Pan-cancer evaluation of tumor-infiltrating lymphocytes and programmed cell death protein ligand-1 in metastatic biopsies and matched primary tumors.

Tumor immunological characterization includes evaluation of tumor-infiltrating lymphocytes (TILs) and programmed cell death protein ligand-1 (PD-L1) expression. This study investigated TIL distribution, its prognostic value, and PD-L1 expression in metastatic and matched primary tumors (PTs). Specimens from 550 pan-cancer patients of the SHIVA01 trial (NCT01771458) with available metastatic biopsy and 111 matched PTs were evaluated for TILs and PD-L1. Combined positive score (CPS), tumor proportion score (TPS), and immune cell (IC) score were determined. TILs and PD-L1 were assessed according to PT organ of origin, histological subtype, and metastatic biopsy site. We found that TIL distribution in metastases did not vary according to PT organ of origin, histological subtype, or metastatic biopsy site, with a median of 10% (range: 0-70). TILs were decreased in metastases compared to PT (20% [5-60] versus 10% [0-40], p < 0.0001). CPS varied according to histological subtype (p = 0.02) and biopsy site (p < 0.02). TPS varied according to PT organ of origin (p = 0.003), histological subtype (p = 0.0004), and metastatic biopsy site (p = 0.00004). TPS was higher in metastases than in PT (p < 0.0001). TILs in metastases did not correlate with overall survival. In conclusion, metastases harbored fewer TILs than matched PT, regardless of PT organ of origin, histological subtype, and metastatic biopsy site. PD-L1 expression increased with disease progression. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

A Pipeline for Evaluation of Machine Learning/Artificial Intelligence Models to Quantify Programmed Death Ligand 1 Immunohistochemistry.

Immunohistochemistry (IHC) is used to guide treatment decisions in multiple cancer types. For treatment with checkpoint inhibitors, programmed death ligand 1 (PD-L1) IHC is used as a companion diagnostic. However, the scoring of PD-L1 is complicated by its expression in cancer and immune cells. Separation of cancer and noncancer regions is needed to calculate tumor proportion scores (TPS) of PD-L1, which is based on the percentage of PD-L1-positive cancer cells. Evaluation of PD-L1 expression requires highly experienced pathologists and is often challenging and time-consuming. Here, we used a multi-institutional cohort of 77 lung cancer cases stained centrally with the PD-L1 22C3 clone. We developed a 4-step pipeline for measuring TPS that includes the coregistration of hematoxylin and eosin, PD-L1, and negative control (NC) digital slides for exclusion of necrosis, segmentation of cancer regions, and quantification of PD-L1+ cells. As cancer segmentation is a challenging step for TPS generation, we trained DeepLab V3 in the Visiopharm software package to outline cancer regions in PD-L1 and NC images and evaluated the model performance by mean intersection over union (mIoU) against manual outlines. Only 14 cases were required to accomplish a mIoU of 0.82 for cancer segmentation in hematoxylin-stained NC cases. For PD-L1-stained slides, a model trained on PD-L1 tiles augmented by registered NC tiles achieved a mIoU of 0.79. In segmented cancer regions from whole slide images, the digital TPS achieved an accuracy of 75% against the manual TPS scores from the pathology report. Major reasons for algorithmic inaccuracies include the inclusion of immune cells in cancer outlines and poor nuclear segmentation of cancer cells. Our transparent and stepwise approach and performance metrics can be applied to any IHC assay to provide pathologists with important insights on when to apply and how to evaluate commercial automated IHC scoring systems.

Sequence-Prescribed ß-Sheet for Enhanced Electron Tunneling: Boosting Interface Recognition and Electrochemical Measurement.

Peptide self-assemblies could leverage their specificity, stability, biocompatibility, and electrochemical activity to create functionalized interfaces for molecular sensing and detection. However, the dynamics within these interfaces are complex, with competing forces, including those maintaining peptide structures, recognizing analytes, and facilitating signal transmission. Such competition could lead to nonspecific interference, compromising the detection sensitivity and accuracy. In this study, a series of peptides with precise structures and controllable electron transfer capabilities were designed. Through examining their stacking patterns, the interplay between the peptides' hierarchical structures, their ability to recognize targets, and their conductivity were clarified. Among these, the EP5 peptide assembly was identified for its ability to form controllable electronic tunnels facilitated by π-stacking induced ß-sheets. EP5 could enhance the long-range conductivity, minimize nonspecific interference, and exhibit targeted recognition capabilities. Based on EP5, an electrochemical sensing interface toward the disease marker PD-L1 (programmed cell death ligand 1) was developed, suitable for both whole blood assay and in vivo companion diagnosis. It opens a new avenue for crafting electrochemical detection interfaces with specificity, sensitivity, and compatibility.

