Analytical Concordance of PD-L1 Assays Utilizing Antibodies From FDA-Approved Diagnostics in Advanced Cancers: A Systematic Literature Review

Microsatellite Instability, Mismatch Repair, and Tumor Mutation Burden in Lung Cancer

Since US Food and Drug Administration approval of programmed death ligand 1 (PD-L1) as the first companion diagnostic for immune checkpoint inhibitors (ICIs) in non-small cell lung cancer, many patients have experienced increased overall survival. To improve selection of ICI responders versus nonresponders, microsatellite instability/mismatch repair deficiency (MSI/MMR) and tumor mutation burden (TMB) came into play. Clinical data show PD-L1, MSI/MMR, and TMB are independent predictive immunotherapy biomarkers. Harmonization of testing methodologies, optimization of assay design, and results analysis are ongoing. Future algorithms to determine immunotherapy eligibility might involve complementary use of current and novel biomarkers. Artificial intelligence could facilitate algorithm implementation to convert complex genetic data into recommendations for specific ICIs.

DRG2 is required for surface localization of PD-L1 and the efficacy of anti-PD-1 therapy

More than half of tumor patients with high PD-L1 expression do not respond to anti-PD-1/PD-L1 therapy, and the underlying mechanisms are yet to be clarified. Here we show that developmentally regulated GTP-binding protein 2 (DRG2) is required for response of PD-L1-expressing tumors to anti-PD-1 therapy. DRG2 depletion enhanced IFN-γ signaling and increased the PD-L1 level in melanoma cells. However, it inhibited recycling of endosomal PD-L1 and reduced surface PD-L1 levels, which led to defects in interaction with PD-1. Anti-PD-1 did not expand effector-like T cells within DRG2-depleted tumors and failed to improve the survival of DRG2-depleted tumor-bearing mice. Cohort analysis revealed that patients bearing melanoma with low DRG2 protein levels were resistant to anti-PD-1 therapy. These findings identify DRG2 as a key regulator of recycling of endosomal PD-L1 and response to anti-PD-1 therapy and provide insights into how to increase the correlation between PD-L1 expression and response to anti-PD-1 therapy.

Interpretation of PD-L1 expression in gastric cancer: summary of a consensus meeting of Korean gastrointestinal pathologists

Nivolumab plus chemotherapy in the first-line setting has demonstrated clinical efficacy in patients with human epidermal growth factor receptor 2-negative advanced or metastatic gastric cancer, and is currently indicated as a standard treatment. Programmed death-ligand 1 (PD-L1) expression is an important biomarker for predicting response to anti-programmed death 1/PD-L1 agents in several solid tumors, including gastric cancer. In the CheckMate-649 trial, significant clinical improvements were observed in patients with PD-L1 combined positive score (CPS) ≥ 5, determined using the 28-8 pharmDx assay. Accordingly, an accurate interpretation of PD-L1 CPS, especially at a cutoff of 5, is important. The CPS method evaluates both immune and tumor cells and provides a comprehensive assessment of PD-L1 expression in the tumor microenvironment of gastric cancer. However, CPS evaluation has several limitations, one of which is poor interobserver concordance among pathologists. Despite these limitations, clinical indications relying on PD-L1 CPS are increasing. In response, Korean gastrointestinal pathologists held a consensus meeting for the interpretation of PD-L1 CPS in gastric cancer. Eleven pathologists reviewed 20 PD-L1 slides with a CPS cutoff close to 5, stained with the 28-8 pharmDx assay, and determined the consensus scores. The issues observed in discrepant cases were discussed. In this review, we present cases of gastric cancer with consensus PD-L1 CPS. In addition, we briefly touch upon current practices and clinical issues associated with assays used for the assessment of PD-L1 expression in gastric cancer.

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.

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.

Predictive and prognostic biomarkers in female genital tract tumours: an update highlighting their clinical relevance and practical issues

The evaluation of biomarkers by molecular techniques and immunohistochemistry has become increasingly relevant to the treatment of female genital tract tumours as a consequence of the greater availability of therapeutic options and updated disease classifications. For ovarian cancer, mutation testing for BRCA1/2 is the standard predictive biomarker for poly(ADP-ribose) polymerase inhibitor therapy, while homologous recombination deficiency testing may allow the identification of eligible patients among cases without demonstrable BRCA1/2 mutations. Clinical recommendations are available which specify how these predictive biomarkers should be applied. Mismatch repair (MMR) protein and folate receptor alpha immunohistochemistry may also be used to guide treatment in ovarian cancer. In endometrial cancer, MMR immunohistochemistry is the preferred test for predicting benefit from immune checkpoint inhibitor (ICI) therapy, but molecular testing for microsatellite instability may have a supplementary role. HER2 testing by immunohistochemistry and in situ hybridisation is applicable to endometrial serous carcinomas to assess trastuzumab eligibility. Immunohistochemistry for oestrogen receptor and progesterone receptor expression may be used for prognostication in endometrial cancer, but its predictive value for hormonal therapy is not yet proven. POLE mutation testing and p53 immunohistochemistry (as a surrogate for TP53 mutation status) serve as prognostic markers for favourable and adverse outcomes, respectively, in endometrial cancer, especially when combined with MMR testing for molecular subtype designation. For cervical cancer, programmed death ligand 1 immunohistochemistry may be used to predict benefit from ICI therapy although its predictive value is under debate. In vulvar cancer, p16 and p53 immunohistochemistry has established prognostic value, stratifying patients into three groups based on the human papillomavirus and TP53 mutation status of the tumour. Awareness of the variety and pitfalls of expression patterns for p16 and p53 in vulvar carcinomas is crucial for accurate designation. It is hoped that collaborative efforts in standardising and optimising biomarker testing for gynaecological tumours will contribute to evidence-based therapeutic decisions.

Molecular Characterization of TFE3-Rearranged Renal Cell Carcinoma: A Comparative Study With Papillary and Clear Cell Renal Cell Carcinomas

TFE3-rearranged renal cell carcinoma (rRCC) is a rare subtype of renal cell carcinomas belonging to the MiT family translocation RCC. To further elucidate the co-alterations that occur along with TFE3 fusions in rRCC, we characterized the genomic, transcriptional, and immune landscapes in comparison to clear cell (ccRCC) and papillary renal cell carcinoma (pRCC). Next-generation sequencing of RNA (whole transcriptome) and DNA (592-gene panel or whole exome) for rRCC (N = 20), pRCC (N = 20), and ccRCC samples (N = 392) was performed. Patients with rRCC were significantly younger and more frequently female (median 44.5 years, 75.0% female) as compared with patients with pRCC (68.5 years, 25.0% female; P < .05) and ccRCC (62.0 years, 27.8% female; P < .05). A total of 8 unique fusion partners were observed, including a novel fusion with SRRM2::TFE3 in 2 patients. ccRCC exhibited significantly higher mutation rates of VHL (0% rRCC, 0% pRCC, 78.7% ccRCC; P < .05) and PBMR1 (0% rRCC, 5.0% pRCC, 49.4% ccRCC; P < .05). The genomic landscapes of rRCC were sparse with no mutations occurring with a prevalence higher than 10% other than pTERT (18.2% rRCC, 0% pRCC, 9.2% ccRCC). rRCC were associated with significantly less M1 macrophages (0.8%) as compared with pRCC (1.4%) and ccRCC (2.7%) (P < .05), suggesting a cold tumor-immune microenvironment. However, rRCC were more commonly PD-L1+ (rRCC 50%, pRCC 19.0%, ccRCC 12.2%; P < .05). Gene set enrichment analysis showed that rRCC are enriched in genes related to oxidative phosphorylation when compared with both ccRCC and pRCC. Despite having a colder tumor-immune microenvironment than pRCC and ccRCC, increased PDL1+ rates in rRCC suggest a potential benefit from immune checkpoint inhibitor therapy.

Current and Future Biomarkers in Esophagogastric Adenocarcinoma

PURPOSE

Biomarker-based therapies have shown improved patient outcomes across various cancer types. The purpose of this review to summarize our knowledge of current and future biomarkers in esophagogastric adenocarcinoma (EGA).

METHODS

In this publication, we will review current standard biomarkers in patients with upper GI cancers. We will also discuss novel biomarkers that are under investigations and their associated therapies that are currently in clinical trials.

RESULTS

EGAa are a group of heterogeneous diseases, both anatomically and molecularly. There are several established biomarkers (HER2, PD-L1, microsattelite instability or mismatch repair protein expression) that allow for individualized treatments for patients with these cancers. There are also several emerging biomarkers for EGA, some of which have clinically relevant associated therapies. Claudin 18.2 is the furthest along among these. Anti-claudin antibody, zolbetuximab, improved overall survival in biomarker select patients with advanced GEA in two phase 3 studies. Other novel biomarkers, such as FGFR2b and DKN01, are also in the process of validation, and treatments based on the presence of these biomarkers are currently in clinical studies.

CONCLUSION

Ongoing efforts to identify novel biomarkers in EGA have led to enhanced subclassification of upper GI cancers. These advances, coupled with the strategic application of targeted therapies and immunotherapy when appropriate, hold promise to further improve patients outcomes.

A Clinical Viewpoint on the Use of Targeted Therapy in Advanced Gastric Cancer

The development of therapies for advanced gastric cancer (GC) has made significant progress over the past few years. The identification of new molecules and molecular targets is expanding our understanding of the disease's intricate nature. The end of the classical oncology era, which relied on well-studied chemotherapeutic agents, is giving rise to novel and unexplored challenges, which will cause a significant transformation of the current oncological knowledge in the next few years. The integration of established clinically effective regimens in additional studies will be crucial in managing these innovative aspects of GC. This study aims to present an in-depth and comprehensive review of the clinical advancements in targeted therapy and immunotherapy for advanced GC.

Prevalence and prognostic role of PD-L1 in patients with gynecological cancers: A systematic review and meta-analysis

OBJECTIVE

Our study aims to evaluate programmed cell death ligand-1 (PD-L1) expression and its prognostic significance in cervical cancer (CC), endometrial cancer (EC) and ovarian cancer (OC).

METHODS

Several electronic databases were searched. Fixed effects models or random effects models were employed to calculate the pooled prevalence of PD-L1 positivity and pooled hazard ratios (HRs) as appropriate. Heterogeneity and publication bias were also assessed.

RESULTS

The pooled prevalence of PD-L1 positivity was 58.1%, 33.8% and 37.5% for CC, EC and OC patients, respectively. There were significant differences in the pooled estimates after stratification by PD-L1-positive assessment criteria and antibody clones. PD-L1 positivity was associated with worse OS in CC and EC patients and poorer progression-free survival (PFS) in CC patients.

CONCLUSIONS

The prevalence of PD-L1-positive expression was considerably high in CC and modestly high in EC and OC patients. PD-L1 expression has the potential to be a prognostic biomarker for predicting the clinical outcomes of patients with CC and EC but not OC.

The Future of Precision Oncology

Our understanding of the molecular mechanisms underlying cancer development and evolution have evolved rapidly over recent years, and the variation from one patient to another is now widely recognized. Consequently, one-size-fits-all approaches to the treatment of cancer have been superseded by precision medicines that target specific disease characteristics, promising maximum clinical efficacy, minimal safety concerns, and reduced economic burden. While precision oncology has been very successful in the treatment of some tumors with specific characteristics, a large number of patients do not yet have access to precision medicines for their disease. The success of next-generation precision oncology depends on the discovery of new actionable disease characteristics, rapid, accurate, and comprehensive diagnosis of complex phenotypes within each patient, novel clinical trial designs with improved response rates, and worldwide access to novel targeted anticancer therapies for all patients. This review outlines some of the current technological trends, and highlights some of the complex multidisciplinary efforts that are underway to ensure that many more patients with cancer will be able to benefit from precision oncology in the near future.

Society for Immunotherapy of Cancer (SITC) clinical practice guideline on immunotherapy for the treatment of gynecologic cancer

Advanced gynecologic cancers have historically lacked effective treatment options. Recently, immune checkpoint inhibitors (ICIs) have been approved by the US Food and Drug Administration for the treatment of cervical cancer and endometrial cancer, offering durable responses for some patients. In addition, many immunotherapy strategies are under investigation for the treatment of earlier stages of disease or in other gynecologic cancers, such as ovarian cancer and rare gynecologic tumors. While the integration of ICIs into the standard of care has improved outcomes for patients, their use requires a nuanced understanding of biomarker testing, treatment selection, patient selection, response evaluation and surveillance, and patient quality of life considerations, among other topics. To address this need for guidance, the Society for Immunotherapy of Cancer (SITC) convened a multidisciplinary panel of experts to develop a clinical practice guideline. The Expert Panel drew on the published literature as well as their own clinical experience to develop evidence- and consensus-based recommendations to provide guidance to cancer care professionals treating patients with gynecologic cancer.

High Interobserver Variability among Pathologists Using Combined Positive Score to Evaluate PD-L1 Expression in Gastric, Gastroesophageal Junction and Esophageal Adenocarcinoma

Reliable, reproducible methods to interpret programmed death ligand-1 (PD-L1) expression on tumor cells (TC) and immune cells (IC) are needed for pathologists to inform decisions associated with checkpoint inhibitor therapies. Our international study compared interpathologist agreement of PD-L1 expression using combined positive score (CPS) under standardized conditions on samples from patients with gastric/gastroesophageal junction/esophageal adenocarcinoma. Tissue sections from 100 adenocarcinoma pre-treatment biopsies were stained in a single laboratory using the PD-L1 IHC 28-8 and 22C3(Agilent) pharmDx immunohistochemical assays. PD-L1 CPS was evaluated by 12 pathologists on scanned whole slide images of these biopsies before and after a 2-hour CPS training session by Agilent. Additionally, pathologists determined PD-L1 positive TC, IC, and total viable TC on a single tissue fragment from 35 of 100 biopsy samples. Scoring agreement among pathologists was assessed using the intraclass correlation coefficient (ICC). Interobserver variability for CPS for 100 biopsies was high with only fair agreement among pathologists both pre- (range 0.45 to 0.55) and post-training (range 0.56 to 0.57) for both assays. For the 35 single biopsy samples, poor/fair agreement was also observed for the total number viable TC (ICC 0.09), number of PD-L1 positive IC (ICC 0.19), number of PD-L1 positive TC (ICC 0.54), and calculated CPS (ICC 0.14), while calculated TC score (positive TC/Total TC) showed excellent agreement (ICC 0.82). Retrospective histologic review of samples with the poorest interpathologist agreement revealed (1) ambiguous identification of positively staining stromal cells, (2) faint or variable intensity of staining, (3) difficulty in distinguishing membranous from cytoplasmic tumor staining, and (4) cautery and crush artifact, as possible confounding factors. These results emphasize the need for objective techniques to standardize the interpretation of PD-L1 expression when using the CPS methodology on gastric/gastroesophageal junction cancer biopsies to accurately identify patients most likely to benefit from immune checkpoint inhibitor therapy.

The Ring Study: an international comparison of PD-L1 diagnostic assays and their interpretation in non-small cell lung cancer, head and neck squamous cell cancer and urothelial cancer

PD-L1 immunohistochemistry has been approved as a diagnostic assay for immunotherapy. However, an international comparison across multiple cancers is lacking. This study aimed to assess the performance of PD-L1 diagnostic assays in non-small cell lung cancer (NSCLC), head and neck squamous cell cancer (HNSCC) and urothelial cancer (UC). The excisional specimens of NSCLC, HNSCC and UC were assayed by Ventana SP263 and scored at three sites in each country, including Australia, Brazil, Korea, Mexico, Russia and Taiwan. All slides were rotated to two other sites for interobserver scoring. The same cohort of NSCLC was assessed with Dako 22C3 pharmDx PD-L1 for comparison. The PD-L1 immunopositivity was scored according to the approved PD-L1 scoring algorithms which were the percentage of PD-L1-expressing tumour cell (TC) and tumour proportion score (TPS) by Ventana SP263 and Dako 22C3 staining, respectively. In NSCLC, the comparison demonstrated the comparability of the SP263 and 22C3 assays (cut-off of 1%, κ=0.71; 25%, κ=0.75; 50%, κ=0.81). The interobserver comparisons showed moderate to almost perfect agreement for SP263 in TC staining at 25% cut-off (NSCLC, κ=0.72 to 0.86; HNSCC, κ=0.60 to 0.82; UC, κ=0.68 to 0.91) and at 50% cut-off for NSCLC (κ=0.64 to 0.90). Regarding the immune cell (IC) scoring in UC, there was a lower correlation (concordance correlation coefficient=0.10 to 0.68) and poor to substantial agreements at the 1%, 5%, 10% and 25% cut-offs (κ= -0.04 to 0.76). The interchangeability of SP263 and 22C3 in NSCLC might be acceptable, especially at the 50% cut-off. In HNSCC, the performance of SP263 is comparable across five countries. In UC, there was low concordance of IC staining, which may affect treatment decisions. Overall, the study showed the reliability and reproducibility of SP263 in NSCLC, HNSCC and UC.

PD-L1 testing by immunohistochemistry in immuno-oncology

Immunotherapy, based on immune checkpoint inhibitors targeting the Programmed cell death ligand 1 (PD-L1) and/or Programmed Death Receptor 1 (PD-1), has substantially improved the outcomes of patients with various cancers. However, only ~30% of patients benefit from immune checkpoint inhibitors. Tumor PD-L1 expression, assessed by immunohistochemistry, is the most widely validated and used predictive biomarker to guide the selection of patients for immune checkpoint inhibitors. PD-L1 assessment may be challenging due to the necessity for different companion diagnostic assays for required specific immune checkpoint inhibitors and a relatively high level of inter-assay variability in terms of performance and cutoff levels. In this review, we discuss the role of PD-L1 immunohistochemistry as a predictive test in immunotherapy (immuno-oncology), highlight the complexity of the PD-L1 testing landscape, discuss various preanalytical, analytical and clinical issues that are associated with PD-L1 assays, and provide some insights into optimization of PD-L1 as a predictive biomarker in immuno-oncology.

Modifying factors of PD-L1 expression on tumor cells in advanced non-small-cell lung cancer

BACKGROUND

Programmed death ligand-1 (PD-L1) expression predicts immunotherapy utility in nononcogenic addictive lung adenocarcinoma (ADC). However, its reproducibility and reliability may be compromised outside clinical trials. This study aimed to evaluate factors associated with PD-L1 expression in lung ADC.

METHODS

This observational study assessed 547 tumor samples with advanced lung ADC from January 2016 to December 2020 in a single cancer institution. Tumor samples were stained by at least one approved PD-L1 clone, SP263 (Ventana) or 22C3 (Dako), and stratified in tumor proportion score (TPS) <1%, 1-49%, or ≥50%.

RESULTS

Of all the tumor samples, positive PD-L1 staining was higher in poorly differentiated tumors (67.3% vs. 32.7%, p < 0.001). Analytical factors associated with a PD-L1 high expression (TPS ≥ 50%) were the SP263 clone (19.6% vs. 8.2%, p < 0.001), time of archival tumor tissue <12 months (15.3% vs. 3.8%, p = 0.024), whenever the analysis was performed in the most recent years (2019-2020) (19.0% vs. 8.3%, p < 0.001), and whenever the analysis was performed by pathologists in the academic setting (Instituto Nacional de Cancerologia, INCan) (19.9% vs. 11.9%, p = 0.001). In the molecular analysis, EGFR wild-type tumors had an increased proportion of PD-L1 positive and PD-L1 high cases (60.2% vs. 47.9%, p = 0.006 and 17.4% vs.8.5%, p = 0.004). A moderate correlation (r = 0.69) in the PD-L1 TPS% was observed between the two different settings (INCan vs. external laboratories).

CONCLUSION

Clinicopathological factors were associated with an increased PD-L1 positivity rate. These differences were significant in the PD-L1 high group and associated with the academic setting, the SPS263 clone, time of archival tumor tissue <12 months, and a more recent period in the PD-L1 analysis.

Immune checkpoint therapy and response biomarkers in non-small-cell lung cancer: Serum NY-ESO-1 and XAGE1 antibody as predictive and monitoring markers

Immune checkpoint inhibitors (ICI) are key drugs in systemic therapy for advanced non-small-cell lung cancer (NSCLC) and have recently been incorporated into neoadjuvant and adjuvant settings for surgical resection. Currently, ICI combinations with cytotoxic agents are frequently used in clinical practice, although several ICI clinical trials have failed to produce long-term clinical benefits. Unfortunately, clinical benefit is moderate and limited considering physical and financial burden. Therefore, selecting appropriate patients and regimens for ICI therapy is important, and biomarkers are necessary for their selection. Tumor PD-L1 expression is universally used as a biomarker; however, PD-L1 assays show low analytical validity and reproducibility due to the visual-scoring system by pathologists. Recent tumor immunology studies explore that neoantigens derived from somatic mutations and the collaboration between T and B cells efficiently elicit antitumor responses. This suggests that high tumor mutational burden and T-cell infiltration are predictive biomarkers. However, B cells producing antibody (Ab) remain poorly understood and analyzed as biomarkers. We found that NY-ESO-1 and XAGE1 of cancer-testis antigen frequently elicit spontaneous humoral and cellular immune responses in NSCLC. Serum Ab against these antigens were detected in approximately 25% of NSCLC patients and predicted ICI monotherapy responses. In addition, the Ab levels were decreased with tumor shrinkage after ICI therapy. Thus, NY-ESO-1 and XAGE1 Ab are potentially biomarkers predicting and monitoring response to ICI therapy. For clinical applications, a fully-automated assay system measuring the Ab was developed. Here, we review current ICI therapy, tumor immunology, and biomarkers in NSCLC, and discuss the applicability of the serum biomarkers NY-ESO-1 and XAGE1 Ab.

Validation of E1L3N antibody for PD-L1 detection and prediction of pembrolizumab response in non-small-cell lung cancer

BACKGROUND

The programmed death-ligand 1 (PD-L1) 22C3 assay is one of the approved companion diagnostic assays for receiving anti-programmed cell death ligand 1 (PD-L1) therapy. Our study evaluated the performance of E1L3N and 22C3 antibodies in estimating PD-L1 expression in non-small cell lung cancer (NSCLC).

METHODS

Our retrospective study included 46 patients diagnosed with unresectable EGFR/ALK/ROS1-negative NSCLC who received first-line pembrolizumab therapy between 2018 and 2021. PD-L1 immunohistochemistry of baseline tissue biopsy samples was performed using PDL1-E1L3N and PDL1-22C3 antibodies. The concordance between the PD-L1 assays and the treatment outcomes was assessed.

RESULTS

Using a tumor proportion score (TPS) cutoff of ≥1%, 67.4% of patients are evaluated to be positive using PDL1-E1L3N and 73.9% using PDL1-22C3. Using a TPS of ≥50% as the cutoff, 26.1% of patients are positive using PDL1-E1L3N and 30.4% using PDL1-22C3. The PDL1-22C3 and PDL1-E1L3N assays are highly concordant and reveal a correlation coefficient of 0.925 (p < 0.0001). Patients with PDL1-E1L3N TPS > 50% have a significantly higher objective response rate than patients with PDL1-E1L3N TPS < 1% (p = 0.047), with a similar trend observed for PDL1-22C3 (p = 0.051). Consistent with PDL1-22C3, patients with higher PDL1-E1L3N expression (≥50%, 1-49%) have longer progression-free survival than those with PDL1-E1L3N TPS < 1%.

CONCLUSION

Our study provides clinical evidence on the concordance of PD-L1 TPS scores between clones E1L3N and 22C3. Moreover, the treatment responses to pembrolizumab are also comparable between the PDL1-E1L3N and PDL1-22C3. These findings indicate that E1L3N is a reliable and cost-effective assay and may serve as an alternative to 22C3.

Comparison of PD-L1 tumor cell expression with 22C3, 28-8, and SP142 IHC assays across multiple tumor types

BACKGROUND

Multiple PD-L1 immunohistochemistry (IHC) assays, including DAKO 22C3, DAKO 28-8, and Ventana SP142 PD-L1 IHC assays, have been approved by the Food and Drug Administration as a companion diagnostic (CDx) for various antiprogrammed death-1 and antiprogrammed death ligand 1 (PD-L1) based cancer immunotherapies. Here we present 22C3, 28-8, and SP142 analysis of 418 tumor specimens encountered in routine clinical practice.

METHODS

All specimens were tested with 22C3, 28-8, and SP142 assays following the manufacturer's established staining protocols.

RESULTS

The same PD-L1 status (defined as tumor cell expression (TC) scores with all three assays ≥1% or all &lt;1%) was observed in 60.0% (251/418) tumor specimens (45.9% (192/418) were triple negative and 14.1% (59/418) were triple positive). A total of 54.1% (226/418) tumor cases were positive with at least one IHC assay (94.2% (213/226), 77.0% (174/226), and 28.8% (65/226) of these were positive for 22C3, 28-8 and SP142, respectively). Among the 40.0% (167/418) tumor cases that showed a different PD-L1 status, 62.3% (104/167) were 22C3+/28-8+/SP142-, and 28.7% (48/167) were 22C3+/28-8-/SP142-. The same PD-L1 status with all three antibody clones was observed in 48.7% (97/199) of NSCLC cases, and among these, 54.6% (53/97) were triple negative and 45.4% (44/97) triple positive. A total of 73.4% (146/199) NSCLC cases were positive with at least one IHC assay (95.2% (n=139/146), 82.2% (n=120/146), and 32.2% (n=47/146) were positive for 22C3, 28-8, and SP142, respectively). Among the 51.3% (102/199) NSCLC cases that showed a different status among the three IHC assays, 67.6% (69/102) were 22C3+/28-8+/SP142-, and 23.5% (24/102) were 22C3+/28-8-/SP142-. A total of 81.1% (43/53) lung squamous cell carcinoma, 72.1% (88/122) of lung adenocarcinoma, 69.6% (16/23) of non-small cell lung cancer (NSCLC) not otherwise specified (NOS), and 50.0% (4/8) of small cell lung carcinoma cases were positive with at least one IHC assay.

CONCLUSIONS

Our data suggest that 22C3 is the most sensitive PD-L1 IHC assay for tumor cell expression, followed by 28-8 and in turn by SP-142. These findings represent an additional factor for clinical teams to consider when deciding which PD-L1 IHC assay (and in turn which CDx-associated PD-L1 based immunotherapy) is most appropriate for each individual patient.

Esophagogastric Cancers: Integrating Immunotherapy Therapy Into Current Practice

Immunotherapy (IO) agents have led to significant improvements in patient outcomes across many tumor types. There have been great efforts to introduce immune checkpoint inhibitors into the treatment paradigm of esophagogastric cancers as well. A number of randomized phase III trials, which will be reviewed here, established the role of these agents in both early-stage and advanced-stage disease. Adjuvant nivolumab is US Food and Drug Administration-approved after neoadjuvant chemoradiation and resection of esophageal and gastroesophageal junction cancers on the basis of the phase III CheckMate 577 trial. In the advanced setting, patients with programmed death receptor ligand-1-positive tumors should be recommended IO in combination with chemotherapy in the first-line setting on the basis of the results from KEYNOTE 590, CheckMate 649, and CheckMate 648. Across trials, chemotherapy continues to play a critical role in the first-line setting and should be offered to all patients who are eligible for systemic therapy, including those with biomarker select tumors. In the later lines of treatment, IO has modest activity, and prior studies have grown largely irrelevant because of the enrollment of IO-naive patients. Similar to other disease types, patients with microsatellite unstable (microsatellite instability high) tumors represent a unique cohort that is more sensitive to IO. However, there are no randomized studies evaluating how best to apply IO in early or advanced stages specifically for the treatment of patients with microsatellite instability high upper GI tumors. Questions remain how to best select patients who benefit from IO treatments, how to augment IO activity in programmed death receptor ligand-1-negative tumors, and how to incorporate IO in late-line settings or for recurrent disease that has been treated with IO-containing regimens during early stages.

TCF1+PD-1+ tumour-infiltrating lymphocytes predict a favorable response and prolonged survival after immune checkpoint inhibitor therapy for non-small-cell lung cancer

BACKGROUND

T-cell factor 1 (TCF1)⁺Programmed cell death-1 (PD-1)⁺ tumour-infiltrating lymphocytes (TILs) are a recently defined subset of exhausted T-cells (Texh-cells) that exhibit a progenitor phenotype. They have been associated with a response to immune checkpoint inhibitor (ICI) therapy in murine tumour models and in patients with malignant melanoma. We investigated the significance of TCF1⁺PD-1⁺ TILs as a predictive biomarker for ICI therapy response in non-small-cell lung cancer (NSCLC).

METHODS

Two different cohorts of NSCLC patients treated with ICI targeting the PD-1/PD-L1 pathway were included. RNA-seq was performed using NSCLC tissues obtained from 234 patients prior to immunotherapy (RNA-seq cohort). Double immunostaining of TCF1 and PD-1 and single immunostaining of other immunologic markers were performed in resected tumour tissues from another 116 patients (immunohistochemistry cohort).

RESULTS

In the RNA-seq cohort, both Texh-cell and progenitor Texh-cell gene sets were enriched in responders compared with non-responders. Larger Texh-cell fractions and increased progenitor Texh-cell gene sets were significantly associated with better progression-free survival (PFS). In the immunohistochemistry cohort, the TCF1⁺PD-1⁺ TIL number and PD-L1 tumour proportion score were significantly higher in responders than in non-responders. A high number of TCF1⁺PD-1⁺ TILs was significantly associated with both PFS and overall survival (OS) after ICI therapy, and it independently predicted a better PFS and OS according to multivariate analysis.

CONCLUSION

TCF1⁺PD-1⁺ TILs, representing progenitor Texh-cells, predict both better response and survival in NSCLC patients after ICI therapy. Thus, they may be a useful predictive biomarker for ICI therapy in NSCLC.

From Immunohistochemistry to New Digital Ecosystems: A State-of-the-Art Biomarker Review for Precision Breast Cancer Medicine

Simple Summary

In this state-of-the-art breast biomarker review, we have tried to imagine and illustrate future, emerging digital breast cancer ecosystems which allow for greater incorporation of traditional immunohistochemical and molecular biomarkers, WSI, and radiomic features.

Abstract

Breast cancers represent complex ecosystem-like networks of malignant cells and their associated microenvironment. Estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) are biomarkers ubiquitous to clinical practice in evaluating prognosis and predicting response to therapy. Recent feats in breast cancer have led to a new digital era, and advanced clinical trials have resulted in a growing number of personalized therapies with corresponding biomarkers. In this state-of-the-art review, we included the latest 10-year updated recommendations for ER, PR, and HER2, along with the most salient information on tumor-infiltrating lymphocytes (TILs), Ki-67, PD-L1, and several prognostic/predictive biomarkers at genomic, transcriptomic, and proteomic levels recently developed for selection and optimization of breast cancer treatment. Looking forward, the multi-omic landscape of the tumor ecosystem could be integrated with computational findings from whole slide images and radiomics in predictive machine learning (ML) models. These are new digital ecosystems on the road to precision breast cancer medicine.

The Multi-Dimensional Biomarker Landscape in Cancer Immunotherapy

The field of immuno-oncology is now at the forefront of cancer care and is rapidly evolving. The immune checkpoint blockade has been demonstrated to restore antitumor responses in several cancer types. However, durable responses can be observed only in a subset of patients, highlighting the importance of investigating the tumor microenvironment (TME) and cellular heterogeneity to define the phenotypes that contribute to resistance as opposed to those that confer susceptibility to immune surveillance and immunotherapy. In this review, we summarize how some of the most widely used conventional technologies and biomarkers may be useful for the purpose of predicting immunotherapy outcomes in patients, and discuss their shortcomings. We also provide an overview of how emerging single-cell spatial omics may be applied to further advance our understanding of the interactions within the TME, and how these technologies help to deliver important new insights into biomarker discovery to improve the prediction of patient response.

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.

Expression of CD274 mRNA Measured by qRT-PCR Correlates With PD-L1 Immunohistochemistry in Gastric and Urothelial Carcinoma

Programmed death-ligand 1 (PD-L1) immunohistochemistry (IHC) is widely used to predict the clinical responses to immune checkpoint inhibitors (ICIs). However, PD-L1 IHC suffers from the complexity of multiple testing platforms and different cutoff values caused by the current one drug-one diagnostic test co-development approach for ICIs. We aimed to test whether PD-L1 (CD274) mRNA expression levels measured using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) can represent PD-L1 IHC and predict responses to ICI. The FDA-approved PD-L1 IHC results with 22C3 pharmDx (gastric cancer) and SP142 (urothelial carcinoma) were compared with CD274 mRNA expression levels via qRT-PCR using the same formalin-fixed, paraffin-embedded tissue blocks from 59 gastric cancer and 41 urothelial carcinoma samples. CD274 mRNA expression was identified using three independent sets of primers and TaqMan® probes targeting exon 1-2, exon 3-4, and exon 5-6. CD274 mRNA levels in spanning exon 1-2, exon 3-4, and exon 5-6 junctions of CD274 correlated well with PD-L1 expression (r²=0.81, 0.65, and 0.59, respectively). The area under the curve of exon 1-2 was the highest (0.783), followed by exon 3-4 (0.701), and exon 5-6 (0.671) of the CD274 gene against the PD-L1 combined positive score cutoff of 10. When CD274 mRNA expression was matched for response to immunotherapy, the overall response rate was higher in patients with high CD274 mRNA levels with a cutoff of 0.0722 (gastric cancer) and 0.0480 (urothelial carcinoma) than in those with low CD274 mRNA expression (P < 0.001 and P = 0.018, respectively). These results show that CD274 mRNA levels predicted ICI responses in patients with gastric or urothelial carcinomas and could be used as alternatives for PD-L1 IHC.

Biomarkers of response to PD-1 pathway blockade

The binding of T cell immune checkpoint proteins programmed death 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) to their ligands allows immune evasion by tumours. The development of therapeutic antibodies, termed checkpoint inhibitors, that bind these molecules or their ligands, has provided a means to release this brake on the host anti-tumour immune response. However, these drugs are costly, are associated with potentially severe side effects, and only benefit a small subset of patients. It is therefore important to identify biomarkers that discriminate between responders and non-responders. This review discusses the determinants for a successful response to antibodies that bind PD-1 or its ligand PD-L1, dividing them into markers found in the tumour biopsy and those in non-tumour samples. It provides an update on the established predictive biomarkers (tumour PD-L1 expression, tumour mismatch repair deficiency and tumour mutational burden) and assesses the evidence for new potential biomarkers.

Toripalimab plus axitinib in patients with metastatic mucosal melanoma: 3-year survival update and biomarker analysis

BACKGROUND

Mucosal melanoma is an aggressive melanoma subtype with poor response to antiprogrammed cell death-1 (PD-1) monotherapy. Axitinib in combination with toripalimab, a humanized IgG4 mAb against PD-1, showed a promising response rate in patients with metastatic mucosal melanoma (MM) in a phase Ib study. Here, we report the updated overall survival (OS), duration of response (DoR), and biomarker analysis results.

METHODS

Patients with advanced MM received toripalimab 1 or 3 mg/kg intravenously every 2 weeks combined with axitinib 5 mg orally two times per day until disease progression or unacceptable toxicity. Tumor programmed cell death ligand-1 (PD-L1) expression, tumor mutational burden (TMB), and gene expression profile (GEP) by messenger RNA sequencing were evaluated for correlation with survival.

RESULTS

As of April 2, 2021, the median follow-up was 42.5 months. Among 29 chemotherapy-naïve patients with metastatic MM, the median OS was 20.7 months (95% CI 9.7 to 32.7 months); the median progression-free survival (PFS) was 7.5 months (95% CI 3.8 to 14.8 months); and the median DoR was 13.4 months (95% CI 5.5 to 20.6 months). The OS rates of 1, 2, and 3 years were 62.1%, 44.8%, and 31.0%, respectively. Biomarker analysis found that PD-L1 expression and TMB level were not associated with survival benefits. In contrast, a 12-GEP signature correlated with improved PFS (17.7 vs 5.7 months, p=0.0083) and OS (35.6 vs 17.6 months, p=0.039).

CONCLUSIONS

The 3-year survival update confirmed the antitumor activity and long-term survival benefit of the toripalimab plus axitinib combination in patients with advanced MM. The 12-gene GEP is of value in predicting the outcomes of vascular endothelial growth factor receptor-tyrosine kinase inhibitor and PD-1 blockade combination therapy, but requires further validation.

TRIAL REGISTRATION NUMBERS

NCT03086174.

Biomarkers of response to checkpoint inhibitors beyond PD-L1 in lung cancer

Immunotherapy, including use of checkpoint inhibitors against PD-1, PD-L1, and CTLA-4, forms the backbone of oncologic management for the majority of non-small cell lung carcinoma patients. However, response to these therapies varies widely, from patients who have complete resolution of metastatic disease and long-term remission, to those who rapidly progress and succumb to their cancer despite use of the newest checkpoint inhibitors. While PD-L1 protein expression by immunohistochemistry serves as the principle predictive biomarker for immunotherapy response, neither the sensitivity nor the specificity of this approach is optimal, and clinical PD-L1 testing is plagued by concerns around result reproducibility and confusion born from the proliferation of different companion diagnostic assays. At the same time, insights into tumor and host immune-specific factors that inform both prognosis and response prediction are beginning to define better immunotherapy biomarkers. Beyond immune checkpoint expression status, common themes in analyses of immunotherapy response prediction include cancer neoantigen production, the state of the antigen presentation pathway in both tumor and antigen presenting cells, the admixture of effector and suppressor immune cells in the tumor microenvironment, and the genomic drivers and comutations that can influence the all of these variables. This review will address the state of PD-L1 testing in lung cancer, the role for tumor mutation burden as a predictive biomarker, the evolving status of human leukocyte antigen/major histocompatibility complex expression as a marker of antigen presentation, approaches to tumor immune cell quantitation including by multiplex immunofluorescence, and the importance of tumor genomic profiling to ascertain oncogenic driver (EGFR, ALK, KRAS, MET, etc.) and co-mutation (STK11, KEAP1, SMARCA4) status.

Association of artificial intelligence-powered and manual quantification of programmed death-ligand 1 (PD-L1) expression with outcomes in patients treated with nivolumab ± ipilimumab

Assessment of programmed death ligand 1 (PD-L1) expression by immunohistochemistry (IHC) has emerged as an important predictive biomarker across multiple tumor types. However, manual quantitation of PD-L1 positivity can be difficult and leads to substantial inter-observer variability. Although the development of artificial intelligence (AI) algorithms may mitigate some of the challenges associated with manual assessment and improve the accuracy of PD-L1 expression scoring, use of AI-based approaches to oncology biomarker scoring and drug development has been sparse, primarily due to the lack of large-scale clinical validation studies across multiple cohorts and tumor types. We developed AI-powered algorithms to evaluate PD-L1 expression on tumor cells by IHC and compared it with manual IHC scoring in urothelial carcinoma, non-small cell lung cancer, melanoma, and squamous cell carcinoma of the head and neck (prospectively determined during the phase II and III CheckMate clinical trials). 1,746 slides were retrospectively analyzed, the largest investigation of digital pathology algorithms on clinical trial datasets performed to date. AI-powered quantification of PD-L1 expression on tumor cells identified more PD-L1-positive samples compared with manual scoring at cutoffs of ≥1% and ≥5% in most tumor types. Additionally, similar improvements in response and survival were observed in patients identified as PD-L1-positive compared with PD-L1-negative using both AI-powered and manual methods, while improved associations with survival were observed in patients with certain tumor types identified as PD-L1-positive using AI-powered scoring only. Our study demonstrates the potential for implementation of digital pathology-based methods in future clinical practice to identify more patients who would benefit from treatment with immuno-oncology therapy compared with current guidelines using manual assessment.