Heterogeneity of PD-L1 expression in non-small cell lung cancer: Implications for specimen sampling in predicting treatment response

Longitudinal analysis of PD-L1 expression in patients with relapsed NSCLC

BACKGROUND

The use and approval of immune checkpoint inhibitors for the treatment of non-small cell lung cancer (NSCLC) depends on PD-L1 expression in the tumor tissue. Nevertheless, PD-L1 often fails to predict response to treatment. One possible explanation could be a change in PD-L1 expression during the course of the disease and the neglect of reassessment. The purpose of this study was a longitudinal analysis of PD-L1 expression in patients with relapsed NSCLC.

METHODS

We retrospectively analyzed PD-L1 expression in patients with early-stage NSCLC and subsequent relapse in preoperative samples, matched surgical specimens and biopsy samples of disease recurrence. Ventana PD-L1 (SP263) immunohistochemistry assay was used for all samples. PD-L1 expression was scored based on clinically relevant groups (0%, 1%-49%, and ≥50%). The primary endpoint was the change in PD-L1 score group between preoperative samples, matched surgical specimens and relapsed tumor tissue.

RESULTS

395 consecutive patients with stages I-III NSCLC and 136 (34%) patients with a subsequent relapse were identified. For 87 patients at least two specimens for comparison of PD-L1 expression between early stage and relapsed disease were available. In 72 cases, a longitudinal analysis between preoperative biopsy, the surgically resected specimen and biopsy of disease recurrence was feasible. When comparing preoperative and matched surgical specimens, a treatment-relevant conversion of PD-L1 expression group was found in 25 patients (34.7%). Neoadjuvant treatment showed no significant effect on PD-L1 alteration (p=0.39). In 32 (36.8%) out of 87 cases, a change in PD-L1 group was observed when biopsies of disease relapse were compared with early-stage disease. Adjuvant treatment was not significantly associated with a change in PD-L1 expression (p=0.53). 39 patients (54.2%) showed at least 1 change into a different PD-L1 score group during the course of disease. 14 patients (19.4%) changed the PD-L1 score group twice, 5 (6.9%) of them being found in all different score groups.

CONCLUSION

PD-L1 expression shows dynamic changes during the course of disease. There is an urgent need for consensus guidelines to define a PD-L1 testing strategy including time points of reassessment, the number of biopsies to be obtained and judgment of surgical specimens.

Association of PD-L1 expression with driver gene mutations and clinicopathological characteristics in non-small cell lung cancer: A real-world study of 10 441 patients

BACKGROUND

Programmed death ligand-1 (PD-L1) expression is a well-known predictive biomarker of response to immune checkpoint blockade in non-small cell lung cancer (NSCLC). However, there is limited evidence of the relationship between PD-L1 expression, clinicopathological features, and their association with major driver mutations in NSCLC patients in Latin America.

METHODS

This retrospective study included patients from Argentina with advanced NSCLC, and centralized evaluation of PD-L1 expression concurrently with genomic alterations in the driver genes EGFR, ALK, ROS1, BRAF, and/or KRAS G12C in FFPE tissue samples.

RESULTS

A total of 10 441 patients with advanced NSCLC were analyzed. Adenocarcinoma was the most frequent histological subtype (71.1%). PD-L1 expression was categorized as PD-L1 negative (45.1%), PD-L1 positive low-expression 1%-49% (32.3%), and PD-L1 positive high-expression ≥50% (22.6%). Notably, current smokers and males were more likely to have tumors with PD-L1 tumor proportion score (TPS) ≥50% and ≥ 80% expression, respectively (p < 0.001 and p = 0.013). Tumors with non-adenocarcinoma histology had a significantly higher median PD-L1 expression (p < 0.001). Additionally, PD-L1 in distant nodes was more likely ≥50% (OR 1.60 [95% CI: 1.14-2.25, p < 0.01]). In the multivariate analysis, EGFR-positive tumors were more commonly associated with PD-L1 low expression (OR 0.62 [95% CI: 0.51-0.75], p < 0.01), while ALK-positive tumors had a significant risk of being PD-L1 positive (OR 1.81 [95% CI: 1.30-2.52], p < 0.01).

CONCLUSIONS

PD-L1 expression was associated with well-defined clinicopathological and genomic features. These findings provide a comprehensive view of the expression of PD-L1 in patients with advanced NSCLC in a large Latin American cohort.

Noninvasive Evaluation of Tumoral PD-L1 Using a Novel 99mTc-Labeled Nanobody Tracer with Rapid Renal Clearance

The expression level of PD-L1 in tumor tissue is considered one of the effective biomarkers to guide PD-1/PD-L1 therapy. Quantifying whole-body PD-L1 expression by SPECT imaging may help in selecting patients that potentially respond to PD-1/PD-L1 therapy. Nanobody is the smallest antibody fragment with antigen-binding ability that is well suited for radionuclide imaging. Nevertheless, high retention of radioactivity in the kidney may limit its clinical translation. The present study aimed to screen, design, and prepare a nanobody-based SPECT probe with rapid renal clearance to evaluate the PD-L1 expression level in vivo noninvasively. A phage library was constructed by immunizing alpaca with recombinant human PD-L1 protein, and 17 anti-PD-L1 nanobodies were screened by the phage display technique. After sequence alignment and flow cytometry analysis, APN09 was selected as the candidate nanobody, and a GGGC chelator was attached to its C-terminus for 99mTc labeling to prepare a SPECT imaging probe. The affinity and specificity of 99mTc-APN09 were evaluated by protein and cell-binding experiments, and SPECT imaging and biodistribution were performed in a mouse model with bilateral transplantation of A549 and A549PD-L1 tumors. The ability of 99mTc-APN09 to quantify the PD-L1 expression level in vivo was validated in tumor models with different PD-L1 expression levels. 99mTc-APN09 had a radiochemical purity higher than 99% and a binding equilibrium dissociation constant of 21.44 ± 1.65 nM with hPD-L1, showing high affinity. SPECT imaging results showed that 99mTc-APN09 could efficiently detect PD-L1-positive tumors within 0.5 h, and the quantitative results of SPECT were well correlated with the expression level of PD-L1 in cell lines. SPECT imaging and biodistribution results also showed that 99mTc-APN09 was rapidly cleared from the kidney in 2 h postinjection. 99mTc-APN09 was a simple and stable tool for visualizing PD-L1 expression in the whole body. In addition, due to its significant reduction in renal retention, it has better prospects for clinical translation.

Treatment response of advanced HNSCC towards immune checkpoint inhibition is associated with an activated effector memory T cell phenotype

Locally advanced or metastatic head and neck squamous cell carcinoma (HNSCC) is associated with a poor prognosis. The introduction of PD-1 inhibitors has led to a significant improvement in survival, but only a subpopulation of patients responds to therapy. Current biomarkers cannot reliably identify these patients. The identification of biomarkers for the prediction and monitoring of immunotherapy is therefore of great importance. In this study, we characterized lymphocyte subsets in the peripheral blood of HNSCC patients under PD-1 inhibition. Patients with primary response (n=11) to PD-1 inhibition showed an increase of the CD3+ effector memory (CD3/EM) population and an elevated expression of the activation marker CD69 in CD3+ T cells, particularly in the CD3/EM subpopulation at 3 months when treatment response was assessed. In contrast, patients with primary treatment failure and progressive disease (n=9) despite PD-1 inhibition had lower absolute lymphocyte counts and an increased expression of CTLA-4 in CD3+ T cells at the time of treatment failure compared with baseline, particularly in CD4+ and CD8+ effector memory populations. Our results demonstrate that HNSCC patients' response to immune checkpoint inhibition shows a distinct immune signature in peripheral blood, which could help identify refractory patients earlier. Furthermore, strategies to overcome primary therapy failure by inducing a beneficial T cell phenotype or adding alternative immune checkpoint inhibitors could improve response rates and survival of HNSCC patients.

PD-L1 assessment in lung cancer biopsies-pitfalls and limitations

The programmed cell death-ligand 1 (PD-L1) protein expression on tumor cells predicts the efficacy of immunotherapy in patients with non-small cell lung cancer. However, the assessment of PD-L1 expression on tumor cells has limited power for selecting patients for immunotherapy due to intra-tumoral heterogeneity and inter-tumoral heterogeneity of PD-L1 expression, the inter-observer variability in scoring PD-L1 staining, and reproducibility. These difficulties and pitfalls in interpreting the PD-L1 assessment are discussed in detail in this review.

