Density Of Tumor-infiltrating Lymphocytes Research Articles

The Possible Role of Anti- and Protumor-Infiltrating Lymphocytes in Pathologic Complete Response in Early Breast Cancer Patients Treated with Neoadjuvant Systemic Therapy.

The tumor microenvironment, composed of pro- and antitumor immune cells, affects cancer cell behavior. We aimed to evaluate whether tumor-infiltrating lymphocyte (TIL) density and TIL subtypes in core biopsies at the diagnosis of breast cancer patients could predict a pathologic complete response (pCR; ypT0/is ypN0) from neoadjuvant systemic therapy (NST). The TIL subtypes were determined based on the proportions of presumably antitumor (CD8+, CXCL13+) and protumor (PD-1+, FOXP3+) immune cells. A prospective, noninterventional study, including 171 participants undergoing NST, was performed. The median TIL density for the entire cohort was 10% (IQR: 3.5-23.8), and 59 (35%) patients achieved pCR. TIL density was positively associated with pCR (univariately and multivariably). In the multivariable logistic regression model, TIL density was an independent predictor of pCR (p = 0.012, OR 1.27; 95% CI 1.05-1.54) when controlled for age (p = 0.232), Ki-67 (p = 0.001), node-negative status (p = 0.024), and HER2+/triple negative vs. luminal B-like subtype (p < 0.001). In our sample, higher proportions of PD-1+ TILs and FOXP3+ TILs were associated with a higher probability of pCR but the association was not statistically significant and we could not make any conclusions on the direction of associations in the model with all four biomarkers. In the exploratory multivariable analysis, we showed that only higher CD8+ TILs were associated with pCR. In conclusion, TIL density and its subtypes are associated with pCR.

Tumor-Infiltrating Lymphocyte Recognition in Primary Melanoma by Deep Learning Convolutional Neural Network

The presence of tumor-infiltrating lymphocytes (TILs) is associated with a favorable prognosis of primary melanoma (PM). Recently, artificial intelligence (AI)-based approach in digital pathology was proposed for the standardized assessment of TILs on hematoxylin and eosin-stained whole slide images (WSIs). Herein, the study applied a new convolution neural network (CNN) analysis of PM WSIs to automatically assess the infiltration of TILs and extract a TIL score. A CNN was trained and validated in a retrospective cohort of 307 PMs including a training set (237 WSIs, 57,758 patches) and an independent testing set (70 WSIs, 29,533 patches). An AI-based TIL density index (AI-TIL) was identified after the classification of tumor patches by the presence or absence of TILs. The proposed CNN showed high performance in recognizing TILs in PM WSIs, showing 100% specificity and sensitivity on the testing set. The AI-based TIL index correlated with conventional TIL evaluation and clinical outcome. The AI-TIL index was an independent prognostic marker associated directly with a favorable prognosis. A fully automated and standardized AI-TIL appeared to be superior to conventional methods at differentiating the PM clinical outcome. Further studies are required to develop an easy-to-use tool to assist pathologists to assess TILs in the clinical evaluation of solid tumors.

Abstract PO-031: Integrated bioinformatics and functional spatial analysis platform for the discovery of predictive biomarkers in oral cancer

