Dataset Information

Concordance of PD-L1 Status Between Image-Guided Percutaneous Biopsies and Matched Surgical Specimen in Non-Small Cell Lung Cancer.

ABSTRACT:

Objective

Programmed death-ligand 1 (PD-L1) expression status is a crucial index for identifying patients who will benefit from anti-programmed cell death protein 1 (PD-1)/PD-L1 therapy for non-small cell lung cancer (NSCLC). However, the concordance of Tumor Proportion Score (TPS) between biopsies and matched surgical specimens remains controversial. This study aims to evaluate the concordance of PD-L1 expression between image-guided percutaneous biopsies and matched surgical specimens.

Method

We evaluated 157 patients diagnosed with operable NSCLC on both surgical tissue sections and matched lung biopsies retrospectively. The patients underwent either regular computed tomography (CT)-guided biopsy (n = 82) or positron emission tomography (PET)/CT-guided biopsy (n = 75). The concordance between surgical specimens and lung biopsies for PD-L1 TPS was evaluated using Cohen's kappa (?) coefficient.

Results

Immunohistochemical expression of PD-L1 was evaluated in both surgical resected specimens and matched biopsies in the eligible 138 patients. The concordance rate of PD-L1 expression between surgical tissue sections and matched biopsies was fairly high at 84.1% (116/138), and the ? value was 0.73 (95% CI: 0.63-0.83, P < 0.001). The concordance rate was higher for tissue sections from PET/CT-guided biopsy than for tissue sections from CT-guided biopsy [88.6% (62/70, ? value: 0.81) vs 79.4% (54/68, ? value: 0.66)].

Conclusion

PD-L1 TPS was strongly concordant between surgical specimens and matched lung biopsies. Thus, the routine evaluation of PD-L1 expression in diagnostic percutaneous biopsies could be reliable for identifying patients who will benefit from anti-PD-1/PD-L1 immunotherapy.

SUBMITTER: Zhao L

PROVIDER: S-EPMC7940543 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Concordance of PD-L1 Status Between Image-Guided Percutaneous Biopsies and Matched Surgical Specimen in Non-Small Cell Lung Cancer.

Zhao Liang L Chen Peiqiong P Fu Kaili K Li Jinluan J Dai Yaqing Y Wang Yuhuan Y Zhuang Yanzhen Y Sun Long L Chen Haojun H Lin Qin Q

Frontiers in oncology 20210223

<h4>Objective</h4>Programmed death-ligand 1 (PD-L1) expression status is a crucial index for identifying patients who will benefit from anti-programmed cell death protein 1 (PD-1)/PD-L1 therapy for non-small cell lung cancer (NSCLC). However, the concordance of Tumor Proportion Score (TPS) between biopsies and matched surgical specimens remains controversial. This study aims to evaluate the concordance of PD-L1 expression between image-guided percutaneous biopsies and matched surgical specimens. ...[more]

PMID: 33708615

Similar Datasets

Project description:BackgroundImmune checkpoint therapies (ICTs) targeting the programmed cell death-1 (PD1)/programmed cell death ligand-1 (PD-L1) pathway have improved outcomes for patients with non-small cell lung cancer (NSCLC), particularly those with high PD-L1 expression. However, the predictive value of manual PD-L1 scoring is imperfect and alternative measures are needed. We report an automated image analysis solution to determine the predictive and prognostic values of the product of PD-L1+ cell and CD8+ tumor infiltrating lymphocyte (TIL) densities (CD8xPD-L1 signature) in baseline tumor biopsies.MethodsArchival or fresh tumor biopsies were analyzed for PD-L1 and CD8 expression by immunohistochemistry. Samples were collected from 163 patients in Study 1108/NCT01693562, a Phase 1/2 trial to evaluate durvalumab across multiple tumor types, including NSCLC, and a separate cohort of 199 non-ICT- patients. Digital images were automatically scored for PD-L1+ and CD8+ cell densities using customized algorithms applied with Developer XD™ 2.7 software.ResultsFor patients who received durvalumab, median overall survival (OS) was 21.0 months for CD8xPD-L1 signature-positive patients and 7.8 months for signature-negative patients (p = 0.00002). The CD8xPD-L1 signature provided greater stratification of OS than high densities of CD8+ cells, high densities of PD-L1+ cells, or manually assessed tumor cell PD-L1 expression ≥25%. The CD8xPD-L1 signature did not stratify OS in non-ICT patients, although a high density of CD8+ cells was associated with higher median OS (high: 67 months; low: 39.5 months, p = 0.0009) in this group.ConclusionsAn automated CD8xPD-L1 signature may help to identify NSCLC patients with improved response to durvalumab therapy. Our data also support the prognostic value of CD8+ TILS in NSCLC patients who do not receive ICT.Trial registrationClinicalTrials.gov identifier: NCT01693562 . Study code: CD-ON-MEDI4736-1108. Interventional study (ongoing but not currently recruiting). Actual study start date: August 29, 2012. Primary completion date: June 23, 2017 (final data collection date for primary outcome measure).

Project description:Although preoperative chemoradiotherapy (CRT) and surgical mesorectal resection is the standard of care for locally advanced rectal carcinomas, it is still difficult to predict which patients will respond to treatment. We explored how differential stromal transcriptomic profiles from microdissected pretreatment rectal biopsies can be used to define an immunohistochemical score based on two CAF-specific proteins for predicting neoadjuvant treatment response. The analysis of differentially expressed genes (DEGs) of stroma and tumour glands from responder and non-responder patients shows that most changes were associated with the stromal compartment. Gene ontology analysis revealed that the DEGs codify mainly for extracellular matrix and ribosomal components. We built a CAF-specific classifier with genes showing monotonic changes in expression according to the tumour regression grade (coefficient >1; FN1, COL3A1, COL1A1, MMP2 and IGFBP5). These are the genes that display the biggest a priori differences in expression between non-responder and responder stroma. We translated these five genes at the protein level by means of immunohistochemical staining in a cohort of 38 patients. For predictive purposes we used a leave-one-out cross-validated (LOOCV) model with a positive predictive value (PPV) of 80%. Classifier optimisation with Random Forest identified FN1 and COL3A1 as the best predictors. Rebuilding the LOOCV regression model improved the classification performance with a PPV of 89.5% and a negative predictive value (NPV) of 73.7%. An independent cohort of 36 patients was used to validate the classifier performance, which had a PPV of 84.2% and an NPV of 70.6%. In a multivariate analysis the two-protein classifier proved to be the only independent predictor of response (HR=2.58; P=0.003). We also explored a pharmacogenomic approach to gather information about possible therapeutic strategies for non-responder patients. In conclusion, we developed a two-protein immunohistochemical classifier that performs well at predicting the absence of response to neoadjuvant treatment in rectal cancer.

Dataset Information

Concordance of PD-L1 Status Between Image-Guided Percutaneous Biopsies and Matched Surgical Specimen in Non-Small Cell Lung Cancer.

Objective

Method

Results

Conclusion

Publications

Concordance of PD-L1 Status Between Image-Guided Percutaneous Biopsies and Matched Surgical Specimen in Non-Small Cell Lung Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets