whole cancer core), it did not reach significance (Discovery cohort: p = 0.07, Validation cohort: p = 0.19). We next utilized our region-based nearest neighbourhood approach to determine the spatial relationships between cytotoxic T cells, helper T cells and cancer cell clusters. In the both cohorts, we found that lower distance between cytotoxic T cells, T helper cells and cancer cells was significantly associated with increased disease-free survival. An unsupervised trained model that clustered patients based on the median distance between immune cells and cancer cells, as well as protein expression profiles, successfully classified patients into low-risk and high-risk groups (Discovery cohort: p = 0.01, Validation cohort: p = 0.003).

Therapeutic effects of hederacolchiside A1 on particulate matter-induced pulmonary injury.

Particulate matter (PM) comprises a hazardous mixture of inorganic and organic particles that carry health risks. Inhaling fine PM particles with a diameter of ≤2.5 µm (PM2.5) can promote significant lung damage. Hederacolchiside A1 (HA1) exhibits notable in vivo antitumor effects against various solid tumors. However, our understanding of its therapeutic potential for individuals with PM2.5-induced lung injuries remains limited. Here, we explored the protective properties of HA1 against lung damage caused by PM2.5 exposure. HA1 was administered to the mice 30 min after intratracheal tail vein injection of PM2.5. Various parameters, such as changes in lung tissue wet/dry (W/D) weight ratio, total protein/total cell ratio, lymphocyte counts, inflammatory cytokine levels in bronchoalveolar lavage fluid (BALF), vascular permeability, and histology, were assessed in mice exposed to PM2.5. Our data showed that HA1 mitigated lung damage, reduced the W/D weight ratio, and suppressed hyperpermeability caused by PM2.5 exposure. Moreover, HA1 effectively decreased plasma levels of inflammatory cytokines in those exposed to PM2.5, including tumor necrosis factor-α, interleukin-1ß, and nitric oxide, while also lowering the total protein concentration in BALF and successfully alleviating PM2.5-induced lymphocytosis. Furthermore, HA1 significantly decreased the expression levels of toll-like receptor 4 (TLR4), myeloid differentiation primary response (MyD) 88, and autophagy-related proteins LC3 II and Beclin 1 but increased the protein phosphorylation of the mammalian target of rapamycin (mTOR). The anti-inflammatory characteristics of HA1 highlights its potential as a promising therapeutic agent for mitigating PM2.5-induced lung injuries by modulating the TLR4-MyD88 and mTOR-autophagy pathways.

Comparative Study on the Immunogenicity of COVID-19 mRNA Vaccines in Patients Receiving Adjuvant and Palliative Chemotherapy.

This study was conducted to investigate potential differences in vaccine efficacy between patients undergoing palliative chemotherapy and receiving adjuvant chemotherapy. Additionally, the study proved the influence of vaccination timing on vaccine efficacy during active chemotherapy. Anti-receptor-binding domain (RBD) IgG binding antibody assays and surrogate neutralizing antibody assays were performed after BNT162b2 or mRNA-1273 vaccination in 45 solid cancer patients (23 adjuvant and 22 palliative chemotherapy) and in 24 healthy controls before vaccination (baseline), at every two to four weeks after the first (post-dose 1) and the second vaccination (post-dose 2). The levels of anti-RBD IgG and neutralizing antibodies increased significantly from baseline through post-dose 1 to post-dose 2 in all three groups. At the post-dose 1, the anti-RBD IgG and neutralizing antibody levels were significantly lower in cancer patients than in healthy controls. However, by post-dose 2, the seropositivity of anti-RBD IgG and neutralizing antibodies uniformly reached 100% across all groups, with no significant disparity in antibody levels among the three groups. Moreover, the antibody titers were not significantly different between patients with a vaccine and chemotherapy interval of more than 14 days or those with less than 14 days. This study demonstrated that after second doses of mRNA COVID-19 vaccines, humoral immune responses in patients receiving chemotherapy were comparable to those of healthy controls, regardless of whether the purpose of the anti-cancer treatment was palliative or adjuvant. Furthermore, the timing of vaccination did not affect the level of humoral immunity after the second vaccination.

The Therapeutic Potential of (+)-Afzelechin for Alleviating Sepsis-Associated Pulmonary Injury.

