High-Plex Assessment of Biomarkers in Tumors.

The assessment of biomarkers plays a critical role in the diagnosis and treatment of many cancers. Biomarkers not only provide diagnostic, prognostic, or predictive information but also can act as effective targets for new pharmaceutical therapies. As the utility of biomarkers increases, it becomes more important to utilize accurate and efficient methods for biomarker discovery and, ultimately, clinical assessment. High-plex imaging studies, defined here as assessment of 8 or more biomarkers on a single slide, have become the method of choice for biomarker discovery and assessment of biomarker spatial context. In this review, we discuss methods of measuring biomarkers in slide-mounted tissue samples, detail the various high-plex methods that allow for the simultaneous assessment of multiple biomarkers in situ, and describe the impact of high-plex biomarker assessment on the future of anatomic pathology.

Assessment of the Impact of Alternative Fixatives on HER2 Detection in Breast Cancer and Gastric Cancer Tumor Specimens.

The type of fixative used for preserving tumor specimens can significantly impact the performance of the immunohistochemistry and in situ hybridization assays used for assessing human epidermal growth factor receptor 2 (HER2) status. This study reports the prevalence of the use of alternative fixatives other than the guideline-recommended 10% neutral buffered formalin (NBF) during HER2 testing in a real-world setting. The effects of alternative fixatives [20% NBF and 10% unbuffered formalin (UBF) fixatives] on HER2 testing of breast cancer (BC) and gastric cancer (GC) cell lines and tissues are also assessed. Overall, 117,636 tumor samples received at a central laboratory from >8000 clinical trial sites across 60 countries were reviewed to determine the prevalence of alternative fixative usage. To investigate the impact of alternative fixatives, 27 cell lines (21 BC and 6 GC) and 76 tumor tissue samples (50 BC and 26 GC) were fixed in 10% NBF, 20% NBF, or 10% UBF, and evaluated for HER2 status by immunohistochemistry and in situ hybridization. Real-world data showed that 9195 (7.8%) tumor samples were preserved using an alternative fixative. In cell lines, overall percentage agreement, negative percentage agreement, and positive percentage agreement among the 3 fixatives were 100%. In tumor tissues, the agreement among 10% NBF, 20% NBF, and 10% UBF ranged between 94.7% and 96.6% for negative percentage agreement and 90.9% for overall percentage agreement compared with a range of 58.3% to 66.7% for positive percentage agreement. These results suggest that alternative fixatives may have the potential to convert HER2 status in tissues from positive to negative.

Multi-institutional Assessment of Pathologist Scoring HER2 Immunohistochemistry.

The HercepTest was approved 20+ years ago as the companion diagnostic test for trastuzumab in human epidermal growth factor 2 (HER2) or ERBB2 gene-amplified/overexpressing breast cancers. Subsequent HER2 immunohistochemistry (IHC) assays followed, including the now most common Ventana 4B5 assay. Although this IHC assay has become the clinical standard, its reliability, reproducibility, and accuracy have largely been approved and accepted on the basis of concordance among small numbers of pathologists without validation in a real-world setting. In this study, we evaluated the concordance and interrater reliability of scoring HER2 IHC in 170 breast cancer biopsies by 18 breast cancer-specialized pathologists from 15 institutions. We used the Observers Needed to Evaluate Subjective Tests method to determine the plateau of concordance and the minimum number of pathologists needed to estimate interrater agreement values for large numbers of raters, as seen in the real-world setting. We report substantial discordance within the intermediate categories (<1% agreement for 1+ and 3.6% agreement for 2+) in the 4-category HER2 IHC scoring system. The discordance within the IHC 0 cases is also substantial with an overall percent agreement (OPA) of only 25% and poor interrater reliability metrics (0.49 Fleiss' kappa, 0.55 intraclass correlation coefficient). This discordance can be partially reduced by using a 3-category system (28.8% vs 46.5% OPA for 4-category and 3-category scoring systems, respectively). Observers Needed to Evaluate Subjective Tests plots suggest that the OPA for the task of determining a HER2 IHC score 0 from not 0 plateaus statistically around 59.4% at 10 raters. Conversely, at the task of scoring HER2 IHC as 3+ or not 3+ pathologists' concordance was much higher with an OPA that plateaus at 87.1% with 6 raters. This suggests that legacy HER2 IHC remains valuable for finding the patients in whom the ERBB2 gene is amplified but unacceptably discordant in assigning HER2-low or HER2-negative status for the emerging HER2-low therapies.

