Clinical Validation of Artificial Intelligence-Powered PD-L1 Tumor Proportion Score Interpretation for Immune Checkpoint Inhibitor Response Prediction in Non-Small Cell Lung Cancer.

PURPOSE: Evaluation of PD-L1 tumor proportion score (TPS) by pathologists has been very impactful but is limited by factors such as intraobserver/interobserver bias and intratumor heterogeneity. We developed an artificial intelligence (AI)-powered analyzer to assess TPS for the prediction of immune checkpoint inhibitor (ICI) response in advanced non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: The AI analyzer was trained with 393,565 tumor cells annotated by board-certified pathologists for PD-L1 expression in 802 whole-slide images (WSIs) stained by 22C3 pharmDx immunohistochemistry. The clinical performance of the analyzer was validated in an external cohort of 430 WSIs from patients with NSCLC. Three pathologists performed annotations of this external cohort, and their consensus TPS was compared with AI-based TPS. RESULTS: In comparing PD-L1 TPS assessed by AI analyzer and by pathologists, a significant positive correlation was observed (Spearman coefficient = 0.925; P < .001). The concordance of TPS between AI analyzer and pathologists according to TPS ≥50%, 1%-49%, and <1% was 85.7%, 89.3%, and 52.4%, respectively. In median progression-free survival (PFS), AI-based TPS predicted prognosis in the TPS 1%-49% or TPS <1% group better than the pathologist's reading, with the TPS ≥50% group as a reference (hazard ratio [HR], 1.49 [95% CI, 1.19 to 1.86] v HR, 1.36 [95% CI, 1.08 to 1.71] for TPS 1%-49% group, and HR, 2.38 [95% CI, 1.69 to 3.35] v HR, 1.62 [95% CI, 1.23 to 2.13] for TPS <1% group). CONCLUSION: PD-L1 TPS assessed by AI analyzer correlates with that of pathologists, with clinical performance also being comparable when referenced to PFS. The AI model can accurately predict tumor response and PFS of ICI in advanced NSCLC via assessment of PD-L1 TPS.

[Evaluation of PD-L1 expression and intratumoral lymphocytic infiltration in triple-negative invasive breast carcinoma]. / Evaluación de la expresión de PD-L1 e infiltración linfocitaria intratumoral en carcinoma de mama invasivo triple negativo.

INTRODUCTION: Triple negative breast cancer endophenotype (TNBC) is one of the least frequent and without therapeutic target; therefore we propose to study the correlation of PD-L1 immune checkpoint with the establishment of tumor microenvironment assessed by intratumoral stromal lymphocyte infiltration (TILS) and its importance in clinical practice. METHODS: A retrospective case-control study was performed, with 31 cases of triple-negative infiltrating breast carcinoma and 57 unmatched controls of Luminal A, Luminal B and HER-2 endophenotype seen in one year. The following variables were evaluated: histologic type and grade, PD-L1 expression with clone 22C3, TILS, lymphovascular invasion, tumor size, lymph node involvement and metastasis. Statistical analysis was performed with the chi-square test and Spearman correlation coefficient test. RESULTS: a statistically significant negative correlation was found between TILS and PD-L1 (rho - 0.106, p 0.025), indicating that the higher the expression of PD-L1, the lower the intratumoral lymphocytic infiltration. In the TILS B (10-40% TILS) and C (40-90% TILS) groups where there was a marked intratumoral inflammatory infiltrate, a greater number of patients were negative for PD-L1 (CPS <10) with 16 and 10 cases, respectively. For TNBC cases a negative association coefficient was identified (rho -0.378) with statistical significance (p 0.01). DISCUSSION: The association between TNBC, TILS and PDL1 expression was established, which is important for the establishment of target therapies and the development of precision medicine.