Predictive Analysis in Oral Cancer Immunotherapy: Profiling Dual PD-L1-Positive Extracellular Vesicle Subtypes with Step-Wedge Microfluidic Chips.

PD-L1-positive extracellular vesicles (PD-L1+ EVs) play a pivotal role as predictive biomarkers in cancer immunotherapy. These vesicles, originating from immune cells (I-PD-L1+ EVs) and tumor cells (T-PD-L1+ EVs), hold distinct clinical predictive values, emphasizing the importance of deeply differentiating the PD-L1+ EV subtypes for effective liquid biopsy analyses. However, current methods such as ELISA lack the ability to differentiate their cellular sources. In this study, a novel step-wedge microfluidic chip that combines magnetic microsphere separation with single-layer fluorescence counting is developed. This chip integrates magnetic microspheres modified with anti-PD-L1 antibodies and fluorescent nanoparticles targeting EpCAM (tumor cell marker) or CD45 (immunocyte marker), enabling simultaneous quantification and sensitive analysis of PD-L1+ EV subpopulations in oral squamous cell carcinoma (OSCC) patients' saliva without background interference. Analysis results indicate reduced levels of I-PD-L1+ EVs in OSCC patients compared to those in healthy individuals, with varying levels of heterogeneous PD-L1+ EVs observed among different patient groups. During immunotherapy, responders exhibit decreased levels of total PD-L1+ EVs and T-PD-L1+ EVs, accompanied by reduced levels of I-PD-L1+ EVs. Conversely, nonresponders show increased levels of I-PD-L1+ EVs. Utilizing the step-wedge microfluidic chip allows for simultaneous detection of PD-L1+ EV subtypes, facilitating the precise prediction of oral cancer immunotherapy outcomes.

A Deep Learning-Based Assay for Programmed Death Ligand 1 Immunohistochemistry Scoring in Non-Small Cell Lung Carcinoma: Does it Help Pathologists Score?

Several studies have developed various artificial intelligence (AI) models for immunohistochemical analysis of programmed death ligand 1 (PD-L1) in patients with non-small cell lung carcinoma; however, none have focused on specific ways by which AI-assisted systems could help pathologists determine the tumor proportion score (TPS). In this study, we developed an AI model to calculate the TPS of the PD-L1 22C3 assay and evaluated whether and how this AI-assisted system could help pathologists determine the TPS and analyze how AI-assisted systems could affect pathologists' assessment accuracy. We assessed the 4 methods of the AI-assisted system: (1 and 2) pathologists first assessed and then referred to automated AI scoring results (1, positive tumor cell percentage; 2, positive tumor cell percentage and visualized overlay image) for final confirmation, and (3 and 4) pathologists referred to the automated AI scoring results (3, positive tumor cell percentage; 4, positive tumor cell percentage and visualized overlay image) while determining TPS. Mixed-model analysis was used to calculate the odds ratios (ORs) with 95% CI for AI-assisted TPS methods 1 to 4 compared with pathologists' scoring. For all 584 samples of the tissue microarray, the OR for AI-assisted TPS methods 1 to 4 was 0.94 to 1.07 and not statistically significant. Of them, we found 332 discordant cases, on which the pathologists' judgments were inconsistent; the ORs for AI-assisted TPS methods 1, 2, 3, and 4 were 1.28 (1.06-1.54; P = .012), 1.29 (1.06-1.55; P = .010), 1.28 (1.06-1.54; P = .012), and 1.29 (1.06-1.55; P = .010), respectively, which were statistically significant. For discordant cases, the OR for each AI-assisted TPS method compared with the others was 0.99 to 1.01 and not statistically significant. This study emphasized the usefulness of the AI-assisted system for cases in which pathologists had difficulty determining the PD-L1 TPS.

