PKCε promotes oncogenic functions of ATF2 in the nucleus while blocking its apoptotic function at mitochondria.

The transcription factor ATF2 elicits oncogenic activities in melanoma and tumor suppressor activities in nonmalignant skin cancer. Here, we identify that ATF2 tumor suppressor function is determined by its ability to localize at the mitochondria, where it alters membrane permeability following genotoxic stress. The ability of ATF2 to reach the mitochondria is determined by PKCε, which directs ATF2 nuclear localization. Genotoxic stress attenuates PKCε effect on ATF2; enables ATF2 nuclear export and localization at the mitochondria, where it perturbs the HK1-VDAC1 complex; increases mitochondrial permeability; and promotes apoptosis. Significantly, high levels of PKCε, as seen in melanoma cells, block ATF2 nuclear export and function at the mitochondria, thereby attenuating apoptosis following exposure to genotoxic stress. In melanoma tumor samples, high PKCε levels associate with poor prognosis. Overall, our findings provide the framework for understanding how subcellular localization enables ATF2 oncogenic or tumor suppressor functions.

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.

Correlation of HER2 Protein Level With mRNA Level Quantified by RNAscope in Breast Cancer.

Trastuzumab deruxtecan (T-DXd) has been approved by the US Food and Drug Administration (FDA) to treat patients with metastatic HER2-positive and HER2-low breast cancer, and clinical trials are examining its efficacy against early-stage breast cancer. Current HER2 immunohistochemical (IHC) assays are suboptimal in evaluating HER2-low breast cancers and identifying which patients would benefit from T-DXd. HER2 expression in 526 breast cancer tissue microarray (TMA) cores was measured using the FDA-approved PATHWAY and HercepTest IHC assays, and the corresponding RNA levels were evaluated by RNAscope. HER2 protein levels by regression analysis using a quantitative immunofluorescence score against cell line arrays with known HER2 protein levels determined by mass spectrometry were available in 48 of the cores. RNAscope was also performed in 32 metastatic biopsies from 23 patients who were subsequently treated with T-DXd, and the results were correlated with response rate. HER2 RNA levels by RNAscope strongly correlated with HER2 protein levels (P < .0001) and with HER2 IHC H-scores from the PATHWAY and HercepTest assays (P < .0001). However, neither protein levels nor RNA levels significantly differed between cases scored 0, ultralow, and 1+ by PATHWAY and HercepTest. The RNA levels were significantly higher (P = .030) in responders (6.4 ± 8.2 dots/cell, n = 12) than those in nonresponders (2.6 ± 2.2, n = 20) to T-DXd. RNAscope is a simple assay that can be objectively quantified and is a promising alternative to current IHC assays in evaluating HER2 expression in breast cancers, especially HER2-low cases, and may identify patients who would benefit from T-DXd.

Tissue Age Affects Antigenicity and Scoring for the 22C3 Immunohistochemistry Companion Diagnostic Test.

Programmed death-ligand 1 (PD-L1) antibody 22C3 is the approved companion diagnostic immunohistochemistry test for treatment with pembrolizumab and cemiplimab in multiple cancer types. The 22C3 and 28-8 antibodies target the extracellular domain (ECD) of PD-L1, which is known to contain N-glycosylation sites. We hypothesize that antigenicity could be affected by the degradation of the glycan part of the epitope and thus change the scoring of the assay over time. Here, we test samples over time and assess the effects of time and deglycosylation on PD-L1 signal by comparing an antibody with an ECD antigen to an antibody with an intracellular domain (ICD) antigen. Ten whole-tissue sections of non-small-cell lung cancer (NSCLC) from 2018 were selected for testing. Fresh-cut serial sections for each case were stained on DAKO Link48 for 22C3 according to the label. In parallel, a previously described laboratory-developed test using E1L3N (an ICD antibody) was performed on the Leica BondRX. Tumor proportion scores for 22C3 and E1L3N were read by a pathologist and compared to the previous clinical diagnoses. To determine the effect using a quantitative approach, a tissue microarray (TMA) cohort with 90 NSCLC cases was similarly assessed. Finally, to determine whether the possible effect of epitope glycosylation, antibodies were tested before and after enzymatic deglycosylation of specimens. We found that 6 of 7 archival positive samples showed a significant reduction in positive staining with 22C3 compared to the original diagnostic sample assessed 3 years earlier. In an older archival TMA cohort, a quantitative significant difference in signal intensity was noted when staining with 22C3 was compared to E1L3N. This loss of signal was not noted in the fresh cell line TMA consistent with a time-dependent degradation of staining. Finally, quantitative assessment of the fresh TMA showed a significant loss of signal after a deglycosylation procedure when stained with 22C3, which was not seen when stained with E1L3N. We believe that these data show that the glycan part of the 22C3 epitope is not stable over time, and that this issue should be considered when assessing archival tissue for diagnostic or research purposes.