Artificial Intelligence-Based Treatment Decisions: A New Era for NSCLC

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality among women and men, in developed countries, despite the public health interventions including tobacco-free campaigns, screening and early detection methods, recent therapeutic advances, and ongoing intense research on novel antineoplastic modalities. Targeting oncogenic driver mutations and immune checkpoint inhibition has indeed revolutionized NSCLC treatment, yet there still remains the unmet need for robust and standardized predictive biomarkers to accurately inform clinical decisions. Artificial intelligence (AI) represents the computer-based science concerned with large datasets for complex problem-solving. Its concept has brought a paradigm shift in oncology considering its immense potential for improved diagnosis, treatment guidance, and prognosis. In this review, we present the current state of AI-driven applications on NSCLC management, with a particular focus on radiomics and pathomics, and critically discuss both the existing limitations and future directions in this field. The thoracic oncology community should not be discouraged by the likely long road of AI implementation into daily clinical practice, as its transformative impact on personalized treatment approaches is undeniable.

Redetermination of PD-L1 expression after chemio-radiation in locally advanced PDL1 negative NSCLC patients: retrospective multicentric analysis

Background

Chemoradiation therapy (CRT) is the treatment of choice for locally advanced non-small cell lung cancer (LA-NSCLC). Several clinical trials that combine programmed cell death 1 (PD1) axis inhibitors with radiotherapy are in development for patients with LA-NSCLC. However, the effect of CRT on tumor cells programmed cell death ligand-1 (PD-L1) expression is unknown.

Methods

In this multicentric retrospective study, we analyzed paired NSCLC specimens that had been obtained pre- and post-CRT. PD-L1 expression on tumor cells was studied by immunohistochemistry. The purpose of this study was to evaluate the feasibility, risk of complications, and clinical relevance of performing re-biopsy after CRT in patients with PD-L1 negative LA-NSCLC.

Results

Overall, 31 patients from 6 centers with PD-L1 negative LA-NSCLC were analyzed. The percentage of tumor cells with PD-L1 expression significantly increased between pre- and post-CRT specimens in 14 patients (45%). Nine patients had unchanged PD-L1 expression after CRT, in five patients the rebiopsy material was insufficient for PD-L1 analysis and in two patients no tumor cells at rebiopsy were found. The post-rebiopsy complication rate was very low (6%). All patients with positive PD-L1 re-biopsy received Durvalumab maintenance after CRT, except one patient who had a long hospitalization for tuberculosis reactivation. Median PFS of patients with unchanged or increased PD-L1 expression was 10 and 16.9 months, respectively.

Conclusion

CRT administration can induce PD-L1 expression in a considerable fraction of PD-L1 negative patients at baseline, allowing them receiving the maintenance Durvalumab in Europe. Hence, after a definitive CRT, PD-L1 redetermination should be considered in patients with LA-NSCLC PD-L1 negative, to have a better selection of maintenance Durvalumab candidates.

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.

Improving practice in PD-L1 testing of non-small cell lung cancer in the UK: current problems and potential solutions

AIMS

Programmed cell death ligand 1 (PD-L1) expression, used universally to predict response of non-small cell lung cancer (NSCLC) to immune-modulating drugs, is a fragile biomarker due to biological heterogeneity and challenges in interpretation. The aim of this study was to assess current PD-L1 testing practices in the UK, which may help to define strategies to improve its reliability and consistency.

METHODS

A questionnaire covering NSCLC PD-L1 testing practice was devised and members of the Association of Pulmonary Pathologists were invited to complete this online.

RESULTS

Of 44 pathologists identified as involved in PD-L1 testing, 32 (73%) responded. There was good consistency in practice and approach, but there was wide variability in the distribution of PD-L1 scoring. Although the proportions of scores falling into the three groups (negative, low and high) defined by the 1% and 50% 'cut-offs' (38%, 33% and 27%, respectively) reflect the general experience, the range within each group was wide at 23-70%, 10-60% and 15-36%, respectively.

CONCLUSIONS

There is inconsistency in the crucial endpoint of PD-L1 testing of NSCLC, the expression score that guides management. Addressing this requires formal networking of individuals and laboratories to devise a strategy for its reduction.

Meta-Analysis of Circulating Tumor Cell PD-L1 Expression and the Association with Clinical Outcomes in Non-Small Cell Lung Cancer

BACKGROUND

Programmed death ligand-1 (PD-L1) expression on circulating tumor cells (CTCs) has been suggested to provide prognostic information in non-small cell lung cancer (NSCLC), but consensus relative to treatment outcomes is lacking. We conducted the first comprehensive meta-analysis exploring its potential as a prognostic and predictive marker, and assessed the concordance between PD-L1 + CTCs and paired tumor tissue in NSCLC patients.

METHOD

A comprehensive search was applied to PubMed and EMBASE to identify 26 studies that evaluated PD-L1 + CTCs and their association with survival outcomes in 1236 NSCLC patients.

RESULTS

The meta-analysis estimated a mean PD-L1 + CTCs detection rate of 61% (95% CI, 49-72). Subgroup analysis based on treatment showed that PD-L1 + CTCs was not significantly associated with better overall survival (OS) in NSCLC patients treated with immune checkpoint inhibitors (ICIs) (Hazard Ratio (HR) = 0.96, 95% CI, 0.35-2.65, P = 0.944), but was predictive of worse OS in those treated with other therapies (HR = 2.11, 95% CI, 1.32-3.36, P = 0.002). Similarly, PD-L1 + CTCs was not significantly associated with superior progressing free survival (PFS) in NSCLCs treated with ICIs (HR = 0.67, 95% CI, 0.41-1.09, P = 0.121), but was significantly associated with shorter PFS in patients treated with other therapies (HR = 1.91, 95% CI, 1.24-2.94, P = 0.001). The overall estimate for the concordance between PD-L1 expression on CTCs and tumor cells was 63% (95% CI, 44-80).

CONCLUSION

The average detection rate of PD-L1 + CTCs was comparable to the rate of PD-L1 expression in NSCLC tumors. There was a trend towards better PFS in ICI-treated NSCLC patients with PD-L1 + CTCs. Larger longitudinal studies on the association of PD-L1 + CTCs with clinical outcomes in NSCLC patients treated with ICIs are warranted.

Circulating tumour cells and PD-L1-positive small extracellular vesicles: the liquid biopsy combination for prognostic information in patients with metastatic non-small cell lung cancer

BACKGROUND

Circulating tumour cells (CTCs), circulating tumour DNA (ctDNA), and extracellular vesicles (EVs) are minimally invasive liquid biopsy biomarkers. This study investigated whether they predict prognosis, alone or in combination, in heterogenous unbiased non-small cell lung cancer (NSCLC) patients.

METHODS

Plasma samples of 54 advanced NSCLC patients from a prospective clinical trial. CtDNA mutations were identified using the UltraSEEK™ Lung Panel (MassARRAY® technology). PD-L1 expression was assessed in small EVs (sEVs) using an enzyme-linked immunosorbent assay.

RESULTS

At least one ctDNA mutation was detected in 37% of patients. Mutations were not correlated with overall survival (OS) (HR = 1.1, 95% CI = 0.55; 1.83, P = 0.980) and progression-free survival (PFS) (HR = 1.00, 95% CI = 0.57-1.76, P = 0.991). High PD-L1+ sEV concentration was correlated with OS (HR = 1.14, 95% CI = 1.03-1.26, P = 0.016), but not with PFS (HR = 1.08, 95% CI = 0.99-1.18, P = 0.095). The interaction analysis suggested that PD-L1+ sEV correlation with PFS changed in function of CTC presence/absence (P interaction = 0.036). The combination analysis highlighted worse prognosis for patients with CTCs and high PD-L1+ sEV concentration (HR = 7.65, 95% CI = 3.11-18.83, P < 0.001). The mutational statuses of ctDNA and tumour tissue were significantly correlated (P = 0.0001).

CONCLUSION

CTCs and high PD-L1+ sEV concentration correlated with PFS and OS, but not ctDNA mutations. Their combined analysis may help to identify patients with worse OS.

TRIAL REGISTRATION

NCT02866149, Registered 01 June 2015, https://clinicaltrials.gov/ct2/show/study/NCT02866149 .

Prediction of Tumor PD-L1 Expression in Resectable Non-Small Cell Lung Cancer by Machine Learning Models Based on Clinical and Radiological Features: Performance Comparison With Preoperative Biopsy

OBJECTIVE

We investigated if PD-L1 expression can be predicted by machine learning using clinical and imaging features.

METHODS

We included 117 patients with c-stage I/II non-small cell lung cancer who underwent radical resection. A total of 3951 radiomic features were extracted by defining the tumor (within tumor contour), rim (contour ±3 mm) and exterior (contour +10 mm) on preoperative contrast computed tomography. After feature selection by Boruta algorithm, prediction models of tumor PD-L1 expression (22C3: ≥1%, <1%) of resected specimens were constructed using Random Forest: radiomics, clinical, and combined models. Their performance was evaluated by 5-fold cross-validation, and AUCs were compared using Delong test. Next, study groups were categorized as patients without biopsy (training set), and those with biopsy (test set). Predictive ability of biopsy was compared to each prediction model.