Abstract Background: Oral cavity squamous cell carcinoma (OCSCC) has an unpredictable response to immunotherapy, and standard biomarkers evaluating the tumor immune microenvironment (TIME) lack widespread translational applicability. Defining the TIME is critical to understanding mechanisms and allows the development of reproducible and accurate prognostic and predictive biomarkers based on immune profiles; however, to date, this remains elusive for clinical use. To further study and deconstruct the TIME within OCSCC, we integrated our previously developed computational spatial analysis (CSA) with in-silico deconvolution analyses to comprehensively study the TIME in OCSCC. Methods: We leveraged access to two independent OCSCC cohorts (UM and TCGA) with paired bulk RNASeq, WES, and CSA-immune score data. TMB, neoantigen load, and deconvolution analysis (CIBERSORTx) were performed to generate in silico immune profiles. A previously described CSA evaluates the density and distribution of tumor-infiltrating lymphocytes (TILs) relative to cancer cells to generate immune scores (GCross function [GFx]). GFx scores were then correlated with WES and RNASeq-derived cell-type deconvolution results, immune cell activation expression signatures, and gene expression-based radiosensitivity index scores. Pearson's correlation coefficient and associated p-value were calculated for each comparison. Cox proportional hazards multivariate regression was performed using the entire cohort for survival and recurrence analysis. Results: Here, we better characterize the immunologic tumor environment by objectively measuring the TIL density in spatial relationships with cancer cells. We found that immunoreactive tumors with high GFx scores are highly prognostic for overall survival, with the lowest tiers associated with poor survival. Combining the spatial relationship with immunogenomics (WES and RNASeq immune profiles) increased the prognostic capability of the integrated bioinformatics analysis model. In addition, we further revealed that lymphocyte-infiltrated regions, specifically CD8+ T-cells, are associated with TMB, neoantigen load, and improved overall survival. Conclusion: This study provides an integrated dataset from which to generate future insights and possible immunomodulatory therapies to counteract the poor immunogenicity of OCSCC. We show that integrating computational spatial analysis and in-silico deconvolution analysis is generalizable to multiple patient populations with different demographic compositions and pathology images collected from distinctive digitization methods. Our machine-learning approaches provide clinically actionable predictions that confirm the relevance of these biomarkers with immune cell infiltration and suggest the role of digital pathology profiling in predicting response to immunotherapy which could inform treatments for oral squamous carcinoma patients. Citation Format: Michael M. Allevato, Lisa Chionis, Joshua Smith, Santhoshi Krishnan, Leanne Henry, Tingting Qin, Janice Farlow, Laura Rozek, Jonathan Mchugh, Arvind Rao, Maureen Sartor, Steven B. Chinn. Integrated bioinformatics and functional spatial analysis platform for the discovery of predictive biomarkers in oral cancer [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-031.

Homologous Recombination Deficiency Across Subtypes of Primary Breast Cancer.

Homologous recombination deficiency (HRD) is highly prevalent in triple-negative breast cancer (TNBC) and associated with response to PARP inhibition (PARPi). Here, we studied the prevalence of HRD in non-TNBC to assess the potential for PARPi in a wider group of patients with breast cancer. HRD status was established using targeted gene panel sequencing (360 genes) and BRCA1 methylation analysis of pretreatment biopsies from 201 patients with primary breast cancer in the phase II PETREMAC trial (ClinicalTrials.gov identifier: NCT02624973). HRD was defined as mutations in BRCA1, BRCA2, BRIP1, BARD1, or PALB2 and/or promoter methylation of BRCA1 (strict definition; HRD-S). In secondary analyses, a wider definition (HRD-W) was used, examining mutations in 20 additional genes. Furthermore, tumor BRCAness (multiplex ligation-dependent probe amplification), PAM50 subtyping, RAD51 nuclear foci to test functional HRD, tumor-infiltrating lymphocyte (TIL), and PD-L1 analyses were performed. HRD-S was present in 5% of non-TNBC cases (n = 9 of 169), contrasting 47% of the TNBC tumors (n = 15 of 32). HRD-W was observed in 23% of non-TNBC (n = 39 of 169) and 59% of TNBC cases (n = 19 of 32). Of 58 non-TNBC and 30 TNBC biopsies examined for RAD51 foci, 4 of 4 (100%) non-TNBC and 13 of 14 (93%) TNBC cases classified as HRD-S had RAD51 low scores. In contrast, 4 of 17 (24%) non-TNBC and 15 of 19 (79%) TNBC biopsies classified as HRD-W exhibited RAD51 low scores. Of nine non-TNBC tumors with HRD-S status, only one had a basal-like PAM50 signature. There was a high concordance between HRD-S and either BRCAness, high TIL density, or high PD-L1 expression (each P < .001). The prevalence of HRD in non-TNBC suggests that therapy targeting HRD should be evaluated in a wider breast cancer patient population. Strict HRD criteria should be implemented to increase diagnostic precision with respect to functional HRD.