Sepsis-induced acute lung injury (ALI) poses a common and formidable challenge in clinical practice, currently lacking efficacious therapeutic approaches. This study delves into the evaluation of (+)-afzelechin (AZC), a natural compound derived from Bergenia ligulata with a diverse array of properties, encompassing antioxidant, anticancer, antimicrobial, and cardiovascular effects to ascertain its effectiveness and underlying mechanisms in mitigating sepsis-induced ALI through animal experimentation. An ALI mouse model induced by sepsis was established through lipopolysaccharide (LPS) administration, and various analytical techniques, including quantitative real-time polymerase chain reaction, Western blotting, and enzyme-linked immunosorbent assay were employed to gauge inflammatory cytokine levels, lung injury, and associated signaling pathways. The animal experiments revealed that AZC offered safeguards against lung injury induced by LPS while reducing inflammatory cytokine levels in both blood serum and lung tissue. Western blotting experiments revealed AZC's downregulation of the toll-like receptor (TLR)4/NF-κB pathway and the upregulation of PI3K/Akt, coupled with inhibition of the Hippo and Rho signaling pathways. These findings underscore AZC's efficacy in ameliorating sepsis-induced ALI by modulating cytokine storms and curtailing inflammation via the regulation of TLR4/NF-κB, PI3K/Akt, Hippo, and Rho signaling pathways. This work serves as a foundation for additional exploration into AZC's mechanisms and its potential as a therapy for sepsis-induced ALI. Animals in accordance with Kyungpook National University (IRB No. KNU 2022-174).

Therapeutic Effects of (+)-Afzelechin on Particulate Matter-Induced Pulmonary Injury.

Particulate matter (PM) constitutes a hazardous blend of organic and inorganic particles that poses health risks. Inhalation of fine airborne PM with a diameter of ≤ 2.5 µm (PM2.5) can lead to significant lung impairments. (+)-afzelechin (AZC), a natural compound sourced from Bergenia ligulata, boasts a range of attributes, including antioxidant, antimicrobial, anticancer, and cardiovascular effects. However, knowledge about the therapeutic potential of AZC for patients with PM2.5-induced lung injuries remains limited. Thus, in this study, we investigated the protective attributes of AZC against lung damage caused by PM2.5 exposure. AZC was administered to the mice 30 min after intratracheal instillation of PM2.5. Various parameters, such as changes in lung tissue wet/dry (W/D) weight ratio, total protein/total cell ratio, lymphocyte counts, levels of inflammatory cytokines in bronchoalveolar lavage fluid (BALF), vascular permeability, and histology, were evaluated in mice exposed to PM2.5. Data demonstrated that AZC mitigated lung damage, reduced W/D weight ratio, and curbed hyperpermeability induced by PM2.5 exposure. Furthermore, AZC effectively lowered plasma levels of inflammatory cytokines produced by PM2.5 exposure. It reduced the total protein concentration in BALF and successfully alleviated PM2.5-induced lymphocytosis. Additionally, AZC substantially diminished the expression levels of Toll-like receptors 4 (TLR4), MyD88, and autophagy-related proteins LC3 II and Beclin 1. In contrast, it elevated the protein phosphorylation of the mammalian target of rapamycin (mTOR). Consequently, the anti-inflammatory attribute of AZC positions it as a promising therapeutic agent for mitigating PM2.5-induced lung injuries by modulating the TLR4-MyD88 and mTOR-autophagy pathways.

3D reconstruction of skin and spatial mapping of immune cell density, vascular distance and effects of sun exposure and aging.

Mapping the human body at single cell resolution in three dimensions (3D) is important for understanding cellular interactions in context of tissue and organ organization. 2D spatial cell analysis in a single tissue section may be limited by cell numbers and histology. Here we show a workflow for 3D reconstruction of multiplexed sequential tissue sections: MATRICS-A (Multiplexed Image Three-D Reconstruction and Integrated Cell Spatial - Analysis). We demonstrate MATRICS-A in 26 serial sections of fixed skin (stained with 18 biomarkers) from 12 donors aged between 32-72 years. Comparing the 3D reconstructed cellular data with the 2D data, we show significantly shorter distances between immune cells and vascular endothelial cells (56 µm in 3D vs 108 µm in 2D). We also show 10-70% more T cells (total) within 30 µm of a neighboring T helper cell in 3D vs 2D. Distances of p53, DDB2 and Ki67 positive cells to the skin surface were consistent across all ages/sun exposure and largely localized to the lower stratum basale layer of the epidermis. MATRICS-A provides a framework for analysis of 3D spatial cell relationships in healthy and aging organs and could be further extended to diseased organs.