Comparison of Primary and Metastatic Fumarate Hydratase-Deficient Renal Cell Carcinomas Documents Morphologic Divergence and Potential Diagnostic Pitfall With Peritoneal Mesothelioma.

Fumarate hydratase (FH)-deficient renal cell carcinomas are rare neoplasms characterized by wide morphologic heterogeneity and pathogenetic mutations in the FH gene. They often show aggressive behavior with rapid diffusion to distant organs, so novel therapeutic scenarios have been explored, including EGFR inhibitors and PD-L1 expression for targeted immunotherapy. Herein, we investigated a series of 11 primary FH-deficient renal cell carcinomas and 7 distant metastases to evaluate tumor heterogeneity even in metastatic sites and estimate the specific spread rates to various organs. Furthermore, the tumors were tested for immunohistochemical PD-L1 expression and EGFR mutations. Most metastatic cases involved the abdominal lymph nodes (4/7; 57%), followed by the peritoneum (3/7; 42%), the liver (2/7; 29%), and the lungs (1/7; 14%). Six metastatic localizations were histologically documented, revealing a morphologic heterogeneous architecture often differing from that of the corresponding primary renal tumor. Peritoneal involvement morphologically resembled a benign reactive mesothelial process or primary peritoneal mesothelioma, thus advocating to perform an accurate immunohistochemical panel, including PAX8 and FH, to reach a proper diagnosis. A pure low-grade succinate dehydrogenase-looking primary FH-deficient renal cell carcinoma was also recorded. As for therapy, significant PD-L1 labeling was found in 60% of primary renal tumors, whereas none of them carried pathogenetic EGFR mutations. Our data show that FH-deficient renal cell carcinoma may be morphologically heterogeneous in metastases as well, which involve the lymph nodes, the liver, and the peritoneum more frequently than other renal tumors. Due to the high frequency of this latter (42%), pathologists should always be concerned about ruling out mesothelial-derived mimickers, and the occurrence of rarer, primary, low-grade-looking types. Finally, contrary to EGFR mutations, PD-L1 expression could be a possible predictive biomarker for the therapy of these tumors.

AUNP-12 Near-Infrared Fluorescence Probes across NIR-I to NIR-II Enable In Vivo Detection of PD-1/PD-L1 Axis in the Tumor Microenvironment.

The innovative PD-1/PD-L1 pathway strategy is gaining significant traction in cancer therapeutics. However, fluctuating response rates of 20-40% to PD-1/PD-L1 inhibitors, coupled with the risk of hyperprogression after immunotherapy, underscore the need for accurate patient selection and the identification of more beneficiaries. Molecular imaging, specifically near-infrared (NIR) fluorescence imaging, is a valuable alternative for real-time, noninvasive visualization of dynamic PD-L1 expression in vivo. This research introduces AUNP-12, a novel PD-L1-targeting peptide antagonist conjugated with Cy5.5 and CH1055 for first (NIR-I) and second near-infrared (NIR-II) imaging. These probes have proven to be effective in mapping PD-L1 expression across various mouse tumor models, offering insights into tumor-immune interactions. This study highlights the potential of AUNP-12-Cy5.5 and AUNP-12-CH1055 for guiding clinical immunotherapy through precise patient stratification and dynamic monitoring, supporting the shift toward molecular imaging for personalized cancer care.

PD-L1 expression in vulvar cancer: a systematic review and meta-analysis.