Introducción: El endofenotipo de cáncer de mama triple negativo (TNBC) es uno de los menos frecuentes y sin diana terapéutica, por tanto, se plantea estudiar la correlación del punto de control inmunológico PD-L1 con el establecimiento de microambiente tumoral evaluado por la infiltración linfocitaria intratumoral estromal (TILs) y su importancia en la práctica clínica. Métodos: Se realizó un estudio retrospectivo de casos y controles, con 31 casos de carcinoma infiltrante de la mama triple negativo y 57 controles no pareados de endofenotipo Luminal A, Luminal B y HER-2 atendidos en un año. Se evaluaron las variables: tipo y grado histológico, expresión PD-L1 con el clon 22C3, TILs, invasión linfovascular, tamaño tumoral, compromiso de ganglios linfáticos y metástasis. El análisis estadístico se ejecutó con la prueba de chi cuadrado y prueba de coeficiente de correlación de Spearman. Resultados: Se encontró una correlación negativa estadísticamente significativa entre TILs y PD-L1 (rho - 0.106, p 0.025), indicando que a mayor expresión de PD-L1, es menor la infiltración linfocitaria intratumoral. En los grupos de TILs B (10-40% TILs) y C (40-90% TILs) donde se presenta marcado infiltrado inflamatorio intratumoral se evidenció mayor número de pacientes negativos para PD-L1 (CPS <10) con 16 y 10 casos respectivamente. Para los casos TNBC se logró identificar un coeficiente de asociación negativa (rho -0.378) y con significancia estadística (p 0.01). Discusión: Se estableció la asociación de TNBC, TILs y expresión de PDL1, lo cual es importante para la instauración de terapias diana y el desarrollo de la medicina de precisión.

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.

Comparison of programmed death-ligand 1 expression in adenocarcinoma and squamous cell carcinoma of the cervix in paraffin blocks of patients with cervical cancer.

AIMS: Cervical cancer (CC) is a common malignancy in women, predominantly caused by human papillomavirus. The most subtypes are adenocarcinomas (AC) and squamous cell carcinomas (SCC), which show various features and treatment responses. Programmed death-ligand 1 (PD-L1) and programmed cell death protein 1 (PD-1) as Immune checkpoint molecules, play a role in immune evasion. We investigated PD-L1 expression in AC and SCC of the cervix and explored its link to clinical characteristics. METHODS AND RESULTS: The present cross-sectional research was done between 2016 and 2022 on samples in Shahid Beheshti University of Medical Sciences-affiliated hospitals in Iran. Histological tissue samples of CCs (16 AC and 48 SCC) were assessed, and clinical information was obtained by reviewing their medical documents. PD-L1 expression was evaluated by immunohistochemistry and we used the combined positive score. SCC cases showed a higher (not significant) PD-L1 expression. The PD-L1 expression and clinical characteristics were not significantly correlated in both subgroups. CONCLUSION: Although SCC cases exhibited higher PD-L1 expression, this difference was non-significant. More investigations should highlight the role of PD-L1 in CC and the potential benefits of immunotherapy.

Scoring PD-L1 Expression in Urothelial Carcinoma: An International Multi-Institutional Study on Comparison of Manual and Artificial Intelligence Measurement Model (AIM-PD-L1) Pathology Assessments.

Assessing programmed death ligand 1 (PD-L1) expression on tumor cells (TCs) using Food and Drug Administration-approved, validated immunoassays can guide the use of immune checkpoint inhibitor (ICI) therapy in cancer treatment. However, substantial interobserver variability has been reported using these immunoassays. Artificial intelligence (AI) has the potential to accurately measure biomarker expression in tissue samples, but its reliability and comparability to standard manual scoring remain to be evaluated. This multinational study sought to compare the %TC scoring of PD-L1 expression in advanced urothelial carcinoma, assessed by either an AI Measurement Model (AIM-PD-L1) or expert pathologists. The concordance among pathologists and between pathologists and AIM-PD-L1 was determined. The positivity rate of ≥ 1%TC PD-L1 was between 20-30% for 8/10 pathologists, and the degree of agreement and scoring distribution for among pathologists and between pathologists and AIM-PD-L1 was similar both scored as a continuous variable or using the pre-defined cutoff. Numerically higher score variation was observed with the 22C3 assay than with the 28-8 assay. A 2-h training module on the 28-8 assay did not significantly impact manual assessment. Cases exhibiting significantly higher variability in the assessment of PD-L1 expression (mean absolute deviation > 10) were found to have patterns of PD-L1 staining that were more challenging to interpret. An improved understanding of sources of manual scoring variability can be applied to PD-L1 expression analysis in the clinical setting. In the future, the application of AI algorithms could serve as a valuable reference guide for pathologists while scoring PD-L1.

Coaxial dual-path electrochemical biosensing and logic strategy-based detection of lung cancer-derived exosomal PD-L1.