Proceedings From the ASCO/College of American Pathologists Immune Checkpoint Inhibitor Predictive Biomarker Summit.

PURPOSE: Immune checkpoint inhibition (ICI) therapy represents one of the great advances in the field of oncology, highlighted by the Nobel Prize in 2018. Multiple predictive biomarkers for ICI benefit have been proposed. These include assessment of programmed death ligand-1 expression by immunohistochemistry, and determination of mutational genotype (microsatellite instability or mismatch repair deficiency or tumor mutational burden) as a reflection of neoantigen expression. However, deployment of these assays has been challenging for oncologists and pathologists alike. METHODS: To address these issues, ASCO and the College of American Pathologists convened a virtual Predictive Factor Summit from September 14 to 15, 2021. Representatives from the academic community, US Food and Drug Administration, Centers for Medicare and Medicaid Services, National Institutes of Health, health insurance organizations, pharmaceutical companies, in vitro diagnostics manufacturers, and patient advocate organizations presented state-of-the-art predictive factors for ICI, associated problems, and possible solutions. RESULTS: The Summit provided an overview of the challenges and opportunities for improvement in assay execution, interpretation, and clinical applications of programmed death ligand-1, microsatellite instability-high or mismatch repair deficient, and tumor mutational burden-high for ICI therapies, as well as issues related to regulation, reimbursement, and next-generation ICI biomarker development. CONCLUSION: The Summit concluded with a plan to generate a joint ASCO/College of American Pathologists strategy for consideration of future research in each of these areas to improve tumor biomarker tests for ICI therapy.

Objective assessment of tumor infiltrating lymphocytes as a prognostic marker in melanoma using machine learning algorithms.

BACKGROUND: The prognostic value of tumor-infiltrating lymphocytes (TILs) assessed by machine learning algorithms in melanoma patients has been previously demonstrated but has not been widely adopted in the clinic. We evaluated the prognostic value of objective automated electronic TILs (eTILs) quantification to define a subset of melanoma patients with a low risk of relapse after surgical treatment. METHODS: We analyzed data for 785 patients from 5 independent cohorts from multiple institutions to validate our previous finding that automated TIL score is prognostic in clinically-localized primary melanoma patients. Using serial tissue sections of the Yale TMA-76 melanoma cohort, both immunofluorescence and Hematoxylin-and-Eosin (H&E) staining were performed to understand the molecular characteristics of each TIL phenotype and their associations with survival outcomes. FINDINGS: Five previously-described TIL variables were each significantly associated with overall survival (p<0.0001). Assessing the receiver operating characteristic (ROC) curves by comparing the clinical impact of two models suggests that etTILs (electronic total TILs) (AUC: 0.793, specificity: 0.627, sensitivity: 0.938) outperformed eTILs (AUC: 0.77, specificity: 0.51, sensitivity: 0.938). We also found that the specific molecular subtype of cells representing TILs includes predominantly cells that are CD3+ and CD8+ or CD4+ T cells. INTERPRETATION: eTIL% and etTILs scores are robust prognostic markers in patients with primary melanoma and may identify a subgroup of stage II patients at high risk of recurrence who may benefit from adjuvant therapy. We also show the molecular correlates behind these scores. Our data support the need for prospective testing of this algorithm in a clinical trial. FUNDING: This work was also supported by a sponsored research agreements from Navigate Biopharma and NextCure and by grants from the NIH including the Yale SPORE in in Skin Cancer, P50 CA121974, the Yale SPORE in Lung Cancer, P50 CA196530, NYU SPORE in Skin Cancer P50CA225450 and the Yale Cancer Center Support Grant, P30CA016359.

Quantitative assessment of Siglec-15 expression in lung, breast, head, and neck squamous cell carcinoma and bladder cancer.