Programmed cell death ligand-1 (PD-L1) expression in cancer may predict clinical response to immunotherapeutic treatment with PD-1/PD-L1 inhibitors. Within the vulvar cancer field, PD-L1 expression has only been assessed by a few studies. We conducted a meta-analysis to examine the prevalence of PD-L1 positivity in vulvar cancer. PubMed, Embase, and Cochrane were searched for articles reporting on PD-L1 expression in vulvar cancer. Study selection and data extraction were performed independently by two authors. We extracted data on PD-L1 prevalence in vulvar cancer according to combined positive score (CPS) and tumour proportion score (TPS). Cutoff values for positivity were ≥1 or ≥10 for CPS and ≥1% and ≥5% for TPS. Random-effects models were used to estimate pooled PD-L1 prevalence, with 95% confidence intervals (CIs). Tests of between-study heterogeneity were evaluated by the I2 statistics. Sources of heterogeneity were explored by subgroup analyses and meta-regression. In total, 19 studies were included. Pooled PD-L1 prevalence in vulvar cancer was 83.4% (95% CI: 70.8-91.3; I2 = 80.0) and 53.9% (95% CI: 37.4-69.6; I2 = 93.0) according to CPS and TPS, respectively. Based on TPS, human papillomavirus (HPV)-associated vulvar squamous cell carcinomas (SCC) showed a lower PD-L1 prevalence (39.9%; 95% CI: 13.3-74.2) compared with HPV-independent SCC (62.6%; 95% CI: 33.7-84.6), but meta-regression showed no significant variation in PD-L1 prevalence by HPV status. PD-L1 prevalence was similar in advanced (44.9%; 95% CI: 29.8-61.1) and localized vulvar cancer (56.7%; 95% CI: 18.9-76.7). In conclusion, PD-L1 expression in vulvar cancer is frequent but between-study heterogeneity was high. Based on a subgroup of heterogenous studies, we found no strong variation in PD-L1 prevalence according to HPV status and stage.

Artificial intelligence enhances whole-slide interpretation of PD-L1 CPS in triple-negative breast cancer: A multi-institutional ring study.

BACKGROUND AND AIMS: Evaluation of the programmed cell death ligand-1 (PD-L1) combined positive score (CPS) is vital to predict the efficacy of the immunotherapy in triple-negative breast cancer (TNBC), but pathologists show substantial variability in the consistency and accuracy of the interpretation. It is of great importance to establish an objective and effective method which is highly repeatable. METHODS: We proposed a model in a deep learning-based framework, which at the patch level incorporated cell analysis and tissue region analysis, followed by the whole-slide level fusion of patch results. Three rounds of ring studies (RSs) were conducted. Twenty-one pathologists of different levels from four institutions evaluated the PD-L1 CPS in TNBC specimens as continuous scores by visual assessment and our artificial intelligence (AI)-assisted method. RESULTS: In the visual assessment, the interpretation results of PD-L1 (Dako 22C3) CPS by different levels of pathologists have significant differences and showed weak consistency. Using AI-assisted interpretation, there were no significant differences between all pathologists (P = 0.43), and the intraclass correlation coefficient (ICC) value was increased from 0.618 [95% confidence interval (CI) = 0.524-0.719] to 0.931 (95% CI = 0.902-0.955). The accuracy of interpretation result is further improved to 0.919 (95% CI = 0.886-0.947). Acceptance of AI results by junior pathologists was the highest among all levels, and 80% of the AI results were accepted overall. CONCLUSION: With the help of the AI-assisted diagnostic method, different levels of pathologists achieved excellent consistency and repeatability in the interpretation of PD-L1 (Dako 22C3) CPS. Our AI-assisted diagnostic approach was proved to strengthen the consistency and repeatability in clinical practice.

An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability.

AIMS: Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising clinical outcomes in urothelial carcinoma (UC). The combined positive score (CPS) quantifies PD-L1 22C3 expression in UC, but it can vary between pathologists due to the consideration of both immune and tumour cell positivity. METHODS AND RESULTS: An artificial intelligence (AI)-powered PD-L1 CPS analyser was developed using 1,275,907 cells and 6175.42 mm2 of tissue annotated by pathologists, extracted from 400 PD-L1 22C3-stained whole slide images of UC. We validated the AI model on 543 UC PD-L1 22C3 cases collected from three institutions. There were 446 cases (82.1%) where the CPS results (CPS ≥10 or <10) were in complete agreement between three pathologists, and 486 cases (89.5%) where the AI-powered CPS results matched the consensus of two or more pathologists. In the pathologist's assessment of the CPS, statistically significant differences were noted depending on the source hospital (P = 0.003). Three pathologists reevaluated discrepancy cases with AI-powered CPS results. After using the AI as a guide and revising, the complete agreement increased to 93.9%. The AI model contributed to improving the concordance between pathologists across various factors including hospital, specimen type, pathologic T stage, histologic subtypes, and dominant PD-L1-positive cell type. In the revised results, the evaluation discordance among slides from different hospitals was mitigated. CONCLUSION: This study suggests that AI models can help pathologists to reduce discrepancies between pathologists in quantifying immunohistochemistry including PD-L1 22C3 CPS, especially when evaluating data from different institutions, such as in a telepathology setting.