ASCL2 induces an immune excluded microenvironment by activating cancer-associated fibroblasts in microsatellite stable colorectal cancer

Proficient mismatch repair or microsatellite stable (pMMR/MSS) colorectal cancers (CRCs) are vastly outnumbered by deficient mismatch repair or microsatellite instability-high (dMMR/MSI-H) tumors and lack a response to immune checkpoint inhibitors (ICIs). In this study, we reported two distinct expression patterns of ASCL2 in pMMR/MSS and dMMR/MSI-H CRCs. ASCL2 is overexpressed in pMMR/MSS CRCs and maintains a stemness phenotype, accompanied by a lower density of tumor-infiltrating lymphocytes (TILs) than those in dMMR/MSI CRCs. In addition, coadministration of anti-PD-L1 antibodies facilitated T cell infiltration and provoked strong antitumor immunity and tumor regression in the MC38/shASCL2 mouse CRC model. Furthermore, overexpression of ASCL2 was associated with increased TGFB levels, which stimulate local Cancer-associated fibroblasts (CAFs) activation, inducing an immune-excluded microenvironment. Consistently, mice with deletion of Ascl2 specifically in the intestine (Villin-Cre+, Ascl2flox/flox, named Ascl2 CKO) revealed fewer activated CAFs and higher proportions of infiltrating CD8+ T cells; We further intercrossed Ascl2 CKO with ApcMin/+ model suggesting that Ascl2-deficient expression in intestinal represented an immune infiltrating environment associated with a good prognosis. Together, our findings indicated ASCL2 induces an immune excluded microenvironment by activating CAFs through transcriptionally activating TGFB, and targeting ASCL2 combined with ICIs could present a therapeutic opportunity for MSS CRCs.

Synergistic efficacy of simultaneous anti-TGF-β/VEGF bispecific antibody and PD-1 blockade in cancer therapy

BackgroundRecently, therapeutic antibodies against programmed cell death 1 (PD-1) and its ligand (PD-L1) have exerted potent anticancer effect in a variety of tumors. However, blocking the PD-1/PD-L1 axis alone is not sufficient to restore normal immune response. Other negative regulators of antitumor immunity, like TGF-β and VEGFA, are also involved in immune escape of tumor cells and induce immunotherapy resistance.MethodsWe developed a novel anti-TGF-β/VEGF bispecific antibody Y332D based on the Nano-YBODY™ technology platform. The CCK-8, flow cytometry, SBE4 luciferase reporter assay, western blotting and transwell assays were used to measure the biological activities of the anti-TGF-β moiety. The NFAT luciferase reporter assay, luminescent cell viability assay and tube formation assay were used to measure the biological activities of the anti-VEGF moiety. The in vivo anticancer efficacy of Y332D alone or in combination with PD-1 blockade was evaluated in H22, EMT-6, 4T1, and AKT/Ras-driven murine hepatocellular carcinoma tumor models. Immunofluorescent staining, flow cytometry, RNA-seq and quantitative RT-PCR were adopted to analyze the alterations in the tumor microenvironment.ResultsY332D could maintain specific binding affinities for TGF-β and VEGFA. Y332D almost entirely counteracted the in vitro biological functions of TGF-β and VEGFA, including immunosuppression, activated TGF-β signaling, epithelial-mesenchymal transition (EMT), activated VEGF/VEGFR signaling, HUVEC proliferation and tube formation. The in vivo experiment data demonstrated that Y332D was more effective in inhibiting tumor growth and metastasis than anti-TGF-β and anti-VEGF monotherapies. In combination therapies, Y332D plus PD-1 blockade exhibited the most potent and durable anticancer effect. Mechanistically, Y332D plus PD-1 blockade upregulated the density and function of tumor-infiltrating lymphocytes and exerted reinvigorated antitumor immunity.ConclusionY332D could simultaneously block TGF-β and VEGF signalings. In comparison with the monotherapies, Y332D combined with PD-1 blockade exerts superior antitumor effect through improving immune microenvironment.