RESULTS

Of 117 patients (66 ± 10 years old, 48% male), 33 (28.2%) had PD-L1≥1%. Mean AUC of PD-L1≥1% for the validation set in radiomics, clinical, and combined models were 0.80, 0.80, and 0.83 (P = .32 vs. clinical model), respectively. The diagnosis of malignancy was made in 22 of 38 (58%) patients with attempted biopsies, and PD-L1 was measurable in 19 of 38 (50%) patients. Diagnostic accuracies of PD-L1≥1% from 19 determinable biopsies and 38 all attempted biopsies were 0.68 and 0.34, respectively. These were out performed by machine learning: 0.71, 0.71, and 0.74 for radiomics, clinical, and combined models, respectively.

CONCLUSIONS

Our machine learning could be an adjunctive tool in estimating PD-L1 expression prior to neoadjuvant treatment, particularly when PD-L1 is indeterminable with biopsy.

Evaluation of PD-1 T lymphocytes in bronchoalveolar lavage in lung cancer compared to benign lung diseases

The expression of the programmed cell death protein 1 (PD-1) has been shown to be markedly increased in tumor-infiltrating lymphocytes. However, the proportion of PD-1 + T cells in the bronchoalveolar lavage (BAL) of lung cancer patients has not been sufficiently evaluated so far. In this prospective study, the proportion of PD-1 + CD4 + as well as PD-1 + CD8 + T cells in BAL samples, isolated from patients with lung cancer, asthma or interstitial lung disease (ILD), were determined via flow cytometry and compared for differences. Bronchoalveolar lavage was performed in 34 patients (14 patients with lung cancer, 10 patients with asthma, 10 patients with ILD). The highest median proportion of PD-1 + CD4 + or PD-1 + CD8 + T cells were found in patients with ILD (83.1% [IQR 72.1; 87.5] and 73.8% [IQR 60.3; 86.3]) followed by patients with lung cancer (66.4% [IQR 59; 69] and 77.1% [IQR 35.8; 82.3]) and patients with asthma (61.3% [IQR 57.4; 70.5] and 57.3% [IQR 46; 65]). Thereby, the difference in the proportion of PD-1 + CD3 + CD4 + BAL cells between ILD patients and asthmatics was significantly different (p = 0.04). The proportion of PD-1 + CD4 + and PD-1 + CD8 + T cells in the BAL of patients with lung cancer did not differ significantly to patients with benign lung diseases. The highest proportion was observed in ILD patients suggesting further research to evaluate the role of the PD-1/PD-L1 pathway in ILD patients.

The nexus of dynamic T cell states and immune checkpoint blockade therapy in the periphery and tumor microenvironment

Immune checkpoint blockade (ICB) therapies, that is, using monoclonal antibodies to reinvigorate tumor-reactive, antigen-specific T cells from the inhibitory effects of CTLA-4, PD-1 and PD-L1 immune checkpoints, have revolutionized the therapeutic landscape of modern oncology. However, only a subset of patients can benefit from the ICB therapy. Biomarkers associated with ICB response, resistance and prognosis have been subjected to intensive research in the past decade. Early studies focused on the analysis of tumor specimens and their residing microenvironment. However, biopsies can be challenging to obtain in clinical practice, and do not reflect the dynamic changes of immunological parameters during the ICB therapy. Recent studies have investigated profiles of antigen-specific T cells derived from the peripheral compartment using multi-omics approaches. By tracking the clonotype and diversity of tumor-reactive T cell receptor repertoire, these studies collectively establish that de novo priming of antigen-specific T cells in peripheral blood occurs throughout the course of ICB, whereas preexisting T cells prior to ICB are exhausted to various degrees. Here, we review what is known about ICB-induced T cell phenotypic and functional changes in cancer patients both within the tumor microenvironment and in the peripheral compartment. A better understanding of parameters influencing the response to ICBs will provide rationales for developing novel diagnostics and combinatorial therapeutic strategies to maximize the clinical efficacies of ICB therapies.

Performance of endobronchial ultrasound transbronchial needle aspiration as the first nodal staging procedure for the determination of programmed death ligand-1 expression in non-small cell lung cancer patients

PURPOSE

The determination of the programmed death ligand-1 (PD-L1) expression is part of the diagnostic algorithm for advanced non-small cell lung cancer (NSCLC) patients. We aimed to analyze the diagnostic performance of EBUS-TBNA performed as first-choice nodal staging procedure for the determination of PD-L1 expression in NSCLC patients.

METHODS

Longitudinal-prospective study including NSCLC patients diagnosed between January 2018 and October 2019, for whom a primary tumor biopsy sample and an EBUS-TBNA cytological malignant sample were available. Samples with fewer than 100 malignant cells were considered inadequate. PDL-1 IHC 22C3 pharmDx antibody was used. The percentage of tumor cells expressing PD-L1, setting 1% and 50% as cutoff points, was collected. The weighted kappa coefficient was used to assess the concordance of PD-L1 expression. The PD-L1 expression was compared in precision terms.

RESULTS

From a total of 43 patients, 53 pairs of samples were obtained, of which 23 (43.4%) were adequate and included for analysis. The weighted kappa coefficient for PD-L1 expression was 0.41 (95% CI 0.15-0.68) and 0.56 (95% CI 0.23-0.9) for cutoff values ≥ 1% and ≥ 50%, respectively. In advanced stages, the weighted kappa coefficient was 0.6 (95% CI 0.3-0.9) and 1 (95% CI 1-1) for PD-L1 expression cutoff values ≥ 1% and ≥ 50%, respectively. EBUS-TBNA showed a sensitivity, specificity, positive predictive value, and negative predictive value of 1 to detect PDL-1 expression ≥ 50% in advanced stages.

CONCLUSION

EBUS-TBNA performed as first nodal staging procedure in advanced NSCLC patients provides reliable specimens for the detection of PD-L1 expression ≥ 50% and could guide immunotherapy.

Programmed cell death ligand 1 (PD-L1) expression in non-small cell lung cancer: Findings from a tertiary care institute in western part of India

BACKGROUND

Immune checkpoint inhibitors targeting either programmed cell death protein 1 (PD-1) or programmed cell death ligand 1 (PD-L1) have been established as a novel target for immunotherapy in non-small cell lung cancer (NSCLC). Prevalence of PD-L1 expression in NSCLC varies from 13% to 70%, with sparse data from the Indian subcontinent. In this study, we looked at PD-L1 expression and its association with demographic, clinical, radiologic and pathologic parameters in NSCLC patients.

METHODS

This was an observational study carried over a period of 18 months in which 65 patients of NSCLC were included. Immunohistochemistry (IHC) for PD-L1 was done using an automated IHC stainer and testing was performed using PD-L1 IHC CAL10. For statistical analysis, unpaired t test, Chi square test, Fisher's exact test and binomial logistic regression were used. P < 0.05 was taken to be statistically significant.

RESULTS

Mean age of the patients was 62.9 ± 9.2 years, and majority (87.3%) of them were males. Seventeen (26.2%) patients expressed PD-L1, among whom 10 had high PD-L1 expression (≥50%) and 7 had low PD-L1 expression (1-49%). PD-L1 expression was seen in 13 out of 43 cases of squamous cell carcinoma (SCC) and 4 out of 15 cases of adenocarcinoma. On applying binomial logistic regression analysis, association between smoking and PD-L1 expression was found to be insignificant.

CONCLUSION

Almost a quarter of NSCLC cases were PD-L1 positive without any difference in expression between SCC and adenocarcinoma. PD-L1 status was not associated with any specific demographic, clinical or radiologic parameter including the histologic subtype.

Circulating H3K27 Methylated Nucleosome Plasma Concentration: Synergistic Information with Circulating Tumor DNA Molecular Profiling

The molecular profiling of circulating tumor DNA (ctDNA) is a helpful tool not only in cancer treatment, but also in the early detection of relapse. However, the clinical interpretation of a ctDNA negative result remains challenging. The characterization of circulating nucleosomes (carrying cell-free DNA) and associated epigenetic modifications (playing a key role in the tumorigenesis of different cancers) may provide useful information for patient management, by supporting the contributive value of ctDNA molecular profiling. Significantly elevated concentrations of H3K27Me3 nucleosomes were found in plasmas at the diagnosis, and during the follow-up, of NSCLC patients, compared to healthy donors (p-value < 0.0001). By combining the H3K27Me3 level and the ctDNA molecular profile, we found that 25.5% of the patients had H3K27Me3 levels above the cut off, and no somatic alteration was detected at diagnosis. This strongly supports the presence of non-mutated ctDNA in the corresponding plasma. During the patient follow-up, a high H3K27Me3-nucleosome level was found in 15.1% of the sample, despite no somatic mutations being detected, allowing the identification of disease progression from 43.1% to 58.2% over molecular profiling alone. Measuring H3K27Me3-nucleosome levels in combination with ctDNA molecular profiling may improve confidence in the negative molecular result for cfDNA in lung cancer at diagnosis, and may also be a promising biomarker for molecular residual disease (MRD) monitoring, during and/or after treatment.