Considerable interlaboratory variation in PD-L1 positivity for head and neck squamous cell carcinoma in the Netherlands- A nationwide evaluation study.

AIMS: Patients with recurrent or metastatic head and neck squamous cell carcinoma (HNSCC) are eligible for first-line immune checkpoint inhibition if their tumour is positive for programmed death ligand 1 (PD-L1) determined by the combined positive score (CPS). This nationwide study, using real-world data, investigated the developing PD-L1 testing landscape in the first 3 years after introduction of the test in HNSCC and examined interlaboratory variation in PD-L1 positivity rates. METHODS: Pathology reports of HNSCC patients mentioning PD-L1 were extracted from the Dutch Pathology Registry (Palga). Tumour and PD-L1 testing characteristics were analysed per year and interlaboratory variation in PD-L1 positivity rates was assessed using funnel plots with 95% confidence limits around the overall mean. RESULTS: A total of 817 PD-L1 tests were reported in 702 patients among 19 laboratories; 85.2% of the tests on histological material were stated to be positive. The national PD-L1 positivity rate differed significantly per year during the study period (79.7-89.9%). The use of the recommended 22C3 antibody increased from 59.9 to 74.3%. A total of 673 PD-L1 tests on histological material from 12 laboratories were analysed to investigate interlaboratory variation. Four (33%) deviated significantly from the national mean of PD-L1-positive cases using CPS ≥ 1 cut-off, while two (17%) deviated significantly for CPS ≥ 20 cut-off. CONCLUSION: In the first 3 years of PD-L1 assessment in HNSCC, the testing landscape became more uniform. However, interlaboratory variation in PD-L1 positivity rates between Dutch laboratories was substantial. This implies that there is a need for further test standardisation to reduce this variation.

Retrospective Analyses of PD-L1, LAG-3, TIM-3, OX40L Expressions and MSI Status in Gastroenteropancreatic Neuroendocrine Neoplasms.

We investigated expressions of PD-L1, LAG-3, TIM-3, and OX40L as immune checkpoint proteins, and MSI (repetitive short-DNA-sequences due to defective DNA-repair system) status were analyzed with immunohistochemistry from tissue blocks. Of 83 patients, PD-L1 expression was observed in 18.1% (n = 15) of the patients. None of the patients exhibited LAG-3 expression. TIM-3 expression was 4.9% (n = 4), OX40L was 22.9% (n = 19), and 8.4% (n = 7) of the patients had MSI tumor. A low-to-intermediate positive correlation was observed between PD-L1 and TIM-3 expressions (rho: 0.333, p < 0.01). Although PD-L1 expression was higher in grade 3 NET/NEC, MSI status was prominent in grade 1/2 NET.

Development of small-molecular-based radiotracers for PET imaging of PD-L1 expression and guiding the PD-L1 therapeutics.