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&amp;E)-stained whole-slide images (WSIs) of HGSOC. Methods: 161 H&amp;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&amp;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 &lt; 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&amp;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.

Spatial Distribution and Densities of CD103+ and FoxP3+ Tumor Infiltrating Lymphocytes by Digital Analysis for Outcome Prediction in Breast Cancer.

The evaluation of tumor-infiltrating lymphocytes (TILs) for breast cancer prognosis is now established. However, the clinical value for their spatial distributions of specific immune subsets, namely CD103+ tissue-resident memory T cells FoxP3+ regulatory T ells, have not been thoroughly examined. Representative whole sections of breast cancers were subjected to CD103 and FoxP3 double staining. Their density, ratio, and spatial features were analyzed in tumor area and tumor-stromal interface. Their associations with clinicopathological parameters and patient's prognosis were analyzed. CD103 TILs were closer to tumor nests than FoxP3 TILs in the tumor-stromal interface. Their densities were associated with high-grade disease, TNBC, and stromal TILs. High stromal FoxP3 (sFoxP3) TILs and close proximity of sCD103 TILs to tumor were independently associated with better survival at multivariate analysis. Subgroup analysis showed the high FoxP3 TILs density associated better survival was seen in HER2-OE and TNBC subtypes while the proximity of CD103 TILs to tumor nests associated better survival was seen in luminal cancers. The prognostic impact of CD103 and FoxP3 TILs in breast cancer depends on their spatial localization. High sFoxP3 TIL density and the lower distance of CD103 TILs from the tumor nests had independent favorable prognostic values.

Identification of cytokine-predominant immunosuppressive class and prognostic risk signatures in glioma.

The advent of immune checkpoint blockade (ICB) therapies this year has changed the way glioblastoma (GBM) is treated. Meanwhile, some patients with strong PD-L1 expression remain immune checkpoint resistant. To better understand the molecular processes that influence the immune environment, there is an urgent need to characterize the immunosuppressive tumor microenvironment and identify biomarkers to predict patient survival outcomes. Our study analyzed RNA-sequencing data from 178 GBM samples. Their unique gene expression patterns in the tumor microenvironment were analyzed by an unsupervised clustering algorithm. Through these expression patterns, a panel of T-cell exhaustion signatures, immunosuppressive cells, and clinical features correlates with immunotherapy response. The presence or absence of immune status and prognostic signatures was then validated with the test dataset. 38.2% of GBM patients showed increased expression of anti-inflammatory cytokines, significant enrichment of T cell exhaustion signals, higher proportion of immunosuppressive cells (macrophages and CD4 regulatory T cells) and nine inhibitory checkpoints (CTLA4, PDCD1, LAG3, BTLA, TIGIT, HAVCR2, IDO1, SIGLEC7, and VISTA). The immunodepleted class (IDC) was used to classify these immunocompromised individuals. Despite the high density of tumor-infiltrating lymphocytes shown by IDC, such patients have a poor prognosis. Although PD-L1 was highly expressed in IDC, it suggested that there might be ICB resistance. There are many IDC predictive signatures to discover. PD-1 is strongly expressed in a novel immunosuppressive class of GBM, but this cluster may be resistant to ICB therapy. A comprehensive description of this drug-resistant tumor microenvironment could provide new insights into drug resistance mechanisms and improved immunotherapy techniques.