Predicting Breast Cancer Events in Ductal Carcinoma In Situ (DCIS) Using Generative Adversarial Network Augmented Deep Learning Model.

Standard clinicopathological parameters (age, growth pattern, tumor size, margin status, and grade) have been shown to have limited value in predicting recurrence in ductal carcinoma in situ (DCIS) patients. Early and accurate recurrence prediction would facilitate a more aggressive treatment policy for high-risk patients (mastectomy or adjuvant radiation therapy), and simultaneously reduce over-treatment of low-risk patients. Generative adversarial networks (GAN) are a class of DL models in which two adversarial neural networks, generator and discriminator, compete with each other to generate high quality images. In this work, we have developed a deep learning (DL) classification network that predicts breast cancer events (BCEs) in DCIS patients using hematoxylin and eosin (H & E) images. The DL classification model was trained on 67 patients using image patches from the actual DCIS cores and GAN generated image patches to predict breast cancer events (BCEs). The hold-out validation dataset (n = 66) had an AUC of 0.82. Bayesian analysis further confirmed the independence of the model from classical clinicopathological parameters. DL models of H & E images may be used as a risk stratification strategy for DCIS patients to personalize therapy.

Suppression of triple-negative breast cancer aggressiveness by LGALS3BP via inhibition of the TNF-α-TAK1-MMP9 axis.

Transforming growth factor-ß-activated kinase 1 (TAK1), which is highly expressed and aberrantly activated in triple-negative breast cancer (TNBC), plays a pivotal role in metastasis and progression. This makes it a potential therapeutic target for TNBC. Previously, we reported lectin galactoside-binding soluble 3 binding protein (LGALS3BP) as a negative regulator of TAK1 signaling in the inflammatory response and inflammation-associated cancer progression. However, the role of LGALS3BP and its molecular interaction with TAK1 in TNBC remain unclear. This study aimed to investigate the function and underlying mechanism of action of LGALS3BP in TNBC progression and determine the therapeutic potential of nanoparticle-mediated delivery of LGALS3BP in TNBC. We found that LGALS3BP overexpression suppressed the overall aggressive phenotype of TNBC cells in vitro and in vivo. LGALS3BP inhibited TNF-α-mediated gene expression of matrix metalloproteinase 9 (MMP9), which encodes a protein crucial for lung metastasis in TNBC patients. Mechanistically, LGALS3BP suppressed TNF-α-mediated activation of TAK1, a key kinase linking TNF-α stimulation and MMP9 expression in TNBC. Nanoparticle-mediated delivery enabled tumor-specific targeting and inhibited TAK1 phosphorylation and MMP9 expression in tumor tissues, suppressing primary tumor growth and lung metastasis in vivo. Our findings reveal a novel role of LGALS3BP in TNBC progression and demonstrate the therapeutic potential of nanoparticle-mediated delivery of LGALS3BP in TNBC.

No association between genetically predicted C-reactive protein levels and colorectal cancer survival in Korean: two-sample Mendelian randomization analysis.

OBJECTIVES: Elevated C-reactive protein (CRP) levels are associated with an increased risk for colorectal cancer (CRC), as well as a poor prognosis, but it remains unclear whether these associations are causal. This study examined the potential causality between CRP levels and CRC survival using 2-sample Mendelian randomization (MR). METHODS: From the Korean Genome and Epidemiology Study, a genome-wide association study (n=59,605), 7 single-nucleotide polymorphisms (SNPs) related to log2-transformed CRP levels were extracted as instrumental variables for CRP levels. The associations between the genetically predicted CRP and CRC-specific and overall mortality among CRC patients (n=6,460) were evaluated by Aalen's additive hazard model. The sensitivity analysis excluded a SNP related to the blood lipid profile. RESULTS: During a median of 8.5 years of follow-up, among 6,460 CRC patients, 2,676 (41.4%) CRC patients died from all causes and 1,622 (25.1%) died from CRC. Genetically predicted CRP levels were not significantly associated with overall or CRC-specific mortality in CRC patients. The hazard difference per 1,000 person-years for overall and CRC-specific mortality per 2-fold increase in CRP levels was -2.92 (95% confidence interval [CI], -14.05 to 8.21) and -0.76 (95% CI, -9.61 to 8.08), respectively. These associations were consistent in a subgroup analysis according to metastasis and a sensitivity analysis excluding possible pleiotropic SNPs. CONCLUSIONS: Our findings do not support a causal role for genetically predisposed CRP levels in CRC survival.

Deep learning-based automated pipeline for blood vessel detection and distribution analysis in multiplexed prostate cancer images.