PURPOSE: Programmed cell death protein ligand 1 (PD-L1) is a crucial biomarker for immunotherapy. However, nearly 70% of patients do not respond to PD-L1 immune checkpoint therapy. Accurate monitoring of PD-L1 expression and quantification of target binding during treatment are essential. In this study, a series of small-molecule radiotracers were developed to assess PD-L1 expression and direct immunotherapy. METHODS: Radiotracers of [68Ga]Ga-D-PMED, [68Ga]Ga-D-PEG-PMED, and [68Ga]Ga-D-pep-PMED were designed based on a 2-methyl-3-biphenyl methanol scaffold and successfully synthesized. Cellular experiments and molecular docking assays were performed to determine their specificity for PD-L1. PD-L1 status was investigated via positron emission tomography (PET) imaging in MC38 tumor models. PET imaging of [68Ga]Ga-D-pep-PMED was performed to noninvasively quantify PD-L1 blocking using an anti-mouse PD-L1 antibody (PD-L1 mAb). RESULTS: The radiosyntheses of [68Ga]Ga-D-PMED, [68Ga]Ga-D-PEG-PMED, and [68Ga]Ga-D-pep-PMED were achieved with radiochemical yields of 87 ± 6%, 82 ± 4%, and 79 ± 9%, respectively. In vitro competition assays demonstrated their high affinities (the IC50 values of [68Ga]Ga-D-PMED, [68Ga]Ga-D-PEG-PMED, and [68Ga]Ga-D-pep-PMED were 90.66 ± 1.24, 160.8 ± 1.35, and 51.6 ± 1.32 nM, respectively). At 120 min postinjection (p.i.) of the radiotracers, MC38 tumors displayed optimized tumor-to-muscle ratios for all radioligands. Owing to its hydrophilic modification, [68Ga]Ga-D-pep-PMED had the highest target-to-nontarget (T/NT) ratio of approximately 6.2 ± 1.2. Interestingly, the tumor/liver ratio was hardly affected by different concentrations of the inhibitor BMS202. We then evaluated the impacts of dose and time on accessible PD-L1 levels in the tumor during anti-mouse PD-L1 antibody treatment. The tumor uptake of [68Ga]Ga-D-pep-PMED significantly decreased with increasing PD-L1 mAb dose. Moreover, after 8 days of treatment with a single antibody, the uptake of [68Ga]Ga-D-pep-PMED in the tumor significantly increased but remained lower than that in the saline group. CONCLUSION: PET imaging with [68Ga]Ga-D-pep-PMED, a small-molecule radiotracer, is a promising tool for evaluating PD-L1 expression and quantifying the target blockade of PD-L1 to assist in the development of effective therapeutic regimens.

Clinicopathological and prognostic significance of PD-L1 and TIM-3 expression in medullary thyroid carcinoma: a retrospective immunohistochemistry study.

PURPOSE: Expression of the programmed death-ligand 1 (PD-L1) and T-cell immunoglobulin and mucin-domain containing-3 (TIM-3) in medullary thyroid carcinoma (MTC) has been controversial and rarely reported. METHODS: Surgical specimens of 190 MTC patients who had initial curative-intent surgery were collected. Immunohistochemistry of PD-L1 and TIM-3 was performed using 22C3 pharmDx (Dako, Carpinteria, CA) and anti-TIM-3 (1:500, ab241332, Abcam). Stained slides were scored using a combined positive score (CPS) with a cutoff of ≥ 1. We established correlations between PD-L1 expression, TIM-3 expression, clinicopathological, and survival data. RESULTS: 13 cases (13/190, 6.84%) were positive for PD-L1 expression, and 42 cases (42/154, 27.27%) for TIM-3 expression. PD-L1 expression was correlated to TIM-3 expression (P = 0.002), but was not related to overall survival (OS) or progression-free survival (PFS). TIM-3 expression was correlated to perineural invasion (P = 0.040). Multivariate Cox analysis showed that lymphovascular invasion (LVI) was independently associated with OS. And tumor size, LVI, and lymph node metastases were significantly associated with PFS. Furthermore, the multivariate logistic analysis showed multifocal status, LVI, pathological T stage and lymph node metastasis were independent risk factors for biochemical recurrence/persistent disease. CONCLUSIONS: We demonstrated that PD-L1 and TIM-3 expression were not frequent in MTC and were not associated with survival prognosis. Our results should be considered when clinical trials of PD-L1 or TIM-3 blockades are implemented.

PD-L1 expression in tumor and inflammatory cells is associated with favorable tumor features and favorable prognosis in muscle-invasive urothelial carcinoma of the bladder not treated by immune checkpoint inhibitors.

BACKGROUND: A high level of PD-L1 expression is the most relevant predictive parameter for response to immune checkpoint inhibitor (CPI) therapy in urinary bladder cancer. Existing data on the relationship between PD-L1 expression and the natural course of disease are controversial and sparse. METHODS: To expand our understanding of the relationship between PD-L1 expression and parameters of cancer aggressiveness, PD-L1 was analyzed on tissue microarrays containing 2710 urothelial bladder carcinomas including 512 patients with follow-up data who underwent radical cystectomy and follow-up therapies in the pre-immune checkpoint inhibitor therapy era. RESULTS: Tumor cell positivity in ≥10% of cells were seen in 513 (20%) and an immune cell positivity occurred in 872 (34%) of 2566 interpretable cancers. PD-L1 positivity in tumor cells increased from pTaG2 low grade (0.9% positive) to pTaG3 high grade (4.1%; p = 0.0255) and was even higher in muscle-invasive (pT2-4) carcinomas (29.3%; p < 0.0001). However, within pT2-4 carcinomas, PD-L1 positivity was linked to low pT stage (p = 0.0028), pN0 (p < 0.0001), L0 status (p = 0.0005), and a better prognosis within 512 patients with cystectomy who never received CPIs (p = 0.0073 for tumor cells and p = 0.0086 for inflammatory cells). PD-L1 staining in inflammatory cells was significantly linked to PD-L1 staining in tumor cells (p < 0.0001) and both were linked to a positive p53 immunostaining (p < 0.0001). CONCLUSION: It cannot be fully excluded that the strong statistical link between PD-L1 status and favorable histological tumor features as well as better prognosis could influence the outcome of studies evaluating CPIs in muscle-invasive urothelial carcinoma.