E-cadherin expression in the tumor microenvironment of advanced epidermal growth factor receptor-mutant lung adenocarcinoma and the association with prognosis

BACKGROUND

The expression of programmed death-ligand 1 (PD-L1), tumor-infiltrating lymphocytes (TILs), E-cadherin, and vimentin in lung cancer tumor microenvironment is known to impact patient survival or response to therapy. The expression of these biomarkers may also differ between primary lung tumors and brain metastatic tumors. In this study, we investigated the interaction between these biomarkers in lung tumors with or without concomitant brain metastasis and the interaction with paired brain metastatic tumors.

METHODS

The study included 48 patients with stage IV epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma. Sixteen of the forty-eight patients were diagnosed with brain metastasis, while the remaining thirty-two were not. All sixteen patients with brain metastasis had brain tumors. The expression of PD-L1, TILs (CD8⁺ T lymphocytes and FOXP3⁺ regulatory T lymphocytes), E-cadherin, and vimentin were evaluated using immunohistochemical (IHC) staining.

RESULTS

Patients with brain metastasis exhibited a higher frequency of exon 19 deletion and uncommon EGFR mutations, a higher lung tumor vimentin score, worse progression-free survival (PFS), and overall survival (OS) than patients without brain metastasis. IHC staining showed no difference between paired lung and brain tumors. Patients with low PD-L1 expression had better PFS and OS. After multivariate analysis, higher body mass index, the presence of brain metastasis, bone metastasis, and uncommon EGFR mutations were correlated with worse PFS, while the presence of brain metastasis and high lung tumor E-cadherin score was associated with worse OS.

CONCLUSIONS

In patients with stage IV EGFR-mutant lung adenocarcinoma, high E-cadherin expression in the lung tumor might be associated with worse OS. Vimentin expression in the lung tumor was positively related to the risk of brain metastasis.

PD-L1 and PD-L2 immune checkpoint protein induction by type III interferon in non-small cell lung cancer cells

INTRODUCTION

Despite the clinical success of PD-1/PD-1-ligand immunotherapy in non-small cell lung cancer (NSCLC), the appearance of primary and acquired therapy resistance is a major challenge reflecting that the mechanisms regulating the expression of the PD-1-ligands PD-L1 and PD-L2 are not fully explored. Type I and II interferons (IFNs) induce PD-L1 and PD-L2 expression. Here, we examined if PD-L1 and PD-L2 expression also can be induced by type III IFN, IFN-λ, which is peculiarly important for airway epithelial surfaces.

METHODS

In silico mRNA expression analysis of PD-L1 (CD274), PD-L2 (PDCD1LG2), and IFN- λ signaling signature genes in NSCLC tumors and cell lines was performed using RNA sequencing expression data from TCGA, OncoSG, and DepMap portals. IFN-λ-mediated induction of PD-L1 and PD-L2 expression in NSCLC cell lines was examined by real-time quantitative polymerase chain reaction and flow cytometry.

RESULTS

IFNL genes encoding IFN- λ variants are expressed in the majority of NSCLC tumors and cell lines along with the IFNLR1 and IL10R2 genes encoding the IFN-λ receptor subunits. The expression of PD-L1 and PD-L2 mRNA is higher in NSCLC tumors with IFNL mRNA expression compared to tumors without IFNL expression. In the NSCLC cell line HCC827, stimulation with IFN-λ induced both an increase in PD-L1 and PD-L2 mRNA expression and cell surface abundance of the corresponding proteins. In the NSCLC cell line A427, displaying a low basal expression of PD-L1 and PD-L2 mRNA and corresponding proteins, stimulation with IFN-λ resulted in an induction of the former.

CONCLUSION

The type III IFN, IFN- λ, is capable of inducing PD-L1 and PD-L2 expression, at least in some NSCLC cells, and this regulation will need acknowledgment in the development of new diagnostic procedures, such as gene expression signature profiles, to improve PD-1/PD-1-ligand immunotherapy in NSCLC.

Nasopharyngeal Carcinoma Subtype Discovery via Immune Cell Scores from Tumor Microenvironment

BACKGROUND

Nasopharyngeal carcinoma (NPC) is one of the most prevalent cancers with a poor prognosis. Immunotherapy, especially immune checkpoint blockade (ICB), is becoming a potential therapeutic choice for NPC patients. Thus, the identification of patients who could benefit from immunotherapy is clinically significant.

METHODS

The NPC expression profiles from GSE102349 were used to calculate the cell scores of the tumor microenvironment (TME). The consensus clustering method was utilized to identify the potential molecular subtypes among NPC samples. The hub genes were selected from subtype-specific genes by bioinformatics analysis. Machine learning models, including random forest (RF) and support vector machine (SVM) algorithms, were constructed to predict the immune subtype.

RESULTS

In the present study, we identified two TME subtypes among NPC patients. Patients with the S1 subtype have higher levels of immune cells, immune checkpoint genes, and prognosis. Using expression data profiles of NPC patients, we constructed machine learning models for predicting TME subtypes of NPC patients. This model consists of 8 genes (LCK, CD247, FYN, ZAP70, SH2D1A, CD3D, CD3E, and CD3G). Among them, LCK, FYN, SH2D1A, and CD3D were associated with better prognoses. Among the two constructed models, SVM exhibited a higher area under curve (AUC) of 0.977, when compared with RF (AUC = 0.966). The web server based on the constructed machine learning models will contribute to the identification of NPC patients likely to benefit from ICB therapies.

CONCLUSIONS

This study identified NPC subtypes and provided an accurate model to select individuals who are most likely to respond to ICB.

Heterogeneity of tumour mutational burden in metastatic NSCLC demonstrated by endobronchial ultrasound sampling

Introduction

Tumour mutational burden (TMB) is an important emerging biomarker for immune checkpoint inhibitors (ICI). The stability of TMB values across distinct EBUS tumour regions is not well defined in advanced lung cancer patients.

Methods

This study included a whole-genome sequencing cohort (n=11, LxG cohort) and a targeted Oncomine TML panel cohort (n=10, SxD cohort), where paired primary and metastatic samples were obtained by endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA).

Results

The LxG cohort displayed a strong correlation between the paired primary and metastatic sites, with a median TMB score of 7.70 ± 5.39 and 8.31 ± 5.88 respectively. Evaluation of the SxD cohort demonstrated greater inter-tumoural TMB heterogeneity, where Spearman correlation between the primary and metastatic sites fell short of significance. Whilst median TMB scores were not significantly different between the two sites, 3 out of 10 paired samples were discordant when using a TMB cut-off of 10 mutations per Mb. In addition, PD-L1 copy number and KRAS mutations were assessed, demonstrating the feasibility of performing multiple molecular tests relevant to ICI treatment using a single EBUS sample. We also observed good consistency in PD-L1 copy number and KRAS mutation, where cut-off estimates were consistent across the primary and metastatic sites.

Conclusions

Assessment of TMB acquired by EBUS from multiple sites is highly feasible and has the potential to improve accuracy of TMB panels as a companion diagnostic test. We demonstrate similar TMB values across primary and metastatic sites, however 3 out of 10 samples displayed inter-tumoural heterogeneity that would alter clinical management.

Influence of location-dependent sex difference on PD-L1, MMR/MSI, and EGFR in colorectal carcinogenesis

BACKGROUND

The incidence and mortality rates of colorectal cancer (CRC) has been reported to be strongly associated to sex/gender difference. CRC shows sexual dimorphism, and sex hormones have been shown to affect the tumor immune microenvironment. This study aimed to investigate location-dependent sex differences in tumorigenic molecular characteristics in patients with colorectal tumors, including adenoma and CRC.

METHODS

A total of 231 participants, including 138 patients with CRC, 55 patients with colorectal adenoma, and 38 healthy controls, were recruited between 2015 and 2021 at Seoul National University Bundang Hospital. All patients underwent colonoscopy and acquired tumor lesion samples were further analyzed for programmed death-ligand 1 (PD-L1), epidermal growth factor receptor (EGFR) expression, deficient mismatch repair (dMMR), and microsatellite instability (MSI) status. This study was registered with ClinicalTrial.gov, number NCT05638542.