Immune checkpoint blockade with programmed cell death (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors has resulted in significant progress in the treatment of various cancer types. However, not all patients respond to PD-1/PD-L1 blockade, underscoring the importance of identifying new potential targets for immunotherapy. One promising target is the immune system modulator Siglec-15. In this study, we assess Siglec-15 expression in solid tumors, with a focus on lung, breast, head and neck squamous and bladder cancers. Using quantitative immunofluorescence (QIF) with a previously validated antibody, we found increased Siglec-15 expression in both tumor and immune cells in all the four cancer types. Siglec-15 was seen to be predominantly expressed by the stromal immune cells (83% in lung, 70.1% in breast, 95.2% in head and neck squamous cell and 89% in bladder cancers). Considerable intra-tumoral heterogeneity was noted across cancer types. As previously described for non-small cell lung cancer (NSCLC), Siglec-15 expression was seen to be mutually exclusive to PD-L1 in all the four cancer types, although this differential expression was maintained but somewhat diminished in head and neck squamous cell carcinoma (HNSCC). Siglec-15 was not prognostic either for overall survival (OS) or progression-free survival (PFS). In summary, we show broad expression of this potential immune modulatory target in a wide range of cancer types. These data suggest potential future clinical trials in these tumor types.

Quantitative assessment of the immune microenvironment in African American Triple Negative Breast Cancer: a case-control study.

PURPOSE: Triple negative breast cancer (TNBC) is more common in African American (AA) than Non-AA (NAA) population. We hypothesize that tumor microenvironment (TME) contributes to this disparity. Here, we use multiplex quantitative immunofluorescence to characterize the expression of immunologic biomarkers in the TME in both populations. PATIENTS AND METHODS: TNBC tumor resection specimen tissues from a 100-patient case: control cohort including 49 AA and 51 NAA were collected. TME markers including CD45, CD14, CD68, CD206, CD4, CD8, CD20, CD3, Ki67, GzB, Thy1, FAP, aSMA, CD34, Col4, VWF and PD-L1 we quantitatively assessed in every field of view. Mean expression levels were compared between cases and controls. RESULTS: Although no significant differences were detected in individual lymphoid and myeloid markers, we found that infiltration with CD45+ immune cells (p = 0.0102) was higher in TNBC in AA population. AA TNBC tumors also had significantly higher level of lymphocytic infiltration defined as CD45+ CD14- cells (p = 0.0081). CD3+ T-cells in AA tumors expressed significantly higher levels of Ki67 (0.0066) compared to NAAs, indicating that a higher percentage of AA tumors contained activated T-cells. All other biomarkers showed no significant differences between the AA and NAA group. CONCLUSIONS: While the TME in TNBC is rich in immune cells in both racial groups, there is a numerical increase in lymphoid infiltration in AA compared to NAA TNBC. Significantly, higher activated T cells seen in AA patients raises the possibility that there may be a subset of AA patients with improved response to immunotherapy.

Quantitative Assessment of CD200 and CD200R Expression in Lung Cancer.

CD200/CD200R is an immune checkpoint with broad expression patterns and a potential target for immune therapy. In this study, we assess both CD200 and CD200R expression in solid tumors, with a focus on lung cancer, and evaluate their association with clinicopathologic characteristics, mutation status, outcome, and programmed death-ligand 1 (PD-L1) expression. We used multiplexed quantitative immunofluorescence (QIF) to measure the expression of CD200 and CD200R in a total of 455 patients from three lung cancer cohorts. Using carefully validated antibodies, we performed target measurement with tyramide-based QIF panels and analyzed the data using the PM2000 microscope and AQUA software. CD200 tumor positivity was found in 29.7% of non-small cell lung cancer (NSCLC) patients and 33.3% of lung large cell neuroendocrine carcinoma (LCNEC) patients. CD200 demonstrated notable intratumoral heterogeneity. CD200R was expressed in immune cells in 25% of NSCLC and 41.3% of LCNEC patients. While CD200R is predominantly expressed in immune cells, rare tumor cell staining was seen in a highly heterogeneous pattern. CD200R expression in the stromal compartment was significantly higher in patients with squamous differentiation (p < 0.0001). Neither CD200 nor CD200R were associated with other clinicopathologic characteristics or mutation status. Both biomarkers were not prognostic for disease-free or overall survival in NSCLC. CD200 showed moderate correlation with PD-L1. CD200/CD200R pathway is frequently expressed in lung cancer patients. Differential expression patterns of CD200 and CD200R with PD-L1 suggest a potential role for targeting this pathway alone in patients with NSCLC.

Automated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma.

Accurate prognostic biomarkers in early-stage melanoma are urgently needed to stratify patients for clinical trials of adjuvant therapy. We applied a previously developed open source deep learning algorithm to detect tumor-infiltrating lymphocytes (TILs) in hematoxylin and eosin (H&E) images of early-stage melanomas. We tested whether automated digital (TIL) analysis (ADTA) improved accuracy of prediction of disease specific survival (DSS) based on current pathology standards. ADTA was applied to a training cohort (n = 80) and a cutoff value was defined based on a Receiver Operating Curve. ADTA was then applied to a validation cohort (n = 145) and the previously determined cutoff value was used to stratify high and low risk patients, as demonstrated by Kaplan-Meier analysis (p ≤ 0.001). Multivariable Cox proportional hazards analysis was performed using ADTA, depth, and ulceration as co-variables and showed that ADTA contributed to DSS prediction (HR: 4.18, CI 1.51-11.58, p = 0.006). ADTA provides an effective and attainable assessment of TILs and should be further evaluated in larger studies for inclusion in staging algorithms.

Assessment of Ki67 in Breast Cancer: Updated Recommendations From the International Ki67 in Breast Cancer Working Group.

Ki67 immunohistochemistry (IHC), commonly used as a proliferation marker in breast cancer, has limited value for treatment decisions due to questionable analytical validity. The International Ki67 in Breast Cancer Working Group (IKWG) consensus meeting, held in October 2019, assessed the current evidence for Ki67 IHC analytical validity and clinical utility in breast cancer, including the series of scoring studies the IKWG conducted on centrally stained tissues. Consensus observations and recommendations are: 1) as for estrogen receptor and HER2 testing, preanalytical handling considerations are critical; 2) a standardized visual scoring method has been established and is recommended for adoption; 3) participation in and evaluation of quality assurance and quality control programs is recommended to maintain analytical validity; and 4) the IKWG accepted that Ki67 IHC as a prognostic marker in breast cancer has clinical validity but concluded that clinical utility is evident only for prognosis estimation in anatomically favorable estrogen receptor-positive and HER2-negative patients to identify those who do not need adjuvant chemotherapy. In this T1-2, N0-1 patient group, the IKWG consensus is that Ki67 5% or less, or 30% or more, can be used to estimate prognosis. In conclusion, analytical validity of Ki67 IHC can be reached with careful attention to preanalytical issues and calibrated standardized visual scoring. Currently, clinical utility of Ki67 IHC in breast cancer care remains limited to prognosis assessment in stage I or II breast cancer. Further development of automated scoring might help to overcome some current limitations.

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group.

Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.

Prospective multi-institutional evaluation of pathologist assessment of PD-L1 assays for patient selection in triple negative breast cancer.

The US Food and Drug Administration (FDA) approved the PD-L1 immunohistochemical assay, SP142, as a companion test to determine eligibility for atezolizumab therapy in patients with advanced triple negative breast cancer (TNBC) but data in lung cancer studies suggest the assay suffers from poor reproducibility. We sought to evaluate reproducibility and concordance in PD-L1 scoring across multiple pathologists. Full TNBC sections were stained with SP142 and SP263 assays and interpreted for percentage (%) immune cell (IC) staining by 19 pathologists from 14 academic institutions. Proportion of PD-L1 positive cases (defined as ≥1% IC) was determined for each assay as well as concordance across observers. We utilized a new method we call Observers Needed to Evaluate Subjective Tests (ONEST) to determine the minimum number of evaluators needed to estimate concordance between large numbers of readers, as occurs in the real-world setting. PD-L1 was interpreted as positive with the SP142 assay in an average 58% of cases compared with 78% with SP263 (p < 0.0001). IC positive continuous scores ranged from 1 to 95% (mean = 20%) and 1 to 90% (mean = 10%) for SP263 and SP142, respectively. With SP142, 26 cases (38%) showed complete two category (<1% vs. ≥1%) concordance; with SP263, 38 cases (50%) showed complete agreement. The intraclass correlation coefficient (ICC) for two category scoring of SP263 and SP142 was 0.513 and 0.560. ONEST plots showed decreasing overall percent agreement (OPA) as observer number increased, reaching a low plateau of 0.46 at ten observers for SP263 and 0.41 at eight observers for SP142. IC scoring with both assays showed poor reproducibility across multiple pathologists with ONEST analysis suggesting more than half of pathologists will disagree about IC scores. This could lead to many patients either receiving atezolizumab when they are unlikely to benefit, or not receiving atezolizumab when they may benefit.

Digital quantitative assessment of PD-L1 using digital spatial profiling.

The assessment of programmed death 1 ligand 1 (PD-L1) expression by Immunohistochemistry (IHC) is the US Food and Drug Administration (FDA)-approved predictive marker to select responders to checkpoint blockade anti-PD-1/PD-L1 axis immunotherapies. Different PD-L1 immunohistochemistry (IHC) assays use different antibodies and different scoring methods in tumor cells and immune cells. Multiple studies have compared the performance of these assays with variable results. Here, we investigate an alternative method for assessment of PD-L1 using a new technology known as digital spatial profiling. We use a previously described standardization tissue microarray (TMA) to assess the accuracy of the method and compare digital spatial profiler (DSP) to each FDA-approved PD-L1 assays, one LDT assay and three quantitative fluorescence assays. The standardized cell line Index tissue microarray contains 10 isogenic cells lines in triplicates expressing various ranges of PD-L1. The dynamic range of PD-L1 digital counts was measured in the ten cell lines on the Index TMA using the GeoMx DSP assay and read on the nCounter platform. The digital method shows very high correlation with immunohistochemistry scored with quantitative software and with quantitative fluorescence. High correlation of PD-L1 digital DSP counts were seen between rows on the same Index TMA. Finally, experiments from two Index TMAs showed reproducibility of DSP counts were independent of variable slide storage time over a three-week period after antibody labeling but before collection of cleaved tags. In summary, DSP appears to have quantitative potential comparable to quantitative immunohistochemistry. It is possible that this technology could be used as a PD-L1 protein measurement system for companion diagnostic testing for immune therapy.

The path to a better biomarker: application of a risk management framework for the implementation of PD-L1 and TILs as immuno-oncology biomarkers in breast cancer clinical trials and daily practice.

Immune checkpoint inhibitor therapies targeting PD-1/PD-L1 are now the standard of care in oncology across several hematologic and solid tumor types, including triple negative breast cancer (TNBC). Patients with metastatic or locally advanced TNBC with PD-L1 expression on immune cells occupying ≥1% of tumor area demonstrated survival benefit with the addition of atezolizumab to nab-paclitaxel. However, concerns regarding variability between immunohistochemical PD-L1 assay performance and inter-reader reproducibility have been raised. High tumor-infiltrating lymphocytes (TILs) have also been associated with response to PD-1/PD-L1 inhibitors in patients with breast cancer (BC). TILs can be easily assessed on hematoxylin and eosin-stained slides and have shown reliable inter-reader reproducibility. As an established prognostic factor in early stage TNBC, TILs are soon anticipated to be reported in daily practice in many pathology laboratories worldwide. Because TILs and PD-L1 are parts of an immunological spectrum in BC, we propose the systematic implementation of combined PD-L1 and TIL analyses as a more comprehensive immuno-oncological biomarker for patient selection for PD-1/PD-L1 inhibition-based therapy in patients with BC. Although practical and regulatory considerations differ by jurisdiction, the pathology community has the responsibility to patients to implement assays that lead to optimal patient selection. We propose herewith a risk-management framework that may help mitigate the risks of suboptimal patient selection for immuno-therapeutic approaches in clinical trials and daily practice based on combined TILs/PD-L1 assessment in BC. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Quantitative assessment of PD-L1 as an analyte in immunohistochemistry diagnostic assays using a standardized cell line tissue microarray.

Programmed death 1 ligand 1 (PD-L1) Immunohistochemistry (IHC) is the key FDA-approved predictive marker to identify responders to anti-PD1 axis drugs. Multiple PD-L1 IHC assays with various antibodies and cut points have been used in clinical trials across tumor types. Comparative performance characteristics of these assays have been extensively studied qualitatively but not quantitatively. Here we evaluate the use of a standardized PD-L1 Index tissue microarray (TMA) to objectively determine agreement between antibody assays for PD-L1 applying quantitative digital image analysis. Using a specially constructed Index TMA containing a panel of ten isogenic cell lines in triplicate, we tested identical but independently grown batches of isogenic cells to prove Index TMAs can be produced in large quantities and hence serve as a standardization tool. Then the Index TMAs were evaluated using quantitative immunofluorescence (QIF) to validate the TMA itself and also to compare antibodies including E1L3N, SP142 and SP263. Next, an inter-laboratory and inter-assay comparison of 5 PD-L1 chromogenic IHC assays (US Food and Drug Administration (FDA) approved and lab developed test (LDT)) were performed at 12 sites around the USA. As previously reported, the SP142 FDA assay failed to detect low levels of PD-L1 in cell lines distinguished by the other four assays. The assays for 22C3 FDA, 28-8-FDA, SP263 FDA, and E1L3N LDT were highly similar across sites and all laboratories showed a high consistency over time for all assays using this Index TMA. In conclusion, we were able to objectively quantify PD-L1 expression on a standardized Index TMA using digital image analysis and we confirmed previous subjective assessments of these assays, but now in a multi-institutional setting. We envision commercial use of this Index TMA or similar smaller version as a useful standardization mechanism to compare results between institutions and to identify abnormalities while running routine clinical samples.

Quantitative Assessment of CMTM6 in the Tumor Microenvironment and Association with Response to PD-1 Pathway Blockade in Advanced-Stage Non-Small Cell Lung Cancer.

INTRODUCTION: CKLF like MARVEL transmembrane domain containing 6 (CMTM6) has been described as a programmed death ligand 1 (PD-L1) regulator at the protein level by modulating stability through ubiquitination. In this study, we describe the patterns of CMTM6 expression and assess its association with response to programmed cell death 1 pathway blockade in NSCLC. METHODS: We used multiplexed quantitative immunofluorescence to determine the expression of CMTM6 and PD-L1 in 438 NSCLCs represented in tissue microarrays, including in two independent retrospective cohorts of immunotherapy-treated (n = 69) and non-immunotherapy-treated (n = 258) patients and a third collection of EGFR- and KRAS-genotyped tumors (n = 111). RESULTS: Tumor and stromal CMTM6 expression was detected in approximately 70% of NSCLCs. CMTM6 expression was not associated with clinical features or EGFR/KRAS mutational status and showed a modest correlation with T-cell infiltration (R2 < 0.40). We found a significant correlation between CMTM6 and PD-L1, which was higher in the stroma (R2 = 0.51) than in tumor cells (R2 = 0.35). In our retrospective NSCLC cohort, neither CMTM6 nor PD-L1 expression alone significantly predicted immunotherapy outcomes. However, high CMTM6 and PD-L1 coexpression in the stromal and CD68 compartments (adjusted hazard ratio = 0.38, p = 0.03), but not in tumor cells (p = 0.15), was significantly associated with longer overall survival in treated patients but was not observed in the absence of immunotherapy. CONCLUSION: This study supports the mechanistic role for CMTM6 in stabilization of PD-L1 in patient tumors and suggests that high coexpression of CMTM6 and PD-L1, particularly in stromal immune cells (macrophages), might identify the greatest benefit from programmed cell death 1 axis blockade in NSCLC.

Addressing the dichotomy between individual and societal approaches to personalised medicine in oncology.

Academic, industry, regulatory leaders and patient advocates in cancer clinical research met in November 2018 at the Innovation and Biomarkers in Cancer Drug Development meeting in Brussels to address the existing dichotomy between increasing calls for personalised oncology approaches based on individual molecular profiles and the need to make resource and regulatory decisions at the societal level in differing health-care delivery systems around the globe. Novel clinical trial designs, the utility and limitations of real-world evidence (RWE) and emerging technologies for profiling patient tumours and tumour-derived DNA in plasma were discussed. While randomised clinical trials remain the gold standard approach to defining clinical utility of local and systemic therapeutic interventions, the broader adoption of comprehensive tumour profiling and novel trial designs coupled with RWE may allow patient and physician autonomy to be appropriately balanced with broader assessments of safety and overall societal benefit.

A Multi-Institutional Study to Evaluate Automated Whole Slide Scoring of Immunohistochemistry for Assessment of Programmed Death-Ligand 1 (PD-L1) Expression in Non-Small Cell Lung Cancer.

Assessment of programmed death-ligand 1 (PD-L1) expression is a critical part of patient management for immunotherapy. However, studies have shown that pathologist-based analysis lacks reproducibility, especially for immune cell expression. The purpose of this study was to validate reproducibility of the automated machine-based Optra image analysis for PD-L1 immunohistochemistry for both tumor cells (TCs) and immune cells. We compared conventional pathologists' scores for both tumor and immune cell positivity separately using 22c3 antibody on the Dako Link 48 platform for PD-L1 expression in non-small cell lung carcinoma. We assessed interpretation first by pathologists and second by PD-L1 image analysis scores. Lin's concordance correlation coefficients (LCCs) for each pathologist were measured to assess variability between pathologists and between pathologists and Optra automated quantitative scores in scoring both tumor and immune cells. Lin's LCCs to evaluate the correlation between pathologists for TC was 0.75 [95% confidence interval (CI), 0.64-0.81] and 0.40 (95% CI, 0.40-0.62) for immune cell scoring. Pathologists were highly concordant for tumor scoring, but not for immune cell scoring, which is similar to previously reported studies where agreement is higher in TCs than immune cells. The LCCs between conventional pathologists' read and the machine score were 0.80 (95% CI, 0.74-0.85) for TCs and 0.70 (95% CI, 0.60-0.76) for immune cell population. This is considered excellent agreement for TCs and good concordance for immune cells. The automated scoring methods showed concordance with the pathologists' average scores that were comparable to interpathologist scores. This suggests promise for Optra automated assessment of PD-L1 in non-small cell lung cancer.

An international multicenter study to evaluate reproducibility of automated scoring for assessment of Ki67 in breast cancer.

The nuclear proliferation biomarker Ki67 has potential prognostic, predictive, and monitoring roles in breast cancer. Unacceptable between-laboratory variability has limited its clinical value. The International Ki67 in Breast Cancer Working Group investigated whether Ki67 immunohistochemistry can be analytically validated and standardized across laboratories using automated machine-based scoring. Sets of pre-stained core-cut biopsy sections of 30 breast tumors were circulated to 14 laboratories for scanning and automated assessment of the average and maximum percentage of tumor cells positive for Ki67. Seven unique scanners and 10 software platforms were involved in this study. Pre-specified analyses included evaluation of reproducibility between all laboratories (primary) as well as among those using scanners from a single vendor (secondary). The primary reproducibility metric was intraclass correlation coefficient between laboratories, with success considered to be intraclass correlation coefficient >0.80. Intraclass correlation coefficient for automated average scores across 16 operators was 0.83 (95% credible interval: 0.73-0.91) and intraclass correlation coefficient for maximum scores across 10 operators was 0.63 (95% credible interval: 0.44-0.80). For the laboratories using scanners from a single vendor (8 score sets), intraclass correlation coefficient for average automated scores was 0.89 (95% credible interval: 0.81-0.96), which was similar to the intraclass correlation coefficient of 0.87 (95% credible interval: 0.81-0.93) achieved using these same slides in a prior visual-reading reproducibility study. Automated machine assessment of average Ki67 has the potential to achieve between-laboratory reproducibility similar to that for a rigorously standardized pathologist-based visual assessment of Ki67. The observed intraclass correlation coefficient was worse for maximum compared to average scoring methods, suggesting that maximum score methods may be suboptimal for consistent measurement of proliferation. Automated average scoring methods show promise for assessment of Ki67 scoring, but requires further standardization and subsequent clinical validation.

An assessment of neuronal calcium sensor-1 and response to neoadjuvant chemotherapy in breast cancer patients.

Neuronal calcium sensor-1 (NCS-1) has been identified as a binding partner of the taxane, paclitaxel. Our previous study showed that overexpression of NCS-1 increased the efficacy of paclitaxel in vitro, but was associated with poor clinical outcome. Here, we determine if NCS-1 expression is associated with pathological complete response (pCR) to taxane-based neoadjuvant chemotherapy in 105 pre-treatment breast cancer biopsies. Elevated expression of NCS-1 was found to be positively associated with pCR. These results suggest that NCS-1 may be a predictive biomarker for response to taxane-based neoadjuvant chemotherapy in breast cancer.