Exosomal programmed death ligand-1 (ExoPD-L1) is a vital marker of immune activation in the early stages of tumor therapy and it can inhibit anti-tumor immune responses. However, due to the low expression of ExoPD-L1 in cancer cells, it is difficult to perform highly sensitive assays and accurately differentiate cancer sources. Therefore, we constructed a coaxial dual-path electrochemical biosensor for highly accurate identification and detection of ExoPD-L1 from lung cancer based on chemical-biological coaxial nanomaterials and nucleic acid molecular signal amplification strategies. The measurements showed that the detected ExoPD-L1 concentrations ranged from 6 × 102 particles per mL to 6 × 108 particles per mL, and the detection limit was 310 particles per mL. Compared to other sensors, the electrochemical biosensor designed in this study has a lower detection limit and a wider detection range. Furthermore, we also successfully identified lung cancer-derived ExoPD-L1 by analyzing multiple protein biomarkers expressed on exosomes through the "AND" logic strategy. This sensor platform is expected to realize highly sensitive detection and accurate analysis of multiple sources of ExoPD-L1 and provide ideas for the clinical detection of ExoPD-L1.

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.

Correlation of CT parameters and PD-L1 expression status in gastric cancer.

OBJECTIVE: We aimed to explore the correlation between routine computed tomography (CT) imaging features and programmed cell death ligand-1(PD-L1) expression status in gastric cancer and evaluate the predictive value of imaging parameters for this immunotherapy biomarker. MATERIALS AND METHODS: Patients with gastric adenocarcinoma who underwent abdominal CT three-stage enhanced scan and PD-L1 immunohistochemical testing before treatment were retrospectively examined. All diagnoses were confirmed through pathology. According to the expression status of PD-L1, they were divided into the positive (CPS ≥ 5) or negative group (CPS < 5). Baseline CT imaging features were collected. Diagnostic performances of the different variables were evaluated using receiver operating characteristic (ROC) curve. RESULTS: In total, 67 patients (17 women and 50 men; mean age: 59.55 ± 10.22 years) with gastric adenocarcinoma were included in the study. The overall stages, probability of maximum lymph node short diameter > 1 cm and peak of lesion enhancement occurring in the arterial phase were statistically significant between the two groups (p < 0.05). Moreover, the arterial enhancement fraction (AEF) was significantly higher in the positive group than that in the negative group (p < 0.05), and ROC curve analysis showed that the AEF exhibited a high evaluation efficacy (area under the curve [AUC] = 0.724 [95% confidence interval (CI): 0.602-0.826]). The combined parameters had the best diagnostic efficacy (AUC = 0.825 [95%CI: 0.716-0.933]), sensitivity (75.00%), and specificity (81.40%). CONCLUSIONS: These findings confirm a correlation between CT imaging features and PD-L1 expression status in gastric cancer, and AEF may help evaluate high PD-L1 expression and select patients suitable for immunotherapy.

Prognostic role of PD-L1 expression in head and neck squamous cell carcinoma: An institutional experience from India.

BACKGROUND: Squamous cell carcinoma accounts for > 90% of Head and neck cancers and has a poor 5-year survival rate of only 50%. Immunosuppressive agents like PD-L1 inhibitors have been found to improve survival in many tumour types, including advanced/recurrent head and neck squamous cell carcinoma (HNSCC). The PD-L1 expression in this tumour can also predict clinical outcome. However, this fact still remains to be proven. AIM: The aim was to study the expression of PD-L1 in HNSCC, correlate with clinicopathological parameters and outcome. MATERIAL AND METHOD: This prospective study was conducted between March 2021 to June 2023 in department of Pathology of a tertiary care centre located in northern India. A total of 65 histologically confirmed cases of HNSCC were included. Expression of PD-L1 was determined by immunohistochemistry. The combined positive (CPS) and tumour proportion (TP) scores were calculated. The results were correlated with clinicopathological parameters and outcome using appropriate statistical tools. RESULTS: Considering CPS, 42 (64.6%) cases showed expression of PD-L1. A high score of ≥ 20% was seen in 10 cases (15.4%). PD-L1 expression did not correlate with any of the clinical parameters including age, gender, addiction, site, TNM stage and HPV status. Conventional HNSCC had significantly higher expression of PD-L1. The cases with positive PD-L1 expression had a higher mean survival and a lower mortality, but the difference was not statistically significant. CONCLUSION: PD-L1 expression is more likely to be seen in conventional HNSCC histomorphology. PD-L1 expression is a predictor of better prognosis in HNSCC.

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).

Aptamer-bivalent-cholesterol-mediated proximity entropy-driven exosomal protein reporter for tumor diagnosis.