RESULTS

The average of combined positive score (CPS) was higher in serrated lesions and polyps (lesions/polyps) compared to conventional adenomas (5.73 and 1.41, respectively, P < 0.001). No significant correlation was found between sex and PD-L1 expression within the groups, regardless of histopathological diagnosis. In multivariate analysis where each sex was further stratified by tumor location due to their interaction in CRC, PD-L1 expression was inversely correlated with males having proximal CRC with a CPS cutoff of 1 (Odds ratio (OR) 0.28, P = 0.034). Females with proximal CRC showed a significant association with dMMR/MSI-high (OR 14.93, P = 0.032) and high EGFR expression (OR 4.17, P = 0.017).

CONCLUSION

Sex and tumor location influenced molecular features such as PD-L1, MMR/MSI status and EGFR expression in CRC, suggesting a possible underlying mechanism of sex-specific colorectal carcinogenesis.

Immunotherapy for Metastatic Non-Small Cell Lung Cancer: Therapeutic Advances and Biomarkers

Immunotherapy has revolutionized the treatment paradigm of non-small cell lung cancer and improved patients' prognosis. Immune checkpoint inhibitors have quickly become standard frontline treatment for metastatic non-oncogene addicted disease, either as a single agent or in combination strategies. However, only a few patients have long-term benefits, and most of them do not respond or develop progressive disease during treatment. Thus, the identification of reliable predictive and prognostic biomarkers remains crucial for patient selection and guiding therapeutic choices. In this review, we provide an overview of the current strategies, highlighting the main clinical challenges and novel potential biomarkers.

Immune-based combination therapy to convert immunologically cold tumors into hot tumors: an update and new insights

As a breakthrough strategy for cancer treatment, immunotherapy mainly consists of immune checkpoint inhibitors (ICIs) and other immunomodulatory drugs that provide a durable protective antitumor response by stimulating the immune system to fight cancer. However, due to the low response rate and unique toxicity profiles of immunotherapy, the strategies of combining immunotherapy with other therapies have attracted enormous attention. These combinations are designed to exert potent antitumor effects by regulating different processes in the cancer-immunity cycle. To date, immune-based combination therapy has achieved encouraging results in numerous clinical trials and has received Food and Drug Administration (FDA) approval for certain cancers with more studies underway. This review summarizes the emerging strategies of immune-based combination therapy, including combinations with another immunotherapeutic strategy, radiotherapy, chemotherapy, anti-angiogenic therapy, targeted therapy, bacterial therapy, and stroma-targeted therapy. Here, we highlight the rationale of immune-based combination therapy, the biomarkers and the clinical progress for these immune-based combination therapies.

Design, Synthesis, and Biological Evaluation of a Small-Molecule PET Agent for Imaging PD-L1 Expression

Immunotherapy blocking programmed cell death protein 1/programmed death ligand 1 (PD-1/PD-L1) pathway has achieved great therapeutic effect in the clinic, but the overall response rate is not satisfactory. Early studies showed that response to treatment and overall survival could be positively related to PD-L1 expression in tumors. Therefore, accurate measurement of PD-L1 expression will help to screen cancer patients and improve the overall response rate. A small molecular positron emission tomography (PET) probe [18F]LP-F containing a biphenyl moiety was designed and synthesized for measurement of PD-L1 expression in tumors. The PET probe [18F]LP-F was obtained with a radiochemical yield of 12.72 ± 1.98%, a radiochemical purity of above 98% and molar activity of 18.8 GBq/μmol. [18F]LP-F had good stability in phosphate buffer saline (PBS) and mouse serum. In vitro assay indicated that [18F]LP-F showed moderate affinity to PD-L1. Micro-PET results showed that the tumor accumulation of [18F]LP-F in A375 tumor was inferior to that in A375-hPD-L1 tumor. All the results demonstrated that [18F]LP-F could specifically bind to PD-L1 and had a potential application in non-invasive evaluation of PD-L1 expression in tumors.

Comparison of 22C3-PD-L1 Expression Between Paired Tumor Paraffin Blocks of Surgical Resection Specimens of Nonsmall Cell Lung Cancer

In this study, our aim was to evaluate the discordance of programmed cell death ligand 1 (PD-L1) expression between 2 paired paraffin blocks from surgical nonsmall cell lung cancer (NSCLC) specimens, thus providing recommendations for choosing paraffin blocks for PD-L1 immunohistochemistry detection. A total of 460 paired paraffin blocks of surgical NSCLC specimens were analyzed using the 22C3-PD-L1 assay. PD-L1 expression between 2 paired paraffin blocks was calculated using 3 classification schemes, tumor proportion score (TPS)-based 3-level classification and TPS-based binary classification using TPS ≥1% or TPS ≥50% as the cutoff. Clinicopathological characteristics were analyzed for cases with discordant PD-L1 expression. PD-L1 expression in 2 paired paraffin blocks of surgical NSCLC specimens was highly correlated from a single tumor ( R2 =0.89) in the overall trend. The overall discordance rates were 10.9%, 7.4%, and 3.5% respectively when using TPS-based 3-level classification or binary classification. No statistical differences were observed in PD-L1 expression discordance rates when patients were stratified by age, sex, smoking status, histologic types, TNM stage, or years of paraffin blocks ( P >0.05). The presence of a solid histologic pattern was associated with a higher PD-L1 expression discordance rate in adenocarcinomas ( P <0.05). Twenty-five cases with discordant PD-L1 expression were divided into 2 categories: spatial heterogeneity without recognizable morphology difference (76%) and spatial heterogeneity with significantly different morphology (24%). The discordance rate in TPS scores was much higher in cases with different morphology than those without different morphology. One representative paraffin block containing adequate neoplastic tissue may be adequate to determine PD-L1 expression in most of the surgical specimens of NSCLC. In cases that harbored different morphology in different paraffin blocks, the dual-block immunohistochemistry assessment method is recommended due to the intratumoral heterogeneity.

ANK2 as a novel predictive biomarker for immune checkpoint inhibitors and its correlation with antitumor immunity in lung adenocarcinoma

BACKGROUND

Immune checkpoint inhibitors (ICIs) have been shown to significantly improve the survival of patients with advanced lung adenocarcinoma (LUAD). However, only limited proportion of patients could benefit from ICIs. Novel biomarkers with strong predictability are needed for clinicians to maximize the efficacy of ICIs. Our study aimed to identify potential biomarkers predicting ICIs efficacy in LUAD.

METHODS

The Cancer Genome Atlas (TCGA) PanCancer Atlas studies in cBioportal were used to evaluate the mutation frequency of ANK2 across multiple cancers. Clinical and mutational data for LUAD from ICIs-treated cohorts (Hellmann et al. and Rizvi et al.) were collected to explore the correlation between ANK2 mutation and clinical outcomes. In addition, the relationship between ANK2 expression and clinical outcomes was analyzed using LUAD data from TCGA and Gene Expression Omnibus. Furthermore, the impact of ANK2 mutation and expression on the tumor immune microenvironment of LUAD was analyzed using TCGA and TISIDB databases.

RESULTS

Patients with ANK2 mutation benefited more from ICIs. In ICIs-treated cohort, prolonged progression-free survival (PFS) (median PFS: NR (not reached) vs. 5.42 months, HR (hazard ratio) 0.31, 95% CI 0.18-0.54; P = 0.0037), improved complete response rate (17.65% vs. 1.85%, P = 0.0402), and improved objective response rate (64.71% vs. 24.07%, P = 0.0033) were observed in LUAD patients with ANK2 mutation compared to their wild-type counterparts. Regarding ANK2 expression, it was observed that ANK2 expression was decreased in LUAD (P < 0.05) and a higher level of ANK2 expression was associated with longer overall survival (HR 0.69, 95% CI 0.52-0.92; P = 0.012) in TCGA LUAD cohort. Moreover, ANK2 mutation or higher ANK2 expression correlated with enhanced antitumor immunity and "hot" tumor microenvironment in LUAD, which could be potential mechanisms that ANK2 mutation facilitated ICIs therapy and patients with higher ANK2 expression survived longer.

CONCLUSION

Our findings suggest that ANK2 mutation or increased ANK2 expression may serve as a favorable biomarker for the efficacy of ICIs in patients with LUAD.

Treatment of induced oligometastatic disease after partial response to immunochemotherapy in patient with stage IV non-small cell lung cancer and severe toxicity

Treatment of induced oligometastatic disease after partial response to systemic antineoplastic therapy in non-small cell lung cancer (NSCLC) remains controversial. The introduction of immune checkpoint inhibitors (ICIs) has revolutionised the treatment of stage IV NSCLC. While ICI combined with chemotherapy (ChT) leads to longer duration of response and higher response rates compared with ChT alone, it can also cause serious adverse events (AEs) resulting in treatment discontinuation. In case of treatment discontinuation due to AEs after partial response to systemic treatment, surgical treatment of residual disease can be considered as it could lead to complete response. We present a case of a patient with stage IV NSCLC who is currently alive without any signs of cancer after partial response to ICI/ChT followed by surgical removal of residual disease.

