Lymphocyte Tumor Research Articles

Dual-Armed Oncolytic Myxoma Virus Encoding IFN-γ and CD47 Promotes Lymphocyte Infiltration and Tumor Suppression of Syngeneic Murine Melanoma.

Myxoma virus (MyxV) is a rabbit-specific poxvirus. However, its ability to selectively target tumor cells has established it as a safe and effective anticancer therapy. To strengthen its preclinical efficacy, transgenes that can prolong cancer cell infection and enhance anti-tumor effector functions are currently being investigated. We engineered MyxV armed with CD47, to turn on a 'do not eat me' signal within infected cells with actively replicating viruses, and with IFN-γ to further activate host immune anticancer responses. Tumor suppressive activities were significantly enhanced by the dual-armed MyxV_CD47/IFN-γ compared to parental MyxV or single-armed MyxV_CD47 or MyxV_IFN-γ. In addition, significant increases in IFN-γ+ CD8+T-cells and CD4+ T-cells populations within tumor-infiltrating lymphocytes (TIL) were observed after MyxV_CD47/IFN-γ treatment. Notably, all groups treated with MyxV showed a marked reduction in Foxp3+ CD4+ regulatory T-cells (Tregs) within TIL. We also show that MyxV infection induces PD-L1 up-regulation in cancer cells, and combinational treatment of MyxV with anti-mouse PD-L1 antibodies (αPD-L1) further controlled tumor burden and increased survival in the syngeneic melanoma model B16F10. Our data demonstrate that a CD47 and IFNγ dual-armed MyxV is an effective oncolytic viral immunotherapeutic. These findings strongly support further preclinical investigations to develop next-generation MyxV-based immunotherapy approaches.

Nuclear PARP1-Targeted Photosensitizer as a Dual-Mode DNA-Damaging Agent and Immune Activator for Tumor Ablation.

Photodynamic therapy is a promising cancer therapeutic method that can damage DNA via photoinduced reactive oxygen species production. However, tumor cells can initiate DNA repair pathways to resist oxidative damage. In this study, a nuclear-targeted photosensitizer PARP-PS with a poly (ADP-ribose) polymerase 1 (PARP1) inhibitory effect is developed based on the reported PARP1 inhibitor, rucaparib. As a dual-mode DNA-damaging agent, PARP-PS damages DNA upon photoirradiation and enhances oxidative DNA damage by blocking the DNA repair pathway via PARP1 inhibition and degradation. Both in vitro and in vivo investigations demonstrate that PARP-PS exhibits high antitumor activity with few side effects in breast cancer. In addition, PARP-PS can act as an immunogenic cell death inducer to activate immune responses characterized by the promotion of cytotoxic T lymphocyte activation and tumor infiltration. Therefore, PARP-PS is a potential multimodal antitumor agent with synergistic phototherapeutic, chemotherapeutic, and immunotherapeutic effects.

EFFECT OF PEGYLATED GRAPHENE OXIDE NANOPARTICLES ON THE METABOLISM OF JURKAT CELLS

The effect of graphene oxide (GO) nanoparticles of 100–200 nm size coated with linear (LP-GO) and branched (BP-GO) polyethylene glycol at concentrations of 5 and 25 μg/mL on the metabolism of Jurkat tumor cells was studied. It was found that LP-GO nanoparticles at a concentration of 25 μg/mL can enhance basal glycolysis of Jurkat T lymphocyte tumor cell line cells, while LP-GO and BP-GO at the same concentration can reduce the indicators of compensatory glycolysis. Despite this, GO nanoparticles coated with linear and branched PEG at a concentration of 5 μg/mL do not have pronounced effects on oxidative phosphorylation and glycolysis of Jurkat cells and could therefore be safe for activated T cells.

CCL21-DC in situ vaccination in murine NSCLC overcomes resistance to immunotherapy and generates systemic tumor-specific immunity

BackgroundDespite recent advances in immunotherapy, many patients with non-small cell lung cancer (NSCLC) do not respond to immune checkpoint inhibitors (ICI). Resistance to ICI may be driven by suboptimal priming...