Multiplex Immunohistochemistry and Immunofluorescence: A Practical Update for Pathologists.

Our understanding of the biology and management of human disease has undergone a remarkable evolution in recent decades. Improved understanding of the roles of complex immune populations in the tumor microenvironment has advanced our knowledge of antitumor immunity, and immunotherapy has radically improved outcomes for many advanced cancers. Digital pathology has unlocked new possibilities for the assessment and discovery of the tumor microenvironment, such as quantitative and spatial image analysis. Despite these advances, tissue-based evaluations for diagnosis and prognosis continue to rely on traditional practices, such as hematoxylin and eosin staining, supplemented by the assessment of single biomarkers largely using chromogenic immunohistochemistry (IHC). Such approaches are poorly suited to complex quantitative analyses and the simultaneous evaluation of multiple biomarkers. Thus, multiplex staining techniques have significant potential to improve diagnostic practice and immuno-oncology research. The different approaches to achieve multiplexed IHC and immunofluorescence are described in this study. Alternatives to multiplex immunofluorescence/IHC include epitope-based tissue mass spectrometry and digital spatial profiling (DSP), which require specialized platforms not available to most clinical laboratories. Virtual multiplexing, which involves digitally coregistering singleplex IHC stains performed on serial sections, is another alternative to multiplex staining. Regardless of the approach, analysis of multiplexed stains sequentially or simultaneously will benefit from standardized protocols and digital pathology workflows. Although this is a complex and rapidly advancing field, multiplex staining is now technically feasible for most clinical laboratories and may soon be leveraged for routine diagnostic use. This review provides an update on the current state of the art for tissue multiplexing, including the capabilities and limitations of different techniques, with an emphasis on potential relevance to clinical diagnostic practice.

Multi-Institutional Study of Pathologist Reading of the Programmed Cell Death Ligand-1 Combined Positive Score Immunohistochemistry Assay for Gastric or Gastroesophageal Junction Cancer.

The assessment of the expression of programmed cell death ligand-1 (PD-L1) using immunohistochemistry (IHC) has been controversial since its introduction. The methods of assessment and the range of assays and platforms contribute to confusion. Perhaps the most challenging aspect of PD-L1 IHC is the combined positive score (CPS) method of interpretation of IHC results. Although the CPS method is prescribed for more indications than any other PD-L1 scoring system, its reproducibility has never been rigorously assessed. In this study, we collected a series of 108 gastric or gastroesophageal junction cancer cases, stained them using the Food and Drug Administration-approved 22C3 assay, scanned them, and then circulated them to 14 pathologists at 13 institutions for the assessment of interpretative concordance for the CPS system. We found that higher cut points (10 or 20) performed better than a CPS of <1 or >1. We used the Observers Needed to Evaluate Subjective Tests algorithm to assess how the CPS system might perform in the real-world setting and found that the cut points of <1 or >1 showed an overall percent agreement of only 30% among the pathologist raters, with a plateau occurring at 8 raters. The raters performed better at higher cut points. However, the best cut point of <20 versus that of >20 was still disappointing, with a plateau at an overall percent agreement of 70% (at 7 raters). Although there is no ground truth for CPS, we compared the score with quantitative messenger RNA measurement and showed no relationship between the score (at any cut point) and messenger RNA amount. In summary, we showed that CPS shows high subjective variability among pathologist readers and is likely to perform poorly in the real-world setting. This system may be the root cause of the poor specificity and relatively low predictive value of IHC companion diagnostic tests for PD-1 axis therapies that use the CPS system.