Programmed death-ligand 1 and tumor-infiltrating lymphocytes (TILs) – low TIL density may predict poorer long-term prognosis in T1 laryngeal cancer

We evaluated the prognostic role of programmed death-ligand 1 (PD-L1) and tumor-infiltrating lymphocytes (TILs) in T1 glottic laryngeal squamous cell carcinoma (LSCC). T1 glottic LSCC patients (n = 174) treated at five Finnish university hospitals between 2003 and 2013 were included. Tissue microarray (TMA) blocks were used for PD-L1 immunohistochemistry. TILs were scored from intratumoral and stromal regions in whole tissue sections. Of 174 patients, 92 (53%) had negative, 66 (38%) intermediate, and 16 (9%) high PD-L1 levels. Of 80 patients whose TILs were analyzed, 50 (63%) had low and 30 (38%) high stromal TIL density. Patients with a local recurrence or a new primary tumor of the larynx had lower TIL density than had other patients (p = 0.047). High PD-L1 expression with low stromal TIL density was associated with inferior 5-year disease-specific survival (85% vs. 100%, p = 0.02). In conclusion, in patients treated for T1 glottic LSCC, low stromal TIL density was associated with local recurrences and new primary tumors of the larynx. High PD-L1 expression with low stromal TIL density may be associated with worse survival in T1 glottic LSCC.

TIM-3/Galectin-9 and CD160 expression in salivary adenoid cystic carcinoma.

Investigating T-cell immunoglobulin and mucin-domain containing-3 (TIM-3), Galectin 9 (Gal-9), CD160 expression and tumor-infiltrating lymphocytes (TILs) and correlation with clinicopathological characteristics of salivary adenoid cystic carcinoma (SACC). Sixty cases of SACC were detected by immunohistochemical staining to evaluate TIM-3, Gal-9, and CD160 expression and analyze the correlation between TIM-3, Gal-9, CD160 expression and clinicopathologic features by rank-sum test. The association of TILs with TIM-3, Gal-9, and CD160 expression in SACC stromal was done by Chi-square test. TIM-3 and CD160 overexpression were correlated with recurrence of SACC (p = 0.029, p = 0.007, respectively). High Gal-9 expression was correlated with pathological classification (p = 0.018). The average percentage of TILs was 18.2% in SACC and most of TILs were more likely to occur in minor salivary glands (p = 0.038). Pairwise positive correlations were observed between the expression of TIM-3, Gal-9, and CD160 in tumor cells as well as in TILs, respectively. Low density of TILs was characteristic of the SACC microenvironment, with upregulation of TIM-3, Gal-9, and CD160 all occurring. However, TIM-3, Gal-9, and CD160 expression in the stromal dependent on the number of TILs represent potential therapeutic targets in SACC.

Tumor infiltrating lymphocytes and neutrophil-to-lymphocyte ratio in relation to pathological complete remission to neoadjuvant therapy and prognosis in triple negative breast cancer

ObjectiveTo explore the correlation between the peripheral blood neutrophil-to-lymphocyte ratio (NLR) and tumor infiltrating lymphocyte (TIL) before neoadjuvant therapy (NAT) and the prognosis of patients with triple negative breast cancer. MethodA total of 126 patients with TNBC who received NAT were screened out. TILs, CD8+TIL and FOXP3+TIL were detected by immunohistochemistry in core needle biopsy specimens before treatment, and NLR was calculated. Kaplan-Meier analysis was used to estimate survival rates. Univariate and multivariate analyses were performed using Cox proportional hazards regression. ResultsNLR was negatively correlated with TILs density (p = 0.040) and FOXP3+ TIL was positively correlated with NLR (p = 0.019). Patients with low NLR/high TILs density showed the highest pCR rate (46/48, 95 %), while only 6/22 patients (21 %) with high NLR/low TILs density achieved pCR. Multivariate analysis showed that high NLR was independently associated with pCR ((HR = 5.043, 95 %CI = 1.637–15.535, p = 0.005). High T stage, lymph node involvement, lymphovascular invasion, high NLR, low TILs density and low CD8+ TIL were associated with poor OS and BCSS. Multivariate Cox regression analysis showed that high NLR (HR = 36.182, 95 %CI = 4.120–317.759, p = 0.001), high CD8+ TIL density (HR = 0.182, 95 %CI = 0.044–0.754, p = 0.019) were independently associated with poor OS. Similarly, high NLR (HR = 23.989, 95 %CI = 2.275–252.131, p = 0.008) was independently associated with worse BCSS. ConclusionsNLR may help to screen the high-risk population of TNBC patients after neoadjuvant therapy.