O-104 - HLA I shields tumor lymphocytes from NK cell-mediated elimination in the skin

O-104 - HLA I shields tumor lymphocytes from NK cell-mediated elimination in the skin

367. SPATIAL ORGANIZATION OF TUMOR-INFILTRATING LYMPHOCYTES PREDICTS PROGNOSIS OF PATIENTS WITH ESOPHAGEAL CANCER RECEIVING IMMUNOTHERAPY—A DEEP-LEARNING APPROACH

Abstract Background Neoadjuvant immunotherapy plus chemotherapy has shown satisfying efficacy and manageable safety in locally advanced esophageal squamous cell carcinoma (ESCC) patients. Tumor-infiltrating lymphocytes (TILs) have been shown to be associated with the prognosis of various cancer types. It is unknown whether these TILs-associated characteristics can be adopted as a reliable prognostic biomarker for immunotherapy-based regimen. The current study aimed to assess the prognostic power of spatial organization of TILs in patients with advanced ESCC treated with immunochemotherapy. Methods In this retrospective, multicenter cohort study, pathologically confirmed locally advanced ESCC that was potentially resectable after neoadjuvant immunochemotherapy were included. Image segmentation was performed using UNet++ algorithm and H&E-stained nuclei were segmented using the StarDist deep-learning image segmentation. For the nuclei classification task, we choose to train and validate the classic convolutional neural network (CNN) Resnet50. We calculated tumor density and TiLs density in the tumor region (T_TiLs), TILs in the peritumoral region (P_TiLs) as well as TiLs density in the stromal region (S_TiLs). Based on the relative position relationship of tumor cells and lymphocytes, we subclassified the TILs spatial patterns into TILs-dominant, TILs-infiltrating, and TILs-circulating. Results Among the enrolled 86 patients, the male to female ratio approached 4:1. In this study, the mean IoU (mIoU) for nuclei segmentation is 0.9369 and the mean Dice coefficient is 0.9209. The areas under curve (AUC) for lymphocyte, tumor cell, and stromal cells classification are 0.92, 0.90 and 0.86, respectively. Through univariate analysis, TILs in tumor region (HR = 1.285, 95% CI: 1.042–1.586, p = 0.019), and TILs spatial organization (HR = 3.652, 95% CI: 1.216–10.967, p = 0.021) were identified as significant prognostic factors for OS. Multivariate analysis further revealed TILs in tumor region as the independent prognostic factor (HR = 1.248, 95% CI: 1.006–1.547, p = 0.044). Discussion The present study indicates that spatial organization and T_TILs are significant prognostic factors for ESCC patients receiving neoadjuvant immunochemotherapy. Future prospective studies with large sample size are needed to further validate the prognostic role of interaction between TILs spatial characteristic and distribution density in predicting overall survival.

Study of Neutrophil–Lymphocyte Ratio, Interleukin-6 (IL-6) and Tumor Necrosis Factor-Alpha (TNF-α) in Type 2 Diabetes with Diabetic Nephropathy

Abstract Background Diabetic kidney disease is defined by characteristic structural and functional changes. The predominant structural changes include mesangial expansion, glomerular basement membrane thickening, podocyte injury, and, ultimately, glomerular sclerosis. The major clinical manifestations of diabetic nephropathy are albuminuria, hematuria (less often), and, in many patients, progressive chronic kidney disease, which can be slowed with optimal therapy. Objective to assess the Neutrophil-lymphocyte Ratio, Interleukin- 6 (IL-6) and tumor necrosis factor-alpha (TNF-α) in Type 2 Diabetes with Diabetic Nephropathy. Patients and Methods In Our study We collect 90 subjects with their ages ranging from 35-70, selected from Internal Medicine and Endocrinology outpatient clinics and the inpatient department at Ain Shams University Hospitals. Results As regards NLR, there were statistically significant and direct correlations between NLR and IL6, TNF, serum BUN, serum creatinine and albumin to creatinine ratio, while significant and indirect correlation with EGFR. As regards IL6, there were statistically significant and direct correlations between IL6 and TNF, serum BUN, serum creatinine and albumin to creatinine ratio, while significant and indirect correlation with BMI and EGFR. As regards TNF, there were statistically significant and direct correlations between TNF and serum BUN and albumin to creatinine ratio. There is no statistical difference between the studied groups as regard sex, age, BMI, SBP, DBP. Conclusion The current study could find that NLR, IL-6 and TNF-α were significantly associated with albuminuria in Type 2 Diabetic patients with DN and that they can be used as evident biomarkers in assessing the progression of deteriorating renal function and different stages of renal disease in patients with DN.