Exosomal proteins from the parental cells are considered to be promising biomarker sets for precise tumor diagnostics and monitoring. However, the accurate quantitative analysis of low-abundance exosomal proteins remains challenging due to the heterogeneity of clinical samples. Here, we standardized the exosomal concentration with a fluorogenic membrane probe and developed an aptamer-bivalent-cholesterol-mediated Proximity Entropy-driven Exosomal Protein Reporter (PEEPR). The proposed PEEPR enables the in-situ analysis of multiple exosomal proteins by integrating bivalent cholesterol anchor (exosomal lipid bilayer) and aptamer (exosomal proteins) with a proximity entropy-driven circuit. Based on this strategy, we successfully achieved detection limits of 3.9 pg/mL exosomal GPC-3 and 3.4 pg/mL exosomal PD-L1. Notably, the standardization of exosome concentrations is designed to avoid errors due to biological heterogeneity. The results showed that evaluating the levels of exosomal GPC-3 and PD-L1 in clinical samples via this strategy could accurately differentiate healthy individuals, hepatitis B patients, and hepatocellular carcinoma patients. In summary, PEEPR is a promising clinical diagnostic strategy for the quantitative analysis of a variety of tumor-associated exosomal proteins for the precise diagnosis and personalized treatment monitoring of tumors.

Expression and correlation of PD-L1 and HER2 in oesophageal squamous cell carcinoma.

AIMS: In recent years, patients with programmed cell death-Ligand 1 (PD-L1)-positive oesophageal squamous cell carcinoma (OSCC) have been able to benefit from immunotherapy. However, method for improving the treatment efficacy of PD-L1-positive patients is a problem that needs further consideration. Studies on the relationship between human epidermal growth factor receptor 2 (HER2) and PD-L1 expression have recently been reported in certain cancers, but the relationship between PD-L1 and HER2 expression in OSCC is still unclear. METHODS: A total of 263 patients with OSCC were included in the study. PD-L1 protein expression and HER2 protein expression were analysed by immunohistochemistry (IHC), and fluorescence in situ hybridisation (FISH) was performed to assess HER2 gene amplification. The significance of differences between HER2 status, PD-L1 status and clinicopathological parameters was assessed. The relationship between PD-L1 status and HER2 status was examined. RESULTS: Of the 263 OSCC cases, the PD-L1-positive expression rates were 39.2% and 77.2% in OSCC for Tumour Proportion Score (TPS) and Combined Positive Score (CPS), respectively, and PD-L1 expression was associated with the degree of tumour differentiation. The HER2 expression was positive in 24% (63/263) of cases based on IHC and FISH. HER2 expression was not significantly associated with clinicopathological characteristics. PD-L1 TPS expression and CPS expression were significantly positively correlated with HER2 expression in OSCC. CONCLUSIONS: PD-L1 expression was significantly positively correlated with HER2 expression in OSCC. The results provide valuable insight for the future application of HER2-targeted therapy combined with immunotherapy in OSCC.

Comparison of assessment of programmed death-ligand 1 (PD-L1) status in triple-negative breast cancer biopsies and surgical specimens.

AIMS: Programmed death-ligand 1 (PD-L1) status in triple-negative breast cancer (TNBC) is important for immune checkpoint inhibitor therapies but may vary between different immunohistochemical assays, scorings and the type of specimen used for analysis. METHODS: We compared the analytical concordance of three clinically relevant PD-L1 assays (VENTANA SP142, VENTANA SP263 and DAKO 22C3 pharmDx) assessing immune cell score (IC), tumour proportion score and combined positive score (CPS) in preoperative biopsies and resection specimens of primary TNBC. PD-L1 expression was scored on virtual whole slide images and compared with expression data from corresponding surgical specimens. RESULTS: The mean PD-L1 positivity in TNBC biopsies defined as IC ≥1% and CPS ≥1 ranged between 11% and 61% with the lowest positivity for SP142 and highest for SP263. The corresponding surgical specimens showed overall higher positivity rates (53%-75%). When comparing biopsies with surgical specimens, the agreement for PD-L1 positivity with SP263 and 22C3 at IC score ≥1% and CPS ≥1 was fair (kappa 0.47-0.52) and poor for SP142 (kappa 0.15-0.19). Using CPS ≥10 cut-off, the agreement for SP263 was excellent (kappa 0.751) but poor for 22C3 (kappa 0.261). Spearman correlation coefficients ranged between 0.489 and 0.75 indicating a generally moderate to strong correlation between biopsies and surgical specimens for all assays and scores. CONCLUSIONS: We demonstrate high accordance between biopsies and surgical specimens for SP263 and 22C3 scoring but less for SP142. Generally, biopsies are suitable for PD-L1 testing in TNBC but the appropriate assay, scoring and cut-off must be considered.