Introduction: Prostate cancer is a highly heterogeneous disease, presenting varying levels of aggressiveness and response to treatment. Angiogenesis is one of the hallmarks of cancer, providing oxygen and nutrient supply to tumors. Micro vessel density has previously been correlated with higher Gleason score and poor prognosis. Manual segmentation of blood vessels (BVs) In microscopy images is challenging, time consuming and may be prone to inter-rater variabilities. In this study, an automated pipeline is presented for BV detection and distribution analysis in multiplexed prostate cancer images. Methods: A deep learning model was trained to segment BVs by combining CD31, CD34 and collagen IV images. In addition, the trained model was used to analyze the size and distribution patterns of BVs in relation to disease progression in a cohort of prostate cancer patients (N = 215). Results: The model was capable of accurately detecting and segmenting BVs, as compared to ground truth annotations provided by two reviewers. The precision (P), recall (R) and dice similarity coefficient (DSC) were equal to 0.93 (SD 0.04), 0.97 (SD 0.02) and 0.71 (SD 0.07) with respect to reviewer 1, and 0.95 (SD 0.05), 0.94 (SD 0.07) and 0.70 (SD 0.08) with respect to reviewer 2, respectively. BV count was significantly associated with 5-year recurrence (adjusted p = 0.0042), while both count and area of blood vessel were significantly associated with Gleason grade (adjusted p = 0.032 and 0.003 respectively). Discussion: The proposed methodology is anticipated to streamline and standardize BV analysis, offering additional insights into the biology of prostate cancer, with broad applicability to other cancers.

Epithelial TGFß engages growth-factor signalling to circumvent apoptosis and drive intestinal tumourigenesis with aggressive features.

The pro-tumourigenic role of epithelial TGFß signalling in colorectal cancer (CRC) is controversial. Here, we identify a cohort of born to be bad early-stage (T1) colorectal tumours, with aggressive features and a propensity to disseminate early, that are characterised by high epithelial cell-intrinsic TGFß signalling. In the presence of concurrent Apc and Kras mutations, activation of epithelial TGFß signalling rampantly accelerates tumourigenesis and share transcriptional signatures with those of the born to be bad T1 human tumours and predicts recurrence in stage II CRC. Mechanistically, epithelial TGFß signalling induces a growth-promoting EGFR-signalling module that synergises with mutant APC and KRAS to drive MAPK signalling that re-sensitise tumour cells to MEK and/or EGFR inhibitors. Together, we identify epithelial TGFß signalling both as a determinant of early dissemination and a potential therapeutic vulnerability of CRC's with born to be bad traits.

Tumor Infiltrating Lymphocytes in Multi-National Cohorts of Ductal Carcinoma In Situ (DCIS) of Breast.

Tumor-infiltrating lymphocytes (TILs) are prognostic in invasive breast cancer. However, their prognostic significance in ductal carcinoma in situ (DCIS) has been controversial. To investigate the prognostic role of TILs in DCIS outcome, we used different scoring methods for TILs in multi-national cohorts from Asian and European women. Self-described race was genetically confirmed using QC Infinium array combined with radmixture software. Stromal TILs, touching TILs, circumferential TILs, and hotspots were quantified on H&E-stained slides and correlated with the development of second breast cancer events (BCE) and other clinico-pathological variables. In univariate survival analysis, age older than 50 years, hormone receptor positivity and the presence of circumferential TILs were weakly associated with the absence of BCE at the 5-year follow-up in all cohorts (p < 0.03; p < 0.02; and p < 0.02, respectively, adjusted p = 0.11). In the multivariable analysis, circumferential TILs were an independent predictor of a better outcome (Wald test p = 0.01), whereas younger age was associated with BCE. Asian patients were younger with larger, higher grade, HR negative DCIS lesions, and higher TIL variables. The spatial arrangement of TILs may serve as a better prognostic indicator in DCIS cases than stromal TILs alone and may be added in guidelines for TILs evaluation in DCIS.

Apoptotic and Necroptotic Mediators are Differentially Expressed in Mucinous and Non-Mucinous Colorectal Cancer.