Identification of a novel combination treatment strategy in clear cell renal cell carcinoma stem cells with shikonin and ipilimumab.

Management of clear cell renal cell carcinoma (ccRCC) has changed rapidly in recent years with the advent of immune checkpoint inhibitors (ICIs). However, only a limited number of patients can sustainably respond to immune checkpoint inhibitors and many patients develop resistance to therapy, creating an additional need for therapeutic strategies to improve the efficacy of systemic therapies. Binding probability and target genes prediction using online databases, invasion, migration, and apoptosis assays as well as the inhibition of cancer stem cells (CSCs) markers in ccRCC cell lines were used to select the most promising phytochemicals (PTCs). Mixed lymphocyte tumor cell culture (MLTC) system and flow cytometry were performed to confirm the potential combination strategy. The potential immunotherapeutic targets and novel CSC markers were identified via the NanoString analysis. The mRNA and protein expression, immune signatures as well as survival characteristics of the marker in ccRCC were analyzed via bioinformation analysis. Shikonin was selected as the most promising beneficial combination partner among 11 PTCs for ipilimumab for the treatment of ccRCC patients due to its strong inhibitory effect on CSCs, the significant reduction of FoxP3+ Treg cells in peripheral blood mononuclear cells (PBMCs) of patients and activation of the endogenous effector CD3+CD8+ and CD3+CD4+ T cells in response to the recognition of tumor specific antigens. Based on NanoString analysis VCAM1, CXCL1 and IL8 were explored as potential immunotherapeutic targets and novel CSC markers in ccRCC. The expression of VCAM1 was higher in the tumor tissue both at mRNA and protein levels in ccRCC compared with normal tissue, and was significantly positively correlated with immune signatures and survival characteristics in ccRCC patients. We propose that a combination of shikonin and ipilimumab could be a promising treatment strategy and VCAM1 a novel immunotherapeutic target for the treatment of ccRCC.

Deep learning based quantitative models to distinguish tumoral and stromal tumor-infiltrating lymphocytes and the prognosis patients with high-grade serous ovarian cancer.

84 Background: The better prognostic value of tumor-infiltrating lymphocytes (TILs) has been reported in high-grade serous ovarian cancer (HGSOC). However, the TILs evaluation of previous reports largely depends on manual quantification based on a visual assessment within limited section of pathological slides or tissue microarrays, which is subject to inter-observer variability. Since tumor immune microenvironment (TIME) of HGSOC is highly heterogeneous, there is a need to quantify TILs in large areas of pathological slides in an objective and time-saving manner. Here we present an AI-powered quantification method to distinguish tumoral TILs and stromal TILs using hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) of HGSOC. Methods: 161 H&E stained WSIs of HGSOC patients treated at our hospital between 1998 and 2021 were prepared, and by using these WSIs we generated two AI-powered models. Initially, a TILs detection model (TIL-model) was created using a publicly available dataset of 86104 pan-cancer TILs images of 100 × 100 pixels at magnification of x200 (Saltz et al., 2018, Cell Reports). Secondary, a tumor and stroma segmentation model (T/S seg-model) was developed using 136962 patches of 224 × 224 pixels at magnification of x50 which were manually annotated with tumoral regions and stromal regions in 102 H&E stained WSIs of HGSOC from The Cancer Genome Atlas (TCGA). Deep convolutional neural networks of NASNet-Large for the TIL-model and TransUNet for the T/S seg-model were used. TILs density score (number of TILs positive tiles per tumor area) of each sample was calculated, and association between TILs density score and the prognosis was investigated. Results: The established models achieved high accuracy: the TIL-model showed an area under the curve (AUC) value of 0.896, and the T/S seg-model showed an intersection over union value of 0.967. By combining the two models, we successfully distinguished tumoral TILs and stromal TILs. Using our dataset of 161 WSIs, we split the patients by TILs density score at top quartile into high tumoral TILs subgroup (n=40) and low tumoral TILs subgroup (n=121). High tumoral TILs subgroup showed significantly longer overall survival (OS) and progression free survival (PFS) (OS: median 70 months vs not reached, p < 0.005. PFS: median 34 months vs 21 months, p = 0.02). Conclusions: We developed deep learning based pathological AI models to detect TILs and tumors using H&E stained WSIs, which achieved to quantify tumoral and stromal TILs. The objective assessment of TILs using these models will lead to the development of clinically applicable tools for the evaluation of the immune status in HGSOC.