Machine-learning-based image analysis algorithms improve interpathologist concordance when scoring PD-L1 expression in non-small-cell lung cancer.

Programmed death ligand 1 (PD-L1) expression on tumour cells is the only predictive biomarker of response to immuno-modulatory therapy for patients with non-small-cell lung cancer (NSCLC). Accuracy of this biomarker is hampered by its challenging interpretation. Here we explore if the use of machine-learning derived image analysis tools can improve interpathologist concordance of assessing PD-L1 expression in NSCLC.Five pathologists who routinely score PD-L1 at a major regional referral hospital for thoracic surgery participated. 13 NSCLC small diagnostic biopsies were stained for PD-L1 (SP263 clone) and digitally scanned. Each pathologist independently scored each case with and without the Roche uPath PD-L1 (SP263) image analysis NSCLC algorithm with a wash-out interim period of 6 weeks.A consistent improvement in interpathologist concordance was seen when using the image analysis tool compared with scoring without: (Fleiss' kappa 0.886 vs 0.613 (p<0.0001) and intraclass coefficient correlation 0.954 vs 0.837 (p<0.001)). Five cases (38%) were classified into clinically relevant different categories (negative/weak/strong) by multiple pathologists when not using the image analysis algorithm, whereas only two cases (15%) were classified differently when using the image analysis algorithm.The use of the image analysis algorithm improved the concordance of assessing PD-L1 expression between pathologists. Critically, there was a marked improvement in the placement of cases into more consistent clinical groupings. This small study is evidence that the use of image analysis tools may improve consistency in assessing tumours for PD-L1 expression and may therefore result in more consistent prediction to targeted treatment options.

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.

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.

Systematic assessment of tumor necrosis at baseline in cervical cancer - An independent factor associated with poor outcome.

Cervical cancer (CC) is a leading challenge in oncology worldwide, with high prevalence and mortality rates in young adults, most prominent in low to middle-income countries with marginal screening facilities. From the prospectively collected BioRAIDS (NCT02428842) cohort of primary squamous CC conducted in 7 European countries, a central pathology review was carried out on 294 patients' tumors. The focus was on identification of tumor-stromal characteristics such as CD8+, CD45+, CD68+ staining cells, PD-L1 expression, tumor infiltrating lymphocytes (TILs) together with the degree of tumor necrosis. Both (FIGO-2018) stage (I-II/III-IV) as well as tumor necrosis were highly significantly associated with Progression-free Survival (PFS); with tumor necrosis scoring as most potent independent factor in a multivariable analysis (p < 0.001). Tumor necrosis can be assessed in the very first diagnostic biopsyand our data suggest that this rapid, simple and cost-effective biomarker, should be routinely assessed prior to treatment decisions.

Weakly Supervised Deep Learning Predicts Immunotherapy Response in Solid Tumors Based on PD-L1 Expression.

Programmed death-ligand 1 (PD-L1) IHC is the most commonly used biomarker for immunotherapy response. However, quantification of PD-L1 status in pathology slides is challenging. Neither manual quantification nor a computer-based mimicking of manual readouts is perfectly reproducible, and the predictive performance of both approaches regarding immunotherapy response is limited. In this study, we developed a deep learning (DL) method to predict PD-L1 status directly from raw IHC image data, without explicit intermediary steps such as cell detection or pigment quantification. We trained the weakly supervised model on PD-L1-stained slides from the non-small cell lung cancer (NSCLC)-Memorial Sloan Kettering (MSK) cohort (N = 233) and validated it on the pan-cancer-Vall d'Hebron Institute of Oncology (VHIO) cohort (N = 108). We also investigated the performance of the model to predict response to immune checkpoint inhibitors (ICI) in terms of progression-free survival. In the pan-cancer-VHIO cohort, the performance was compared with tumor proportion score (TPS) and combined positive score (CPS). The DL model showed good performance in predicting PD-L1 expression (TPS ≥ 1%) in both NSCLC-MSK and pan-cancer-VHIO cohort (AUC 0.88 ± 0.06 and 0.80 ± 0.03, respectively). The predicted PD-L1 status showed an improved association with response to ICIs [HR: 1.5 (95% confidence interval: 1-2.3), P = 0.049] compared with TPS [HR: 1.4 (0.96-2.2), P = 0.082] and CPS [HR: 1.2 (0.79-1.9), P = 0.386]. Notably, our explainability analysis showed that the model does not just look at the amount of brown pigment in the IHC slides, but also considers morphologic factors such as lymphocyte conglomerates. Overall, end-to-end weakly supervised DL shows potential for improving patient stratification for cancer immunotherapy by analyzing PD-L1 IHC, holistically integrating morphology and PD-L1 staining intensity. SIGNIFICANCE: The weakly supervised DL model to predict PD-L1 status from raw IHC data, integrating tumor staining intensity and morphology, enables enhanced patient stratification in cancer immunotherapy compared with traditional pathologist assessment.