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.

Tumor-infiltrating lymphocytes and tumor-associated macrophages as potential predictors of lymph node metastases in major salivary gland cancers.

The purpose of this study is to define if tumor-infiltrating lymphocytes (TILs) and tumor-associated macrophages (TAMs) could represent potential predictors of lymph node metastases (LNM) in salivary gland cancers (SGC). A selected number of immunohistochemical markers related to TILs (CD3, CD4, CD68, and FOXP3) and TAMs (CD68 and CD163) were investigated on major salivary gland cancers. TIL and TAM densities were measured on digital images using the open-source QuPath both in the tumor interior (TI) and invasive margin (IM). Correlation with pathologic N classification and follow-up clinical data was investigated. A total of 25 consecutive patients (men: 11; median age: 62.0) were included. Densities of CD3+ IM (OR = 7.7, 95% CI 1.2-51.2), CD8+ TI (OR = 7.7, 95% CI 1.2-51.2), CD8+ IM (OR = 7.7, 95% CI 1.2-51.2), FOXP3+ TI (OR = 24.0, 95% CI 2.2-255.9), CD68+ TI (OR = 7.7, 95% CI 1.2-51.2), and CD163+ IM (OR = 7.7, 95% CI 1.2 - 51.2), and the Immunoscore CD8/CD3 (OR = 1.9, 95% CI 1.1-3.4) were significantly associated with LNM (p < 0.05). CD3+ TI density was significantly associated with tumor recurrence and death (HR = 5.8, 95% CI 1.5-22.6; p < 0.05). A high density of specific TIL and TAM subpopulations might be correlated with a higher probability of LNM in SGC.

Tumor Heterogeneity Confounds Lymphocyte Metrics in Diagnostic Lung Cancer Biopsies.

The immune microenvironment is involved in fundamental aspects of tumorigenesis, and immune scores are now being developed for clinical diagnostics. To evaluate how well small diagnostic biopsies and tissue microarrays (TMAs) reflect immune cell infiltration compared to the whole tumor slide, in tissue from patients with non-small cell lung cancer. A TMA was constructed comprising tissue from surgical resection specimens of 58 patients with non-small cell lung cancer, with available preoperative biopsy material. Whole sections, biopsies, and TMA were stained for the pan-T lymphocyte marker CD3 to determine densities of tumor-infiltrating lymphocytes. Immune cell infiltration was assessed semiquantitatively as well as objectively with a microscopic grid count. For 19 of the cases, RNA sequencing data were available. The semiquantitative comparison of immune cell infiltration between the whole section and the biopsy displayed fair agreement (intraclass correlation coefficient [ICC], 0.29; P = .01; CI, 0.03-0.51). In contrast, the TMA showed substantial agreement compared with the whole slide (ICC, 0.64; P < .001; CI, 0.39-0.79). The grid-based method did not enhance the agreement between the different tissue materials. The comparison of CD3 RNA sequencing data with CD3 cell annotations confirmed the poor representativity of biopsies as well as the stronger correlation for the TMA cores. Although overall lymphocyte infiltration is relatively well represented on TMAs, the representativity in diagnostic lung cancer biopsies is poor. This finding challenges the concept of using biopsies to establish immune scores as prognostic or predictive biomarkers for diagnostic applications.

Current Understanding on Why Ovarian Cancer Is Resistant to Immune Checkpoint Inhibitors.