Detailed characterization of PD-1/PD-L1 and CTLA4 expression and tumor-infiltrating lymphocytes in yolk sac tumors

BackgroundImmune checkpoint blockade (ICB) is considered as a promising approach for cancer treatment. However, the potency of ICB therapy in yolk sac tumors (YSTs) has not been confirmed, and the comprehensive analysis of tumor immune microenvironment and the expression of PD-1/PD-L1 and CTLA4 were also not thoroughly evaluated. MethodsImmunohistochemistry was performed in formalin-fixed, paraffin-embedded tumor specimens from 23 YSTs patients to detect the density and distribution of tumor-infiltrating T cells, tertiary lymphoid structures (TLSs), as well as the expression of PD-1/PD-L1 and CTLA4. ResultsOverall, more than half (61 %) of all patients exhibited an immune-desert phenotype based on CD3+ T cells. PD-1 expression was identified in five tumor samples (21.7 %), and PD-L1 expression exhibited a different positive rate in tumor cells (TCs) and tumor-infiltrating lymphocytes (TILs) (39.1 % and 17.4 %). Noteworthily, the rate of positive CTLA4 expression in both TCs and TILs was markedly higher (69.6 % and 56.5 %) than those of PD-1 and PD-L1 expression. Furthermore, TLSs were observed in 21.74 % of all tissues, and samples with TLSs exhibited significantly higher densities of TILs and higher expression of immune checkpoint molecules, particularly PD-1/PD-L1. In addition, tumors located in testes also exhibited a higher density of TILs and higher expression of immune checkpoint molecules. ConclusionGenerally a high frequency of CTLA4 expression was found, PD-1/PD-L1 expression, the immune-inflamed phenotype, and TLSs were low frequency in YSTs, however, YSTs in testes showed a higher density of TILs and higher expression of immune checkpoint molecules.

Diverging prognostic effects of CD155 and CD73 expressions in locally advanced triple-negative breast cancer.

Immune checkpoint inhibition, combined with novel biomarkers, may provide alternative pathways for treating chemotherapy-resistant triple-negative breast cancer (TNBC). This study investigates the expression of new immune checkpoint receptors, including CD155 and CD73, which play a role in T and natural killer (NK) cell activities, in patients with residual TNBC after neoadjuvant chemotherapy (NAC). The expression of biomarkers was immunohistochemically examined by staining archival tissue from surgical specimens (n = 53) using specific monoclonal antibodies for PD-L1, CD155, and CD73. Of those, 59.2% (29/49) were found to be positive (>1%) for PD-L1 on the tumour and tumour-infiltrating lymphocytes (TILs), while CD155 (30/53, 56.6%) and CD73 (24/53, 45.3%) were detected on tumours. Tumour expressions of CD155 and CD73 significantly correlated with PD-L1 expression on the tumour (p = 0.004 for CD155, p = 0.001 for CD73). Patients with CD155 positivity ≥10% were more likely to have a poor chemotherapy response, as evidenced by higher MDACC Residual Cancer Burden Index scores and Class II/III than those without CD155 expression (100% vs 82.6%, p = 0.03). At a median follow-up time of 80 months (range, 24-239), patients with high CD73 expression showed improved 10-year disease-free survival (DFS) and disease-specific survival (DSS) rates compared to those with low CD73 expression. In contrast, patients with CD155 (≥10%) expression exhibited a decreasing trend in 10-year DFS and DSS compared to cases with lower expression, although statistical significance was not reached. However, patients with coexpression of CD155 (≥10%) and low CD73 were significantly more likely to have decreased 10-year DFS and DSS rates compared to others (p = 0.005). These results demonstrate high expression of CD73 and CD155 in patients with residual tumours following NAC. CD155 expression was associated with a poor response to NAC and poor prognosis in this chemotherapy-resistant TNBC cohort, supporting the use of additional immune checkpoint receptor inhibitor therapy. Interestingly, the interaction between CD155 and CD73 at lower levels resulted in a worse outcome than either marker alone, which calls for further investigation in future studies.