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.

Spatial characterization and quantification of CD40 expression across cancer types.

BACKGROUND: CD40, a TNF receptor family member, is expressed by a variety of immune cells and is involved in the activation of both adaptive and innate immune responses. Here, we used quantitative immunofluorescence (QIF) to evaluate CD40 expression on the tumor epithelium of solid tumors in large patient cohorts of lung, ovarian, and pancreatic cancers. METHODS: Tissue samples from nine different solid tumors (bladder, breast, colon, gastric, head and neck, non-small cell lung cancer (NSCLC), ovarian, pancreatic and renal cell carcinoma), constructed in tissue microarray format, were initially assessed for CD40 expression by QIF. CD40 expression was then evaluated on the large available patient cohorts for three of the tumor types demonstrating high CD40 positivity rate; NSCLC, ovarian and pancreatic cancer. The prognostic impact of CD40 expression on tumor cells was also investigated. RESULTS: CD40 expression on tumor cells was found to be common, with 80% of the NSCLC population, 40% of the ovarian cancer population, and 68% of the pancreatic adenocarcinoma population displaying some degree of CD40 expression on cancer cells. All of three of these cancer types displayed considerable intra-tumoral heterogeneity of CD40 expression, as well as partial correlation between expression of CD40 on tumor cells and on surrounding stromal cells. CD40 was not found to be prognostic for overall survival in NSCLC, ovarian cancer, or pancreatic adenocarcinoma. CONCLUSIONS: The high percentage of tumor cells expressing CD40 in each of these solid tumors should be considered in the development of therapeutic agents designed to target CD40.

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 measurement of HER2 expression to subclassify ERBB2 unamplified breast cancer.

The efficacy of the antibody drug conjugate (ADC) Trastuzumab deruxtecan (T-DXd) in HER2 low breast cancer patients suggests that the historical/conventional assays for HER2 may need revision for optimal patient care. Specifically, the conventional assay is designed to distinguish amplified HER2 from unamplified cases but is not sensitive enough to stratify the lower ranges of HER2 expression. Here we determine the optimal dynamic range for unamplified HER2 detection in breast cancer and then redesign an assay to increase the resolution of the assay to stratify HER2 expression in unamplified cases. We used the AQUA™ method of quantitative immunofluorescence to test a range of antibody concentrations to maximize the sensitivity within the lower range of HER2 expression. Then, using a cell line microarray with HER2 protein measured by mass spectrometry we determined the amount of HER2 protein in units of attomols/mm2. Then by calculation of the limits of detection, quantification, and linearity of this assay we determined that low HER2 range expression in unamplified cell lines is between 2 and 20 attomol/mm2. Finally, application of this assay to a serial collection of 364 breast cancer cases from Yale shows 67% of the population has HER2 expression above the limit of quantification and below the levels seen in HER2 amplified breast cancer. In the future, this assay could be used to determine the levels of HER2 required for response to T-DXd or similar HER2 conjugated ADCs.

Development of an immunohistochemical assay for Siglec-15.

Siglec-15, a member of sialic-acid binding immunoglobulin type lectins, is normally expressed by myeloid cells and upregulated in some human cancers and represents a promising new target for immunotherapy. While PD-L1 blockade is an important strategy for immunotherapy, its effectiveness is limited. The expression of Siglec-15 has been demonstrated to be predominantly mutually exclusive to PD-L1 in certain cancer histologies. Thus, there is significant opportunity for Siglec-15 as an immunotherapeutic target for patients that do not respond to PD-1/PD-L1 inhibition. The aim of this study was to prospectively develop an immunohistochemical (IHC) assay for Siglec-15 to be used as a companion diagnostic for future clinical trials. Here, we create and validate an IHC assay with a novel recombinant antibody to the cytoplasmic domain of Siglec-15. To find an enriched target, this antibody was first used in a quantitative fluorescence (QIF) assay to screen a broad range of tumor histologies to determine tumor types where Siglec-15 demonstrated high expression. Based on this and previous data, we focused on development of a chromogenic IHC assay for lung cancer. Then we developed a scoring system for this assay that has high concordance amongst pathologist readers. We then use this chromogenic IHC assay to test the expression of Siglec-15 in two cohorts of NSCLC. We found that this assay shows a higher level of staining in both tumor and immune cells compared to previous QIF assays utilizing a polyclonal antibody. However, similar to that study, only a small percentage of positive Siglec-15 cases showed high expression for PD-L1. This validated assay for Siglec-15 expression may support development of a companion diagnostic assay to enrich for patients expressing the Siglec-15 target for therapy.