PD-L1 (SP142) Expression in Primary and Recurrent/Metastatic Triple-Negative Breast Cancers and Its Clinicopathological Significance.

PURPOSE: The programmed death-ligand 1 (PD-L1) SP142 assay identifies patients with triple-negative breast cancer (TNBC) who are most likely to respond to the anti-PD-L1 agent atezolizumab. We aimed to compare PD-L1 (SP142) expression between primary and recurrent/metastatic TNBCs and elucidate the clinicopathological features associated with its expression. MATERIALS AND METHODS: Primary and recurrent/metastatic TNBCs tested with PD-L1 (SP142) were collected, and clinicopathological information of these cases was obtained through a review of slides and medical records. RESULTS: PD-L1 (SP142) positivity was observed in 50.9% (144/283) of primary tumors and 37.8% (31/82) of recurrent/metastatic TNBCs with a significant difference. Recurrent or metastatic sites were associated with PD-L1 positivity, with high PD-L1 positivity in the lung, breast, and soft tissues, and low positivity in the bone, skin, liver, and brain. When comparing PD-L1 expression between primary and matched recurrent/metastatic TNBCs using 55 paired samples, 20 cases (36.4%) showed discordance; 10 cases revealed positive conversion, and another 10 cases revealed negative conversion during metastatic progression. In primary TNBCs, PD-L1 expression was associated with a higher histologic grade, lower T category, pushing border, and higher tumor-infiltrating lymphocyte infiltration. In survival analyses, PD-L1 positivity, especially high positivity, was found to be associated with favorable prognosis of patients. CONCLUSION: PD-L1 (SP142) expression was lower in recurrent/metastatic TNBCs, and substantial cases showed discordance in its expression between primary and recurrent/metastatic sites, suggesting that multiple sites may need to be tested for PD-L1 (SP142) when considering atezolizumab therapy. PD-L1 (SP142)-positive TNBCs seems to be associated with favorable clinical outcomes.

Face to face among different chemo-immunotherapy combinations in the first line treatment of patients with advanced non-small cell lung cancer: Results of an international expert panel meeting by the italian association of thoracic oncology (AIOT).

BACKGROUND: The combination of platinum-based chemotherapy with immune-checkpoint inhibitors (ICIs) is a standard of care option in the front-line treatment of advanced non-small cell lung cancer (NSCLC). Positive efficacy and safety results have been demonstrated with different chemo-ICI combinations in the corresponding clinical trials, however no randomized prospective comparison is available and there is no evidence on how to choose among the available regimens. METHODS: A virtual International Expert Panel took place in July 2023 to review data on chemo-ICI regimens available in the first-line setting in patients with NSCLC, and reach common considerations both in clinical practice and in research setting. RESULTS: Overall, all panelists agreed that safety of the chemo-immunotherapy combination regimens is supported by reviewed data, showing no additional toxicity concerns over those of the individual components of each regimen and highlighting differences in toxicity profile based on ICI component (single anti-PD-1 versus double anti-PD-1 and anti-CTLA-4). Among disease characteristics, PD-L1 value (<1%) but not histology was considered a potential selection factor in favor of the combination with dual ICI. With regards to clinical features, the panelists agreed that chemotherapy, whichever the ICI combination regimen, remains the backbone to counteract disease-related symptoms included those conditioning worse performance status. The panelists defined high, medium, and low priorities in clinical research. High priority was attributed to prospectively evaluating the impact of the addition of anti-CTLA-4 on brain metastasis, biomarker subgroups, and the optimal duration and schedule of combination regimens. CONCLUSIONS: Based on the available evidence, the panelists reached common considerations on strengths and differences between chemotherapy plus single agent ICI and chemotherapy plus double agent ICIs in patients with advanced NSCLC. In the absence of direct comparison, different toxicity profile and subgroup analysis by PD-L1 are considered as the main potential features to select among the two regimens, however to be confirmed by recommended prospective randomized clinical research.