Enhanced bypass of PD-L1 translation reduces the therapeutic response to mTOR kinase inhibitors

Increased PD-L1 expression in cancer cells is known to enhance immunosuppression, but the mechanism underlying PD-L1 upregulation is incompletely characterized. We show that PD-L1 expression is upregulated through internal ribosomal entry site (IRES)-mediated translation upon mTORC1 inhibition. We identify an IRES element in the PD-L1 5'-UTR that permits cap-independent translation and promotes continuous production of PD-L1 protein despite effective inhibition of mTORC1. eIF4A is found to be a key PD-L1 IRES-binding protein that enhances PD-L1 IRES activity and protein production in tumor cells treated with mTOR kinase inhibitors (mTORkis). Notably, treatment with mTORkis invivo elevates PD-L1 levels and reduces the number of tumor-infiltrating lymphocytes in immunogenic tumors, but anti-PD-L1 immunotherapy restores antitumor immunity and enhances the therapeutic efficacy of mTORkis. These findings report a molecular mechanism for regulating PD-L1 expression through bypassing mTORC1-mediated cap-dependent translation and provide a rationale for targeting PD-L1 immune checkpoint to improve mTOR-targeted therapy.

PD-L1 and TILs expression and their association with clinicopathological characteristics in Vietnamese women with primary invasive breast cancer.

Tumor-infiltrating lymphocytes (TILs) and programmed death ligand 1 (PD-L1) are promising new factors in the prognosis and prediction of breast cancer patients. Our study evaluated the prevalence of expression of TILs on hematoxylin and eosin (H&E) slides, PD-L1 expression on immunohistochemistry, and their association with clinicopathological characteristics in Vietnamese women with invasive breast cancer. This study was conducted on 216 women with primary invasive breast cancer. The evaluation of TILs on the HE slides was based on the International TILs Working Group 2014 recommendation. PD-L1 protein expression was determined using the Combined Positive Score, the number of tumor cells, lymphocytes, and macrophages stained by PD-L1 divided by the total viable tumor cells multiplied by 100. Based on the cutoff of 11%, the prevalence of TILs expression was 35.6%, of which highly expressed TILs (≥50%) accounted for 15.3%. Postmenopausal women and those who had a body mass index of 25 kg/m2 or greater had a higher odds of having TILs expression. However, patients who had the expression of Ki-67, HER-positive molecular subtype, and triple-negative subtype were more likely to have TILs expression. The prevalence of PD-L1 expression was 30.1%. A significantly higher odds of having PD-L1 was found in patients who had a history of benign breast disease, self-detected tumor and had TILs expression. The expression of TILs and PD-L1 is common in Vietnamese women with invasive breast cancer. Because of the importance of these expressions, routine evaluation to find women who had TILs and PD-L1 is needed so that treatment and prognosis can be optimized. Such routine evaluation can be targeted to those who had a high-risk profile found in this study.