Evaluation of PD-L1 expression in a large set of gastroenteropancreatic neuroendocrine tumours and correlation with clinicopathological data

BACKGROUND

Targeting programmed death protein 1 (PD-1) or its ligand PD-L1 is a promising therapeutic approach for many types of cancer in which PD-L1 is overexpressed. However, data on PD-L1 expression levels in gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are limited and contradictory.

METHODS

We evaluated PD-L1 expression in 457 archived, formalin-fixed, paraffin-embedded GEP-NEN samples from 175 patients by immunohistochemistry using the highly sensitive monoclonal anti-PD-L1 antibody 73-10. The immunostaining was semiquantitatively evaluated using a 12-point immunoreactivity score (IRS) taking both PD-L1-positive tumour cells and immune cells into account. Tumour samples with an IRS ≥ 3 were considered PD-L1-positive. Results were correlated with clinicopathological data and with the expression of several typical markers and receptors for neuroendocrine tumours.

RESULTS

Of the GEP-NEN samples, 73% were PD-L1-positive. The median IRS value across all samples was 4.0, corresponding to low expression. PD-L1 immunostaining was predominantly localised at the plasma membrane of the tumour cells. Positive correlations were observed between PD-L1 expression and tumour grading or Ki-67 index, between PD-L1 expression and the expression of chromogranin A, and between PD-L1 expression and the expression of each of the five somatostatin receptors. PD-L1 expression was lower in tumours with lymph node metastases at diagnosis than in those without regional metastasis and lower in high-stage than in earlier-stage tumours. No association was noted between PD-L1 expression and patient survival.

CONCLUSIONS

PD-L1 expression is common in GEP-NENs and increases with malignancy. Therefore, especially in high-grade GEP-NENs, targeting the PD-1/PD-L1 axis could be a promising additional therapeutic strategy.

Immunotherapy targeting inhibitory checkpoints: The role of NK and other innate lymphoid cells

Monoclonal antibodies that target specific ligand-receptor signaling pathways and act as immune checkpoint inhibitors have been designed to remove the brakes in T cells and restore strong and long-term antitumor-immunity. Of note, many of these inhibitory receptors are also expressed by Innate Lymphoid Cells (ILCs), suggesting that also blockade of inhibitory pathways in innate lymphocytes has a role in the response to the treatment with checkpoint inhibitors. ILCs comprise cytotoxic NK cells and "helper" subsets and are important cellular components in the tumor microenvironment. In addition to killing tumor cells, ILCs release inflammatory cytokines, thus contributing to shape adaptive cell activation in the context of immunotherapy. Therefore, ILCs play both a direct and indirect role in the response to checkpoint blockade. Understanding the impact of ILC-mediated response on the treatment outcome would contribute to enhance immunotherapy efficacy, as still numerous patients resist or relapse.

The Role of Pathology-Based Methods in Qualitative and Quantitative Approaches to Cancer Immunotherapy

Simple Summary

Immunotherapy has become the filar of modern oncological treatment, and programmed death-ligand 1 expression is one of the primary immune markers assessed by pathologists. However, there are still some issues concerning the evaluation of the marker and limited information about the interaction between the tumour and associated immune cells. Recent studies have focused on cancer immunology to try to understand the complex tumour microenvironment, and multiplex imaging methods are more widely used for this purpose. The presented article aims to provide an overall review of a different multiplex in situ method using spectral imaging, supported by automated image-acquisition and software-assisted marker visualisation and interpretation. Multiplex imaging methods could improve the current understanding of complex tumour-microenvironment immunology and could probably help to better match patients to appropriate treatment regimens.

Abstract

Immune checkpoint inhibitors, including those concerning programmed cell death 1 (PD-1) and its ligand (PD-L1), have revolutionised the cancer therapy approach in the past decade. However, not all patients benefit from immunotherapy equally. The prediction of patient response to this type of therapy is mainly based on conventional immunohistochemistry, which is limited by intraobserver variability, semiquantitative assessment, or single-marker-per-slide evaluation. Multiplex imaging techniques and digital image analysis are powerful tools that could overcome some issues concerning tumour-microenvironment studies. This novel approach to biomarker assessment offers a better understanding of the complicated interactions between tumour cells and their environment. Multiplex labelling enables the detection of multiple markers simultaneously and the exploration of their spatial organisation. Evaluating a variety of immune cell phenotypes and differentiating their subpopulations is possible while preserving tissue histology in most cases. Multiplexing supported by digital pathology could allow pathologists to visualise and understand every cell in a single tissue slide and provide meaning in a complex tumour-microenvironment contexture. This review aims to provide an overview of the different multiplex imaging methods and their application in PD-L1 biomarker assessment. Moreover, we discuss digital imaging techniques, with a focus on slide scanners and software.

From rough to precise: PD-L1 evaluation for predicting the efficacy of PD-1/PD-L1 blockades

Developing biomarkers for accurately predicting the efficacy of immune checkpoint inhibitor (ICI) therapies is conducive to avoiding unwanted side effects and economic burden. At the moment, the quantification of programmed cell death ligand 1 (PD-L1) in tumor tissues is clinically used as one of the combined diagnostic assays of response to anti-PD-1/PD-L1 therapy. However, the current assays for evaluating PD-L1 remain imperfect. Recent studies are promoting the methodologies of PD-L1 evaluation from rough to precise. Standardization of PD-L1 immunohistochemistry tests is being promoted by using optimized reagents, platforms, and cutoff values. Combining novel in vivo probes with PET or SPECT will probably be of benefit to map the spatio-temporal heterogeneity of PD-L1 expression. The dynamic change of PD-L1 in the circulatory system can also be realized by liquid biopsy. Consider PD-L1 expressed on non-tumor (immune and non-immune) cells, and optimized combination detection indexes are further improving the accuracy of PD-L1 in predicting the efficacy of ICIs. The combinations of artificial intelligence with novel technologies are conducive to the intelligence of PD-L1 as a predictive biomarker. In this review, we will provide an overview of the recent progress in this rapidly growing area and discuss the clinical and technical challenges.

18F FDG PET/CT and Novel Molecular Imaging for Directing Immunotherapy in Cancer

Immunotherapy has transformed the treatment landscape of many cancers, with durable responses in disease previously associated with a poor prognosis. Patient selection remains a challenge, with predictive biomarkers an urgent unmet clinical need. Current predictive biomarkers, including programmed death-ligand 1 (PD-L1) (measured with immunohistochemistry), are imperfect. Promising biomarkers, including tumor mutation burden and tumor infiltrating lymphocyte density, fail to consistently predict response and have yet to translate to routine clinical practice. Heterogeneity of immune response within and between lesions presents a further challenge where fluorine 18 fluorodeoxyglucose PET/CT has a potential role in assessing response, stratifying treatment, and detecting and monitoring immune-related toxicities. Novel radiopharmaceuticals also present a unique opportunity to define the immune tumor microenvironment to better predict which patients may respond to therapy, for example by means of in vivo whole-body PD-L1 and CD8+ T cell expression imaging. In addition, longitudinal molecular imaging may help further define dynamic changes, particularly in cases of immunotherapy resistance, helping to direct a more personalized therapeutic approach. This review highlights current and emerging applications of molecular imaging to stratify, predict, and monitor molecular dynamics and treatment response in areas of clinical need.

Association of High Tumor Mutation Burden in Non-Small Cell Lung Cancers With Increased Immune Infiltration and Improved Clinical Outcomes of PD-L1 Blockade Across PD-L1 Expression Levels

Importance

Although tumor mutation burden (TMB) has been explored as a potential biomarker of immunotherapy efficacy in solid tumors, there still is a lack of consensus about the optimal TMB threshold that best discriminates improved outcomes of immune checkpoint inhibitor therapy among patients with non-small cell lung cancer (NSCLC).

Objectives

To determine the association between increasing TMB levels and immunotherapy efficacy across clinically relevant programmed death ligand-1 (PD-L1) levels in patients with NSCLC.

Design, Setting, and Participants

This multicenter cohort study included patients with advanced NSCLC treated with immunotherapy who received programmed cell death-1 (PD-1) or PD-L1 inhibition in the Dana-Farber Cancer Institute (DFCI), Memorial Sloan Kettering Cancer Center (MSKCC), and in the Stand Up To Cancer (SU2C)/Mark Foundation data sets. Clinicopathological and genomic data were collected from patients between September 2013 and September 2020. Data analysis was performed from November 2021 to February 2022.

Exposures

Treatment with PD-1/PD-L1 inhibition without chemotherapy.

Main Outcomes and Measures

Association of TMB levels with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS).