Background: Mucinous colorectal cancer (CRC) represents 10% of all CRC and is associated with chemotherapy resistance. This study aimed to determine expression of apoptosis and necroptosis mediators in mucinous CRC. Methods: RNA gene expression data were extracted from TCGA. Protein levels in 14 mucinous and 39 non-mucinous tumors were measured by multiplexed immunofluorescence. Levels of apoptosis and necroptosis signalling proteins were analysed in SW1463 (mucinous rectal), SW837 (non-mucinous rectal), LS174T (mucinous colon) and HCT116 (non-mucinous colon) cell lines by western blot. Cell death was investigated by flow cytometry measurement of propidium iodide stained cells. Results: High cleaved-Caspase 3 expression was noted in resected mucinous tumors. Western blot identified alterations in apoptosis proteins in mucinous CRC, most prominently downregulation of Bcl-xL protein levels (p=0.029) which was also observed at the mRNA level in patients by analysis of TCGA gene expression data (p<0.001). Treatment with 5-FU did not significantly elevate cell death in mucinous cells, while non-mucinous cells showed robust cell death responses. However, 5-FU-induced phosphorylation of MLKL in mucinous cancer cells, suggestive of a switch to necroptotic cell death signaling. Conclusion: Apoptotic and necroptotic mediators are differentially expressed in mucinous and non-mucinous colorectal cancers and represent targets for investigation of cell death mechanisms in the mucinous subtype.

A Phase II Study of Nivolumab plus Gemcitabine in Patients with Recurrent or Metastatic Nasopharyngeal Carcinoma (KCSG HN17-11).

PURPOSE: Although programmed death 1/programmed death ligand 1 (PD-1/PD-L1) inhibitors are promising agents for recurrent or metastatic nasopharyngeal carcinoma (NPC), PD-1/PD-L1 inhibitor monotherapy has shown modest efficacy. This study evaluated the efficacy and safety of nivolumab plus gemcitabine in patients with NPC who failed prior platinum-based chemotherapy. PATIENTS AND METHODS: This is a phase II, multicenter, open-label, single-arm study. Patients with recurrent or metastatic NPC received nivolumab 3 mg/kg and gemcitabine 1,250 mg/m2 every 2 weeks until disease progression or intolerable toxicity. The primary endpoint was progression-free survival (PFS). The secondary endpoints included objective response rate (ORR), overall survival (OS), and safety. To identify potential biomarkers, whole-exome sequencing, whole-transcriptome sequencing, and immune phenotype analysis based on Lunit SCOPE IO, an artificial intelligence-powered spatial tumor-infiltrating lymphocyte analyzer, were performed. RESULTS: Thirty-six patients were enrolled between June 2018 and June 2019. The ORR was 36.1% and disease control rate was 97.2%. With median follow-up of 22.0 months, median PFS was 13.8 months [95% confidence interval (CI), 8.6-16.8 months]. Median OS was not reached, and OS rate at 6 months was 97.0% (95% CI, 80.4%-99.6%). The grade ≥3 treatment-related adverse events were hypertension (2.8%) and anemia (2.8%). In multivariate analysis of mutation of chromatin modifier gene, tumor mutational burden (≥ 2.1 mut/Mb), and somatic copy-number alteration (SCNA) level, the group with high SCNA (> 3 points; HR, 7.0; 95% CI, 1.3-37.9; P = 0.02) had independently associated with poor PFS. Immune phenotype analysis showed that tumors with high proportion of immune-excluded immune phenotype was significantly correlated with poor PFS (HR, 4.4; 95% CI, 1.2-16.2; P = 0.018). CONCLUSIONS: Nivolumab plus gemcitabine showed promising efficacy with favorable toxicity profiles in patients with advanced NPC in whom platinum-based combination chemotherapy failed.

Dysadherin awakens mechanical forces and promotes colorectal cancer progression.

Rationale: Dysadherin is a tumor-associated, membrane-embedded antigen found in multiple types of cancer cells, and associated with malignant behavior of cancer cells; however, the fundamental molecular mechanism by which dysadherin drives aggressive phenotypes of cancer is not yet fully determined. Methods: To get a mechanistic insight, we explored the physiological relevance of dysadherin on intestinal tumorigenesis using dysadherin knockout mice and investigated its impact on clinicopathological features in patients with advanced colorectal cancer (CRC). Next, to discover the downstream signaling pathways of dysadherin, we applied bioinformatic analysis using gene expression data of CRC patient tumors and dysadherin knockout cancer cells. Additionally, comprehensive proteomic and molecular analyses were performed to identify dysadherin-interacting proteins and their functions. Results: Dysadherin deficiency suppressed intestinal tumorigenesis in both genetic and chemical mouse models. Moreover, increased dysadherin expression in cancer cells accounted for shorter survival in CRC patients. Comprehensive bioinformatics analyses suggested that the effect of dysadherin deletion is linked to a reduction in the extracellular matrix receptor signaling pathway. Mechanistically, the extracellular domain of dysadherin bound fibronectin and enhanced cancer cell adhesion to fibronectin, facilitating the activation of integrin-mediated mechanotransduction and leading to yes-associated protein 1 activation. Dysadherin-fibronectin interaction promoted cancer cell growth, survival, migration, and invasion, effects collectively mediated the protumor activity of dysadherin. Conclusion: Our results highlight a novel function of dysadherin as a driver of mechanotransduction that stimulates CRC progression, providing a potential therapy strategy for CRC.

Stratification of chemotherapy-treated stage III colorectal cancer patients using multiplexed imaging and single-cell analysis of T-cell populations.

Colorectal cancer (CRC) has one of the highest cancer incidences and mortality rates. In stage III, postoperative chemotherapy benefits <20% of patients, while more than 50% will develop distant metastases. Biomarkers for identification of patients at increased risk of disease recurrence following adjuvant chemotherapy are currently lacking. In this study, we assessed immune signatures in the tumor and tumor microenvironment (TME) using an in situ multiplexed immunofluorescence imaging and single-cell analysis technology (Cell DIVETM) and evaluated their correlations with patient outcomes. Tissue microarrays (TMAs) with up to three 1 mm diameter cores per patient were prepared from 117 stage III CRC patients treated with adjuvant fluoropyrimidine/oxaliplatin (FOLFOX) chemotherapy. Single sections underwent multiplexed immunofluorescence staining for immune cell markers (CD45, CD3, CD4, CD8, FOXP3, PD1) and tumor/cell segmentation markers (DAPI, pan-cytokeratin, AE1, NaKATPase, and S6). We used annotations and a probabilistic classification algorithm to build statistical models of immune cell types. Images were also qualitatively assessed independently by a Pathologist as 'high', 'moderate' or 'low', for stromal and total immune cell content. Excellent agreement was found between manual assessment and total automated scores (p < 0.0001). Moreover, compared to single markers, a multi-marker classification of regulatory T cells (Tregs: CD3+/CD4+FOXP3+/PD1-) was significantly associated with disease-free survival (DFS) and overall survival (OS) (p = 0.049 and 0.032) of FOLFOX-treated patients. Our results also showed that PD1- Tregs rather than PD1+ Tregs were associated with improved survival. These findings were supported by results from an independent FOLFOX-treated cohort of 191 stage III CRC patients, where higher PD1- Tregs were associated with an increase overall survival (p = 0.015) for CD3+/CD4+/FOXP3+/PD1-. Overall, compared to single markers, multi-marker classification provided more accurate quantitation of immune cell types with stronger correlations with outcomes.

FLINO: a new method for immunofluorescence bioimage normalization.

MOTIVATION: Multiplexed immunofluorescence bioimaging of single-cells and their spatial organization in tissue holds great promise to the development of future precision diagnostics and therapeutics. Current multiplexing pipelines typically involve multiple rounds of immunofluorescence staining across multiple tissue slides. This introduces experimental batch effects that can hide underlying biological signal. It is important to have robust algorithms that can correct for the batch effects while not introducing biases into the data. Performance of data normalization methods can vary among different assay pipelines. To evaluate differences, it is critical to have a ground truth dataset that is representative of the assay. RESULTS: A new immunoFLuorescence Image NOrmalization method is presented and evaluated against alternative methods and workflows. Multiround immunofluorescence staining of the same tissue with the nuclear dye DAPI was used to represent virtual slides and a ground truth. DAPI was restained on a given tissue slide producing multiple images of the same underlying structure but undergoing multiple representative tissue handling steps. This ground truth dataset was used to evaluate and compare multiple normalization methods including median, quantile, smooth quantile, median ratio normalization and trimmed mean of the M-values. These methods were applied in both an unbiased grid object and segmented cell object workflow to 24 multiplexed biomarkers. An upper quartile normalization of grid objects in log space was found to obtain almost equivalent performance to directly normalizing segmented cell objects by the middle quantile. The developed grid-based technique was then applied with on-slide controls for evaluation. Using five or fewer controls per slide can introduce biases into the data. Ten or more on-slide controls were able to robustly correct for batch effects. AVAILABILITY AND IMPLEMENTATION: The data underlying this article along with the FLINO R-scripts used to perform the evaluation of image normalizations methods and workflows can be downloaded from https://github.com/GE-Bio/FLINO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.