Apparent diffusion coefficient correlates with different histopathological features in several intrahepatic tumors

ObjectivesTo investigate associations between apparent diffusion coefficient (ADC) and cell count, Ki 67, tumor-stroma ratio (TSR), and tumoral lymphocytes in different hepatic malignancies.MethodsWe identified 149 cases with performed liver biopsies: hepatocellular cancer (HCC, n = 53), intrahepatic cholangiocarcinoma (iCC, n = 29), metastases of colorectal cancer (CRC, n = 24), metastases of breast cancer (BC, n = 28), and metastases of pancreatic cancer (PC, n = 15). MRI was performed on a 1.5-T scanner with an axial echo-planar sequence. MRI was done before biopsy. Biopsy images of target lesions were selected. The cylindrical region of interest was placed on the ADC map of target lesions in accordance with the needle position on the biopsy images. Mean ADC values were estimated. TSR, cell counts, proliferation index Ki 67, and number of tumor-infiltrating lymphocytes were estimated. Spearman’s rank correlation coefficients and intraclass correlation coefficients were calculated.ResultsInter-reader agreement was excellent regarding the ADC measurements. In HCC, ADC correlated with cell count (r = − 0.68, p < 0.001) and with TSR (r = 0.31, p = 0.024). In iCC, ADC correlated with TSR (r = 0.60, p < 0.001) and with cell count (r = − 0.54, p = 0.002). In CRC metastases, ADC correlated with cell count (r = − 0.54 p = 0.006) and with Ki 67 (r = − 0.46, p = 0.024). In BC liver metastases, ADC correlated with TSR (r = 0.55, p < 0.002) and with Ki 67 (r = − 0.51, p = 0.006). In PC metastases, no significant correlations were found.ConclusionsADC correlated with tumor cellularity in HCC, iCC, and CRC liver metastases. ADC reflects TSR in BC liver metastases, HCC, and iCC. ADC cannot reflect intratumoral lymphocytes.Clinical relevance statementThe present study shows that the apparent diffusion coefficient can be used as a surrogate imaging marker for different histopathological features in several malignant hepatic lesions.Key Points• ADC reflects different histopathological features in several hepatic tumors.• ADC correlates with tumor cellularity in HCC, iCC, and CRC metastases.• ADC strongly correlates with tumor-stroma ratio in BC metastases and iCC.

CXCL8 and the peritoneal metastasis of ovarian and gastric cancer.

CXCL8 is the most representative chemokine produced autocrine or paracrine by tumor cells, endothelial cells and lymphocytes. It can play a key role in normal tissues and tumors by activating PI3K-Akt, PLC, JAK-STAT, and other signaling pathways after combining with CXCR1/2. The incidence of peritoneal metastasis in ovarian and gastric cancer is extremely high. The structure of the peritoneum and various peritoneal-related cells supports the peritoneal metastasis of cancers, which readily produces a poor prognosis, low 5-year survival rate, and the death of patients. Studies show that CXCL8 is excessively secreted in a variety of cancers. Thus, this paper will further elaborate on the mechanism of CXCL8 and the peritoneal metastasis of ovarian and gastric cancer to provide a theoretical basis for the proposal of new methods for the prevention, diagnosis, and treatment of cancer peritoneal metastasis.

DNA mismatch repair in cancer immunotherapy.

Tumors defective in DNA mismatch repair (dMMR) exhibit microsatellite instability (MSI). Currently, patients with dMMR tumors are benefitted from anti-PD-1/PDL1-based immune checkpoint inhibitor (ICI) therapy. Over the past several years, great progress has been made in understanding the mechanisms by which dMMR tumors respond to ICI, including the identification of mutator phenotype-generated neoantigens, cytosolic DNA-mediated activation of the cGAS-STING pathway, type-I interferon signaling and high tumor-infiltration of lymphocytes in dMMR tumors. Although ICI therapy shows great clinical benefits, ∼50% of dMMR tumors are eventually not responsive. Here we review the discovery, development and molecular basis of dMMR-mediated immunotherapy, as well as tumor resistant problems and potential therapeutic interventions to overcome the resistance.

Quantitative 3D assessment of the lung cancer microenvironment using multi-resolution open-top light-sheet microscopy.