Endobronchial Ultrasound Guided Transbronchial Needle Aspiration and PD-L1 Yields.

PURPOSE: Immunotherapy is a leading approach for treating advanced non-small cell lung cancer (NSCLC) by targeting the PD-1/PD-L1 checkpoint signaling pathway, particularly in tumors expressing high levels of PD-L1 (Jug et al. in J Am Soc Cytopathol 9:485-493, 2020; Perrotta et al. in Chest 158: 1230-1239, 2020). Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a minimally invasive method to obtain tissue for molecular studies, including PD-L1 analysis, in unresectable tumors (Genova et al. in Front Immunol 12: 799455, 2021; Wang et al. in Ann Oncol 29: 1417-1422, 2018). This study aimed to assess the adequacy of PD-L1 assessment in EBUS-TBNA cytology specimens. METHODS: Data was collected retrospectively from patients who underwent EBUS-TBNA between 2017 and 2021 for suspected lung cancer biopsy. Samples positive for NSCLC were examined for PD-L1 expression. EBUS was performed by experienced practitioners, following institutional guidelines of a minimum of five aspirations from positively identified lesions. Sample adequacy for molecular testing was determined by the pathology department. RESULTS: The analysis involved 387 NSCLC cases (149 squamous cell, 191 adenocarcinoma, 47 unspecified). Of the 263 EBUS-TBNA specimens tested for PD-L1, 237 (90.1%) were deemed adequate. While 84% adhered to the protocol, adherence did not yield better results. Significantly higher PD-L1 adequacy was observed in squamous cell carcinomas (93.2%) compared to adenocarcinoma (87.6%). The number of aspirations and sedation type did not correlate with PD-L1 adequacy in either cancer type, but lesion size and location had a significant impact in adenocarcinomas. Adenocarcinoma exhibited higher PD-L1 expression (68%) compared to squamous cell carcinoma (48%). CONCLUSION: EBUS-TBNA offers high yields for assessing immunotherapy markers like PD-L1, with satisfactory adequacy regardless of NSCLC subtype, lesion size, or location.

Association of PD-1 and PD-L1 protein expression with selected clinical and morphological parameters in colorectal cancers.

Colorectal cancer is the third most common cancer worldwide and the second cause of death from malignant tumors. Colorectal cancers are treated with surgery, chemotherapy, gene therapy and immunotherapy. PD-1 and PD-L1 proteins have recently been considered as potential targets of anticancer therapy in colorectal cancer. The aim of this study was to evaluate the association of immunohistochemical expression of PD-1 and PD-L1 proteins in colorectal cancer patients with selected clinical and morphological parameters and their survival. Ninety-eight cases of colorectal cancer were studied. Immunohistochemistry was used to evaluate the expression of PD-1 and PD-L1 proteins. Correlations were found between the expression of PD-L1 protein in lymphocytes and lack of lymph node metastases and a lower clinical stage. There was also a correlation between PD-L1 protein expression in cancer cells and a higher grade of histological malignancy.

A study on expression of programmed death ligand-1 in small cell lung carcinoma and correlation with clinicopathological parameters.