Results

In the entire cohort of 1552 patients with advanced NSCLC who received PD-1/PD-L1 blockade, the median (range) age was 66 (22-92) years, 830 (53.5%) were women, and 1347 (86.8%) had cancer with nonsquamous histologic profile. A regression tree modeling ORR as a function of TMB identified 2 TMB groupings in the discovery cohort (MSKCC), defined as low TMB (≤19.0 mutations per megabase) and high TMB (>19.0 mutations per megabase), which were associated with increasing improvements in ORR, PFS, and OS in the discovery cohort and in 2 independent cohorts (DFCI and SU2C/Mark Foundation). These TMB levels also were associated with significant improvements in outcomes of immunotherapy in each PD-L1 tumor proportion score subgroup of less than 1%, 1% to 49%, and 50% or higher. The ORR to PD-1/PD-L1 inhibition was as high as 57% in patients with high TMB and PD-L1 expression 50% or higher and as low as 8.7% in patients with low TMB and PD-L1 expression less than 1%. Multiplexed immunofluorescence and transcriptomic profiling revealed that high TMB levels were associated with increased CD8-positive, PD-L1-positive T-cell infiltration, increased PD-L1 expression on tumor and immune cells, and upregulation of innate and adaptive immune response signatures.

Conclusions and Relevance

These findings suggest that increasing TMB levels are associated with immune cell infiltration and an inflammatory T-cell-mediated response, resulting in increased sensitivity to PD-1/PD-L1 blockade in NSCLC across PD-L1 expression subgroups.

Reshaping the systemic tumor immune environment (STIE) and tumor immune microenvironment (TIME) to enhance immunotherapy efficacy in solid tumors

The development of combination immunotherapy based on the mediation of regulatory mechanisms of the tumor immune microenvironment (TIME) is promising. However, a deep understanding of tumor immunology must involve the systemic tumor immune environment (STIE) which was merely illustrated previously. Here, we aim to review recent advances in single-cell transcriptomics and spatial transcriptomics for the studies of STIE, TIME, and their interactions, which may reveal heterogeneity in immunotherapy responses as well as the dynamic changes essential for the treatment effect. We review the evidence from preclinical and clinical studies related to TIME, STIE, and their significance on overall survival, through different immunomodulatory pathways, such as metabolic and neuro-immunological pathways. We also evaluate the significance of the STIE, TIME, and their interactions as well as changes after local radiotherapy and systemic immunotherapy or combined immunotherapy. We focus our review on the evidence of lung cancer, hepatocellular carcinoma, and nasopharyngeal carcinoma, aiming to reshape STIE and TIME to enhance immunotherapy efficacy.

Correlation of PD-L1 expression on tumour cells between diagnostic biopsies and surgical specimens of lung cancer in real life with respect to biopsy techniques and neoadjuvant treatment

PURPOSES

Programmed death-ligand 1 (PD-L1) testing is performed mainly on biopsy specimens in patients with advanced lung cancer. It is questionable whether the small amount of tissue analysed in biopsies may represent the true PD-L1 expression of a tumour.

METHODS

In this retrospective study, PD-L1 expression on tumour cells derived from bronchoscopy brush cytology, endobronchial ultrasound guided transbronchial needle aspiration (EBUS-TBNA), endobronchial biopsy, transbronchial biopsy (TBB) and computed tomography (CT)-guided transthoracic biopsy was compared to the PD-L1 expression of the corresponding surgical resection in lung cancer patients with regard to neoadjuvant treatment in-between.

RESULTS

A quantitative comparison between the diagnostic biopsy of the primary tumour with corresponding resected surgical specimens in a total of 113 lung cancer patients (60% male, mean age 65 ± 9 years) revealed a statistically significant correlation of PD-L1 expression on tumour cells (r = 0.58, p< 0.001), for patients without neoadjuvant treatment in-between and for patients who underwent neoadjuvant treatment (both p < 0.001). Using a cut-off value of ≥ 50% PD-L1 TPS for comparing the biopsy samples and resected specimens, the concordance rate was 78% with a Cohen's Kappa of 0.45.

CONCLUSION

A statistically significant concordance for PD-L1 expression on tumour cells between biopsies from primary lung tumour and resected specimen was found, but of uncertain clinical accuracy. The use of a cut-off value of ≥ 50% PD-L1 TPS resulted only in a moderate agreement. Therefore, the interpretation of the PD-L1 determined form biopsy specimens status should only be considered with caution for treatment decisionsQuery.

Current and Future Biomarkers for Immune Checkpoint Inhibitors in Head and Neck Squamous Cell Carcinoma

With the introduction of immunotherapy, significant improvement has been made in the treatment of head and neck squamous cell carcinoma (HNSCC). However, only a small subset of patients with HNSCC benefit from immunotherapy. The current biomarker, a programmed cell death protein ligand 1 (PD-L1) expression that is widely used in treatment decision making for advanced HNSCC, has only a moderate predictive value. Additionally, PD-L1-based assay has critical inherent limitations due to its highly dynamic nature and lack of standardization. With the advance in molecular techniques and our understanding of biology, more reliable, reproducible, and practical novel biomarkers are being developed. These include but are not limited to neoantigen/mutation characteristics, immune transcriptomes, tumor-infiltrating immune cell composition, cancer epigenomic, proteomics and metabolic characteristics, and plasma-based and organoid assays.

The current state of molecular profiling in gastrointestinal malignancies

This is a review of the current state of molecular profiling in gastrointestinal (GI) cancers and what to expect from this evolving field in the future. Individualized medicine is moving from broad panel testing of numerous genes or gene products in tumor biopsy samples, identifying biomarkers of prognosis and treatment response, to relatively noninvasive liquid biopsy assays, building on what we have learned in our tumor analysis and growing into its own evolving predictive and prognostic subspecialty. Hence, the field of GI precision oncology is exploding, and this review endeavors to summarize where we are now in preparation for the journey ahead.

Multi-Omics Approaches for the Prediction of Clinical Endpoints after Immunotherapy in Non-Small Cell Lung Cancer: A Comprehensive Review

Immune checkpoint inhibitors (ICI) have revolutionized the management of locally advanced and advanced non-small lung cancer (NSCLC). With an improvement in the overall survival (OS) as both first- and second-line treatments, ICIs, and especially programmed-death 1 (PD-1) and programmed-death ligands 1 (PD-L1), changed the landscape of thoracic oncology. The PD-L1 level of expression is commonly accepted as the most used biomarker, with both prognostic and predictive values. However, even in a low expression level of PD-L1, response rates remain significant while a significant number of patients will experience hyperprogression or adverse events. The dentification of such subtypes is thus of paramount importance. While several studies focused mainly on the prediction of the PD-L1 expression status, others aimed directly at the development of prediction/prognostic models. The response to ICIs depends on a complex physiopathological cascade, intricating multiple mechanisms from the molecular to the macroscopic level. With the high-throughput extraction of features, omics approaches aim for the most comprehensive assessment of each patient. In this article, we will review the place of the different biomarkers (clinical, biological, genomics, transcriptomics, proteomics and radiomics), their clinical implementation and discuss the most recent trends projecting on the future steps in prediction modeling in NSCLC patients treated with ICI.

Identification of sSIGLEC5 and sLAG3 as New Relapse Predictors in Lung Cancer

Lung cancer (LC) continues to be the leading cause of cancer-related deaths in both men and women worldwide. After complete tumour resection, around half of the patients suffer from disease relapse, emphasising the critical need for robust relapse predictors in this disease. In search of such biomarkers, 83 patients with non-microcytic lung cancer and 67 healthy volunteers were studied. Pre-operative levels of sSIGLEC5 along with other soluble immune-checkpoints were measured and correlated with their clinical outcome. Soluble SIGLEC5 (sSIGLEC5) levels were higher in plasma from patients with LC compared with healthy volunteers. Looking into those patients who suffered relapse, sSIGLEC5 and sLAG3 were found to be strong relapse predictors. Following a binary logistic regression model, a sSIGLEC5 + sLAG3 score was established for disease relapse prediction (area under the curve 0.8803, 95% confidence intervals 0.7955−0.9652, cut-off > 2.782) in these patients. Based on score cut-off, a Kaplan−Meier analysis showed that patients with high sSIGLEC5 + sLAG3 score had significantly shorter relapse-free survival (p ≤ 0.0001) than those with low sSIGLEC5 + sLAG3 score.Our study suggests that pre-operative sSIGLEC5 + sLAG3 score is a robust relapse predictor in LC patients.