2616 Background: Non-small cell lung cancer (NSCLC) tissue is a valuable resource for diagnosis, treatment planning, and drug development. Current 2D histopathological techniques introduce under-sampling error (i.e., a single 5 µm section represents 0.5% of a 1 mm thick biopsy), interobserver variability, and failure to capture the biology contained within the entire tissue sample. We have developed a suite of technologies to stain, chemically clarify, image, visualize, and analyze entire, intact lung tissue samples. Herein, we present analysis methods for comprehensive 3D assessment of intact NSCLC tissue. Methods: Human NSCLC tissue, stored frozen in optimal cutting temperature (OCT) compound, was fixed in 4% paraformaldehyde, stained with nuclear (TOPRO-3) and general protein (Eosin) fluorescent dyes, and optically cleared using a modified iDISCO protocol with ethyl cinnamate as the refractive index matching solution. Twenty tissue samples measuring 1-5 mm3 in volume were imaged at 2 µm/pixel resolution with a hybrid open-top light-sheet microscope. Smaller regions of interest (ROIs) with interesting pathologic features were re-imaged at higher resolution, 0.17 µm/pixel. Visualization and analysis was performed using Aivia software, custom spatial analysis software and python scripts. Results: All NSCLC tissue samples were successfully imaged in 3D at both low and high resolution. Computational approaches, such as machine learning, were used to segment and classify tumor cells and lymphocytes within the high resolution ROIs. In one example we quantified a 0.0045 mm3 ROI containing 1x109 voxels. We segmented 1,474 unique objects, and classified 683 (46%) of the objects as lymphocytes and 309 (20%) of the cells as tumor cells. We found that on average the lymphocytes were within 12 µm of the nearest tumor cell. Additionally the tissue was broken into separate lymphocyte dense (58% of volume) and tumor dense regions (42% of volume). Further analysis is in progress to quantify more features, such as tertiary lymphoid structures, stromal cells, and fibrosis over the full 20 sample dataset. Conclusions: We successfully implemented 3D machine learning analysis pipelines using images from intact NSCLC tissue samples measuring up to 5 mm3. The imaging was performed using our custom hybrid open-top light-sheet microscope. This novel method enables us to identify and quantify key histological features such as tumor cells and lymphocytes within the tumor microenvironment. In addition, machine learning driven algorithms clustered cells into distinct tissue regions in 3D which enables a more precise assessment of disease state and heterogeneity. Further investigation is ongoing to link these results to patient outcomes.

Deep learning-based ensemble model using hematoxylin and eosin (H&amp;E) whole slide images (WSIs) for the prediction of MET mutations in non-small cell lung cancer (NSCLC).

e13578 Background: The MET proto-oncogene is involved in tumorigenesis and progression and has emerged as an attractive targetable genomic alteration in NSCLC. However, it has not been actively tested in NSCLC due to the lack of a cost-effective screening tool. We developed a deep-learning based model to predict genomic profiles from H&amp;E WSI and applied it to MET pathologic mutations in NSCLC. The prediction model is based on an ensemble model trained not solely on H&amp;E images but also on multi-layered semantic contents that were produced by a pre-trained AI analyzer, Lunit SCOPE IO. Methods: The model was trained on the MET aberration (exon 14 skipping, n=191; pathogenic mutation, n=109) and paired wild-type dataset (n=500). To extract deep features from raw H&amp;E images, a self-supervised vision transformer was used, and an AI-based pathology profiling analyzer extracted semantic contents such as the spatial information of tumor cells, lymphocytes, cancer epithelium, and cancer stroma. A set of classifiers was trained based on the two features, and the ensemble of these features was used to improve robustness. Following cross-validation, the model was applied to an independent clinical dataset with MET sequencing results from The Cancer Genome Atlas (TCGA) LUAD and LUSC datasets (n=914), Samsung Medical Center (SMC, n=361), and Chonnam National University Hospital (CNUH, n=54). Results: The best cross-validation performances of the models predicting MET aberration measured by mean area under the receiver operating characteristic curve (AUROC) were 0.772 when trained by only H&amp;E images (HE-only), 0.788 by AI semantic content with MLP classifier (AISC-MLP), and 0.803 by AISC with random forest (AI-RF), respectively. An ensemble of the three models showed an increased AUROC of 0.837 in the training dataset by cross-validation. These models were applied to the external validation dataset (n=1,329), including 20 (1.5%) MET exon 14 skipping and known pathologic mutations. The mean AUROC to predict MET aberration by the ensemble model was 0.817 with 95% sensitivity, 64.7% specificity. The AUROC of TCGA, SMC, and CNUH cohorts were 0.815, 0.802, and 0.812, respectively. Conclusions: An AI-based ensemble model combining H&amp;E images with semantic contents extracted from pre-developed AI models significantly improved the accuracy and robustness of MET pathogenic mutation prediction using an H&amp;E sample in NSCLC. These findings allow for cost-effective screening for MET alterations.