The standard treatment of ovarian cancer (OC) patients, including debulking surgery and first-line chemotherapy, is unsatisfactory because of recurrent episodes in the majority (~70%) of patients with advanced OC. Clinical trials have shown only a modest (10-15%) response of OC individuals to treatment based on immune checkpoint inhibitors (ICIs). The resistance of OC to therapy is caused by various factors, including OC heterogeneity, low density of tumor-infiltrating lymphocytes (TILs), non-cellular and cellular interactions in the tumor microenvironment (TME), as well as a network of microRNA regulating immune checkpoint pathways. Moreover, ICIs are the most efficient in tumors that are marked by high microsatellite instability and high tumor mutation burden, which is rare among OC patients. The great challenge in ICI implementation is connected with distinguishing hyper-, pseudo-, and real progression of the disease. The understanding of the immunological, molecular, and genetic mechanisms of OC resistance is crucial to selecting the group of OC individuals in whom personalized treatment would be beneficial. In this review, we summarize current knowledge about the selected factors inducing OC resistance and discuss the future directions of ICI-based immunotherapy development for OC patients.

Prognostic Impact of the Immune-Cell Infiltrate in N1-Positive Non–Small-Cell Lung Cancer

IntroductionThe tumoral immune milieu plays a crucial role for the development of non–small-cell lung cancer (NSCLC) and may influence individual prognosis. We analyzed the predictive role of immune cell infiltrates after curative lung cancer surgery. Materials and MethodsThe tumoral immune-cell infiltrate from 174 patients with pN1 NSCLC and adjuvant chemotherapy was characterized using immunofluorescence staining. The density and distribution of specific immune cells in tumor center (TU), invasive front (IF) and normal tissue (NORM) were correlated with clinical parameters and survival data. ResultsTumor specific survival (TSS) of all patients was 69.9% at 5 years. The density of tumor infiltrating lymphocytes (TIL) was higher in TU and IF than in NORM. High TIL density in TU (low vs. high: 62.0% vs. 86.7%; p = .011) and the presence of cytotoxic T-Lymphocytes (CTLs) in TU and IF were associated with improved TSS (positive vs. negative: 90.6% vs. 64.7% p = .024). High TIL-density correlated with programmed death-ligand 1 expression levels ≥50% (p < .001). Multivariate analysis identified accumulation of TIL (p = .016) and low Treg density (p = .003) in TU as negative prognostic predictors in squamous cell carcinoma (p = .025), whereas M1-like tumor- associated macrophages (p = .019) and high programmed death-ligand 1 status (p = .038) were associated with better survival in adenocarcinoma. ConclusionThe assessment of specific intratumoral immune cells may serve as a prognostic predictor in pN1 NSCLC. However differences were observed related to adenocarcinoma or squamous cell carcinoma histology. Prospective assessment of the immune-cell infiltrate and further clarification of its prognostic relevance could assist patient selection for upcoming perioperative immunotherapies.

Tumor-infiltrating lymphocytes predict efficacy of immunotherapy in advanced non-small cell lung cancer: a single-center retrospective cohort study

Background/Purpose The current study aimed to investigate the correlation between tumor-infiltrating lymphocytes (TILs) and immunotherapy efficacy in patients with advanced non-small cell lung cancer (NSCLC). Materials and methods Eighty-nine patients with advanced NSCLC who received immune checkpoint inhibitors (ICIs) monotherapy were retrospectively enrolled in this study. The density of TILs in paraffin-embedded pathological tissues taken before receiving ICIs was quantitatively analyzed by immunohistochemical staining. The density of TILs was treated as a dichotomous variable using the median as the cutoff value. The Kaplan–Meier analysis was used to assess survival differences between groups. Univariate and multivariate Cox analyses were applied to screen out independent prognostic factors and further construct a nomogram prediction model to predict survival. Results Survival analysis showed that CD8+ TILs, CD4+ TILs, and IFN-γ+ Th1 were significant positive indicators for predicting progression-free survival (PFS) and overall survival (OS) (p < 0.05), whereas Foxp3+ Treg were a significant negative predictor (p < 0.05). The predictive role of IL-4+ Th2 was not apparent in this study and requires further investigation and exploration (p > 0.05). The nomogram prediction model exhibited good discriminative ability, with C-index values of 0.723 (95% CI 0.682-0.764) and 0.793 (95% CI, 0.738-0.848) in the training cohort and validation cohort, respectively. The AUC values indicated that the nomogram prediction model had high predictive value and the calibration curve presented good prediction accuracy. Conclusions TILs could predict the efficacy of immunotherapy and may become a promising predictor.