Correlation of PD-L1 Expression with Clinicopathological and Genomic Features in Chinese Non-Small-Cell Lung Cancer

Programmed cell death 1 ligand 1 (PD-L1) has been approved as predictive biomarker for non-small-cell lung cancer (NSCLC) patients treated with PD-(L)1 blockade therapy. The clinical/genomic features associated with PD-L1 are not well studied. Genomic profiling of tumor biopsies from 883 Chinese NSCLC patients was performed by targeted next-generation sequencing. Immunohistochemical analysis was conducted to evaluate PD-L1 expression levels using antibodies Dako 22C3 and 28-8, respectively. Our study showed distinct correlation between PD-L1 expression and clinical/genomic characteristics when using different PD-L1 antibodies and in different histological subtypes including adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively. PD-L1 high expression (22C3) was associated with male and lymph node metastasis only in ADC patients. Furthermore, mutations of TP53 and KRAS, KIF5B-RET fusion, copy number gains of PD-L1 and PD-L2, and arm-level amplifications of chr.12p were significantly associated with PD-L1 positive status in ADC patients. For SCC patients, the gain of EGFR and MDM2 and loss of PTPRD were negatively associated with PD-L1 expression. We also compared our results with other studies and found conflicting results presumably because of the multiplicity of antibody clones and platforms, the difference of cutoffs for assigning PD-L1 expression levels, and the variation in study populations. Our study can help to understand the utility and validity of PD-L1 as biomarker of response to immune checkpoint inhibitors.

Automated Detection of Portal Fields and Central Veins in Whole-Slide Images of Liver Tissue

Many physiological processes and pathological phenomena in the liver tissue are spatially heterogeneous. At a local scale, biomarkers can be quantified along the axis of the blood flow, from portal fields (PFs) to central veins (CVs), i.e., in zonated form. This requires detecting PFs and CVs. However, manually annotating these structures in multiple whole-slide images is a tedious task. We describe and evaluate a fully automated method, based on a convolutional neural network, for simultaneously detecting PFs and CVs in a single stained section. Trained on scans of hematoxylin and eosin-stained liver tissue, the detector performed well with an F1 score of 0.81 compared to annotation by a human expert. It does, however, not generalize well to previously unseen scans of steatotic liver tissue with an F1 score of 0.59. Automated PF and CV detection eliminates the bottleneck of manual annotation for subsequent automated analyses, as illustrated by two proof-of-concept applications: We computed lobulus sizes based on the detected PF and CV positions, where results agreed with published lobulus sizes. Moreover, we demonstrate the feasibility of zonated quantification of biomarkers detected in different stainings based on lobuli and zones obtained from the detected PF and CV positions. A negative control (hematoxylin and eosin) showed the expected homogeneity, a positive control (glutamine synthetase) was quantified to be strictly pericentral, and a plausible zonation for a heterogeneous F4/80 staining was obtained. Automated detection of PFs and CVs is one building block for automatically quantifying physiologically relevant heterogeneity of liver tissue biomarkers. Perspectively, a more robust and automated assessment of zonation from whole-slide images will be valuable for parameterizing spatially resolved models of liver metabolism and to provide diagnostic information.

Among Multiple Needle Core Biopsy Samples, the One with the Highest Tumor Proportion Score Best Represents the PD-L1 Status of the Whole Surgical Specimen in Non-Small Cell Lung Cancer

The heterogeneity of programmed death-ligand 1 (PD-L1) status between core needle biopsies (CNBs) from one tumor has not been well studied before. The current study attempts to find out the best index using multiple core biopsies from one tumor which can better reflect the actual PD-L1 status. Random CNB was performed in surgical specimens from 170 consecutive non-small cell lung cancer samples. Fifty-one cases (41 cases with PD-L1 positive and 10 cases with PD-L1 negative) and 216 matched CNBs were analyzed by DAKO 22C3 PharmDx Link 48 Autostainer. The PD-L1 status was compared between the surgical specimens and matched CNBs. Heterogeneity of PD-L1 status between CNBs from one tumor was observed in 56% of PD-L1 positive cases. Different tumor proportion score (TPS) statistical forms with regard to the highest, mean, median, weighted average TPS, as well as TPS showed by the longest biopsy specimen and the biopsy with most tumor volume were compared. At a cut-off of 1%, the concordance rates were 94.1%, 88.2%, 90.2%, 86.3%, 86.3%, and 86.3%; At a cut-off of 50%, the concordance rates were 92.2%, 86.3%, 84.3%, 82.4%, 82.4%, and 86.3%, respectively. The CNB with the highest TPS can best represent PD-L1 status estimated by whole surgical specimen. The highest TPS among the multiple biopsies is a robust evaluation of the PD-L1 status, but not mean TPS, at the 1% and 50% cut-offs.

Actionable Molecular Alterations Are Revealed in Majority of Advanced Non-Small Cell Lung Cancer Patients by Genomic Tumor Profiling at Progression after First Line Treatment

Background: Genomic profiling in advanced Non-Small Cell Lung cancer (NSCLC) can reveal Actionable Molecular Alterations (AMAs). Our study aims to investigate clinical relevance of re-biopsy after first line treatment, by reporting on acquired and persistent AMAs and potential targeted treatments in a real-time cohort of NSCLC patients. Methods: Patients with advanced NSCLC receiving first-line treatment were prospectively included in an observational study (NCT03512847). Genomic profiling was performed by TruSight Oncology 500 HT gene panel on tumor tissue collected at diagnosis and at time of progression. Results: The 92 patients re-biopsied at progression had received immunotherapy (n = 44), chemotherapy (n = 44), or combination treatment (n = 4). In 87 of these patients (95%), successful genomic profiling was performed at both the diagnostic biopsy and the re-biopsy. In 74 patients (85%), ≥1 AMA were found. The AMAs were acquired in 28%. The most frequent AMAs were observed in TP53 (45%), KRAS (24%), PIK3CA (6%), and FGFR1 (6%). Only five patients (5%) received targeted treatment mainly due to deterioration in performance status. Conclusions: Re-biopsy at progression revealed acquired AMAs in approximately one third of patients, and 85% had at least one AMA with the potential of receiving targeted treatment, thus strengthening the clinical relevance of re-biopsy.

Comprehensive Statistical Exploration of Prognostic (Bio-)Markers for Responses to Immune Checkpoint Inhibitor in Patients with Non-Small Cell Lung Cancer

Simple Summary

Metastatic non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs) may suffer from heavy side effects, and not all patients benefit from the treatment. Therefore, it is crucial to gain knowledge about possible (bio-)markers for response to ICIs. We used retrospective data acquired from NSCLC patients treated with ICIs in first- or further-line therapy settings, including 16 possible markers. We conducted a comprehensive statistical analysis study to find markers for response to treatment, assessed the robustness of our results, and discussed often encountered statistical pitfalls. Our study yielded hypotheses for various predictive and prognostic (bio-)markers for response to ICIs in NSCLC patients. In particular, we found that high basophil counts may be predictive for treatment response in patients in further-line therapy settings.

Abstract

Metastatic non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs) may suffer from heavy side effects and not all patients benefit from the treatment. We conducted a comprehensive statistical analysis to identify promising (bio-)markers for treatment response. We analyzed retrospective data from NSCLC patients treated with ICIs in first- or further-line therapy settings at the University Hospital Zurich. We investigated 16 possible prognostic markers with respect to overall survival, tumor size reduction, and the development of an immune-related adverse event (irAE) and assessed the robustness of our results. For the further-line patient group, the most significant result was that increased basophil counts were associated with increased odds of tumor size reduction within three months and with the development of an irAE. For the first-line patient group, the most significant results were that increased lymphocyte counts, the histology of adenocarcinoma, and the intake of non-steroidal anti-rheumatic drugs (NSAR) were associated with decreased hazards of dying. Our study yielded new hypotheses for predictive (bio-)markers for response to ICIs in NSCLC patients. The possibly beneficial role of high basophil counts is a particularly interesting finding. Our results should be tested on independent data in a prospective fashion.

QuPath Digital Immunohistochemical Analysis of Placental Tissue

Background:

QuPath is an open-source digital image analyzer notable for its user-friendly design, cross-platform compatibility, and customizable functionality. Since it was first released in 2016, at least 624 publications have reported its use, and it has been applied in a wide spectrum of settings. However, there are currently limited reports of its use in placental tissue. Here, we present the use of QuPath to quantify staining of G-protein coupled receptor 18 (GPR18), the receptor for the pro-resolving lipid mediator Resolvin D2, in placental tissue.

Methods:

Whole slide images of vascular smooth muscle (VSM) and extravillous trophoblast (EVT) cells stained for GPR18 were annotated for areas of interest. Visual scoring was performed on these images by trained and in-training pathologists, while QuPath scoring was performed with the methodology described herein.

Results:

Bland–Altman analyses showed that, for the VSM category, the two methods were comparable across all staining levels. For EVT cells, the high-intensity staining level was comparable across methods, but the medium and low staining levels were not comparable.

Conclusions:

Digital image analysis programs offer great potential to revolutionize pathology practice and research by increasing accuracy and decreasing the time and cost of analysis. Careful study is needed to optimize this methodology further.