Small cell lung carcinoma (SCLC) is characterized by rapid growth and an aggressive clinical course. Standard therapy regimes have limited effects on disease course; therefore the prognosis of SCLC is poor. In the current study, the frequency of programmed death ligand 1 (PD-L1) expression in SCLC and its correlation with clinico-pathological features were evaluated. The study included 100 cases of SCLC wherein testing for PD-L1 was done with the SP263 clone on the Ventana benchmark XT system. Cases with > 1% PD-L1 expression in tumour cells or immune cells were categorized as positive. PD-L1 expression was identified in 14% of cases using the cut-off of ≥ 1%. The tumour proportion score was 10% and the immune proportion score was 9.78% using a cut-off of ≥ 1%. PD-L1 positive expression was more frequent in the male population with age > 40 years. All the patients with positive PD-L1 expression were smokers. In the PD-L1 positive group, presence of necrosis was identified in 71.4% of cases and when compared with the PD-L1 negative subgroup this finding was statistically significant (p = 0.010). Personalized targeted therapy for cases of SCLC is still under evaluation. The use of immunotherapeutic targets, such as PD-L1, may help to define a new treatment strategy for SCLC. Development of new treatment strategies may improve prognosis and survival.

Detailed Characterization of the Lung-Gut Microbiome Axis Reveals the Link between PD-L1 and the Microbiome in Non-Small-Cell Lung Cancer Patients.

Next-generation sequencing technologies have started a new era of respiratory tract research in recent years. Alterations in the respiratory microbiome between healthy and malignant conditions have been revealed. However, the composition of the microbiome varies among studies, even in similar medical conditions. Also, there is a lack of complete knowledge about lung-gut microbiome interactions in lung cancer patients. The aim of this study was to explore the lung-gut axis in non-small-cell lung cancer (NSCLC) patients and the associations between lung-gut axis microbiota and clinical parameters (CRP, NLR, LPS, CD8, and PD-L1). Lung tissue and fecal samples were used for bacterial 16S rRNA sequencing. The results revealed, for the first time, that the bacterial richness in lung tumor tissue gradually decreased with an increase in the level of PD-L1 expression (p < 0.05). An analysis of ß-diversity indicated a significant positive correlation between the genera Romboutsia and Alistipes in both the lung tumor biopsies and stool samples from NSCLC patients (p < 0.05). Survival analysis showed that NSCLC patients with higher bacterial richness in their stool samples had prolonged overall survival (HR: 2.06, 95% CI: 1.025-4.17, p = 0.0426).

The Role of Programmed Cell Death 1/Programmed Death Ligand 1 (PD-1/PD-L1) Axis in Sepsis-Induced Apoptosis.

Background and Objectives: Sepsis involves a dysregulated host response, characterized by simultaneous immunosuppression and hyperinflammation. Initially, there is the release of pro-inflammatory factors and immune system dysfunction, followed by persistent immune paralysis leading to apoptosis. This study investigates sepsis-induced apoptosis and its pathways, by assessing changes in PD-1 and PD-L1 serum levels, CD4+ and CD8+ T cells, and Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation (APACHE II) severity scores. Materials and Methods: This prospective, observational, single-centre study enrolled 87 sepsis patients admitted to the intensive care unit at the County Emergency Clinical Hospital in Târgu Mureș, Romania. We monitored the parameters on day 1 (the day sepsis or septic shock was diagnosed as per the Sepsis-3 Consensus) and day 5. Results: Our study found a statistically significant variation in the SOFA score for the entirety of the patients between the studied days (p = 0.001), as well as for the studied patient groups: sepsis, septic shock, survivors, and non-survivors (p = 0.001, p = 0.003, p = 0.01, p = 0.03). On day 1, we found statistically significant correlations between CD8+ cells and PD-1 (p = 0.02) and PD-L1 (p = 0.04), CD4+ and CD8+ cells (p < 0.0001), SOFA and APACHE II scores (p < 0.0001), and SOFA and APACHE II scores and PD-L1 (p = 0.001 and p = 0.01). On day 5, we found statistically significant correlations between CD4+ and CD8+ cells and PD-L1 (p = 0.03 and p = 0.0099), CD4+ and CD8+ cells (p < 0.0001), and SOFA and APACHE II scores (p < 0.0001). Conclusions: The reduction in Th CD4+ and Tc CD8+ lymphocyte subpopulations were evident from day 1, indicating that apoptosis is a crucial factor in the progression of sepsis and septic shock. The increased expression of the PD-1/PD-L1 axis impairs costimulatory signalling, leading to diminished T cell responses and lymphopenia, thereby increasing the susceptibility to nosocomial infections.