Tumor Microenvironment Landscape of NSCLC Reveals Resistance Mechanisms for Programmed Death-Ligand 1 Blockade After Chemoradiotherapy: A Multicenter Prospective Biomarker Study (WJOG11518L:SUBMARINE)

IntroductionThe PACIFIC regimen of consolidation therapy with the programmed cell death-ligand 1 inhibitor durvalumab after definitive concurrent chemoradiation therapy has become a standard of care for individuals with unresectable stage III NSCLC. Nevertheless, approximately half of the treated patients experience disease progression within 1 year, with the mechanisms of treatment resistance being poorly understood. We here performed a nationwide prospective biomarker study to explore the resistance mechanisms (WJOG11518L:SUBMARINE). MethodsA total of 135 patients with unresectable stage III NSCLC who received the PACIFIC regimen were included for comprehensive profiling of the tumor microenvironment by immunohistochemistry, transcriptome analysis, and genomic sequencing of pretreatment tumor tissue and flow cytometric analysis of circulating immune cells. Progression-free survival was compared on the basis of these biomarkers. ResultsThe importance of preexisting effective adaptive immunity in tumors was revealed for treatment benefit regardless of genomic features. We also identified CD73 expression by cancer cells as a mechanism of resistance to the PACIFIC regimen. Multivariable analysis of immunohistochemistry data with key clinical factors as covariables indicated that low CD8+ tumor-infiltrating lymphocyte density and the high CD73+ cancer cells were independently associated with poor durvalumab outcome (hazard ratios = 4.05 [95% confidence interval: 1.17–14.04] for CD8+ tumor-infiltrating lymphocytes; 4.79 [95% confidence interval: 1.12–20.58] for CD73). In addition, whole-exome sequencing of paired tumor samples suggested that cancer cells eventually escaped immune pressure as a result of neoantigen plasticity. ConclusionsOur study emphasizes the importance of functional adaptive immunity in stage III NSCLC and implicates CD73 as a promising treatment target, thus providing insight forming a basis for development of a new treatment approach in NSCLC.

Prognostic and predictive value of tumor infiltrating lymphocytes in combination with systemic inflammatory markers in colon cancer

Objective. Systemic inflammatory indices and CD8(+) tumor infiltrating lymphocytes (TILs) in the tumor microenvironment are highly prognostic in colon cancer (CC) but combined assessment is less well studied. The purpose of this study was to investigate the prognostic and predictive value of CD8(+) TILs in combination with systemic inflammatory indices in patients with resected stage II-III colon cancer.Patients and methods. Patients with stage II-III CC (n = 304) diagnosed between 2008 and 2016 were included. Pan-immune inflammation value (PIV) was used as a comprehensive inflammatory index and was calculated as: [neutrophil count × platelet count × monocyte count]/lymphocyte count. The mean density of CD8+ TILs in the periphery and center of the tumor was assessed and dichotomized at the 75th percentile. Combined inflammation score (CIS) was classified as “high” in patients with high PIV (>median) plus low mean CD8(+) TILs density, and CIS “low” in the remaining patients.Results. 5-year DFS was 71% (78% in stage II, 63.4% in stage III). PIV was higher in right colon tumors, T4 tumors and in patients with obstruction / perforation. CD8(+) TIL density was lower in node positive tumors. High PIV and low CD8(+) TILs were associated with shorter disease-free survival (DFS). In multivariate analysis; age > 65 years, stage III disease and high CIS (PIVhigh / CD8low) were associated with shorter DFS. Among patients with stage II disease, patients with high CIS (PIVhigh / CD8low) derived significant benefit from adjuvant chemotherapy while those with low CIS derived no benefit.Conclusion. Combined inflammation score may represent a new prognostic factor for localized colon cancer and predictor of chemotherapy response in patients with stage II disease.