Inflammation-related nomogram for predicting survival of patients with unresectable hepatocellular carcinoma received conversion therapy

The efficacy of conversion therapy for patients with unresectable hepatocellular carcinoma (HCC) is a common clinical concern.To analyse the prognostic factors of overall survival (OS) in patients with unresectable HCC who received conversion therapy.One hundred and fifty patients who met the inclusion criteria were enrolled and divided into a training cohort (n = 120) and a validation cohort (n = 30). Using the independent risk factors in the training cohort, a nomogram model was constructed to predict OS for patients treated with transarterial chemoembolization following hepatic resection. The nomogram was internally validated with the bootstrapping method. The predictive performance of nomogram was assessed by Harrell's concordance index (C-index), calibration plot and time-dependent receiver operating characteristic curves and compared with six other conventional HCC staging systems.Multivariate Cox analysis identified that albumin, blood urea nitrogen, gamma-glutamyl transpeptidase to platelet ratio, platelet to lymphocyte ratio, macrovascular invasion and tumour number were the six independent prognostic factors correlated with OS in nomogram model. The C-index in the training cohort and validation cohort were 0.752 and 0.807 for predicting OS, which were higher than those of the six conventional HCC staging systems (0.563 to 0.715 for the training cohort and 0.458 to 0.571 for the validation cohort). The calibration plots showed good consistency between the nomogram prediction of OS and the actual observations of OS. Decision curve analyses indicated satisfactory clinical utility. With a total nomogram score of 196, patients were accurately classified into low-risk and high-risk groups. Furthermore, we have deployed the model into online calculators that can be accessed for free at https://ctmodelforunresectablehcc.shinyapps.io/DynNomapp/.The nomogram achieved optimal individualized prognostication of OS in HCC patients who received conversion therapy, which could be a useful clinical tool to help guide postoperative personalized interventions and prognosis judgement.

Diagnosis and management of vitreoretinal lymphoma: present and future treatment perspectives.

Intraocular lymphoma (IOL) is a rare malignant intraocular lymphocytic tumor that mimics uveitis. IOL is anatomically classified into vitreoretinal lymphoma (VRL) and uveal lymphoma; most IOLs are VRLs, while uveal lymphoma is rare. VRL is highly malignant, with 60%-85% of patients developing central nervous system (CNS) lymphoma; primary VRL (PVRL) is an ocular disease with poor prognosis. We aimed to review the management and both current and future treatments for VRL. VRL diagnosis is based on the results of cytopathological examination using vitreous biopsy. However, the positive ratio of vitreous cytology remains 29%-70%. A combination of adjunctive tests may improve diagnostic accuracy, but as yet no gold-standard regimen has been established. Methotrexate intravitreal injections are effective in controlling ocular lesions; however, this treatment allows CNS dissemination. The efficacy of systemic chemotherapy in suppressing CNS dissemination has been recently debated. A multicenter prospective study with a unified treatment protocol is required to clarify this issue. In addition, establishing a treatment protocol for elderly patients and those with poor general health is necessary. Moreover, relapsed/refractory VRL and secondary VRL are more difficult to treat than PVRL because they are prone to recurrence. Ibrutinib, lenalidomide with or without rituximab, and temozolomide are promising treatments for relapsed/refractory VRL. In Japan, Bruton's tyrosine kinase (BTK) inhibitors have been approved for treating refractory CNS lymphoma. Furthermore, a randomized prospective study of tirabrutinib, a highly selective BTK inhibitor, is ongoing for evaluating the suppressing of CNS progression in patients with PVRL.