Deep learning trained on hematoxylin and eosin tumor region of Interest predicts HER2 status and trastuzumab treatment response in HER2+ breast cancer.

The current standard of care for many patients with HER2-positive breast cancer is neoadjuvant chemotherapy in combination with anti-HER2 agents, based on HER2 amplification as detected by in situ hybridization (ISH) or protein immunohistochemistry (IHC). However, hematoxylin & eosin (H&E) tumor stains are more commonly available, and accurate prediction of HER2 status and anti-HER2 treatment response from H&E would reduce costs and increase the speed of treatment selection. Computational algorithms for H&E have been effective in predicting a variety of cancer features and clinical outcomes, including moderate success in predicting HER2 status. In this work, we present a novel convolutional neural network (CNN) approach able to predict HER2 status with increased accuracy over prior methods. We trained a CNN classifier on 188 H&E whole slide images (WSIs) manually annotated for tumor Regions of interest (ROIs) by our pathology team. Our classifier achieved an area under the curve (AUC) of 0.90 in cross-validation of slide-level HER2 status and 0.81 on an independent TCGA test set. Within slides, we observed strong agreement between pathologist annotated ROIs and blinded computational predictions of tumor regions / HER2 status. Moreover, we trained our classifier on pre-treatment samples from 187 HER2+ patients that subsequently received trastuzumab therapy. Our classifier achieved an AUC of 0.80 in a five-fold cross validation. Our work provides an H&E-based algorithm that can predict HER2 status and trastuzumab response in breast cancer at an accuracy that may benefit clinical evaluations.

Systematically higher Ki67 scores on core biopsy samples compared to corresponding resection specimen in breast cancer: a multi-operator and multi-institutional study.

Ki67 has potential clinical importance in breast cancer but has yet to see broad acceptance due to inter-laboratory variability. Here we tested an open source and calibrated automated digital image analysis (DIA) platform to: (i) investigate the comparability of Ki67 measurement across corresponding core biopsy and resection specimen cases, and (ii) assess section to section differences in Ki67 scoring. Two sets of 60 previously stained slides containing 30 core-cut biopsy and 30 corresponding resection specimens from 30 estrogen receptor-positive breast cancer patients were sent to 17 participating labs for automated assessment of average Ki67 expression. The blocks were centrally cut and immunohistochemically (IHC) stained for Ki67 (MIB-1 antibody). The QuPath platform was used to evaluate tumoral Ki67 expression. Calibration of the DIA method was performed as in published studies. A guideline for building an automated Ki67 scoring algorithm was sent to participating labs. Very high correlation and no systematic error (p = 0.08) was found between consecutive Ki67 IHC sections. Ki67 scores were higher for core biopsy slides compared to paired whole sections from resections (p ≤ 0.001; median difference: 5.31%). The systematic discrepancy between core biopsy and corresponding whole sections was likely due to pre-analytical factors (tissue handling, fixation). Therefore, Ki67 IHC should be tested on core biopsy samples to best reflect the biological status of the tumor.

Determination of the number of observers needed to evaluate a subjective test and its application in two PD-L1 studies.

In pathological studies, subjective assays, especially companion diagnostic tests, can dramatically affect treatment of cancer. Binary diagnostic test results (ie, positive vs negative) may vary between pathologists or observers who read the tumor slides. Some tests have clearly defined criteria resulting in highly concordant outcomes, even with minimal training. Other tests are more challenging. Observers may achieve poor concordance even with training. While there are many statistically rigorous methods for measuring concordance between observers, we are unaware of a method that can identify how many observers are needed to determine whether a test can reach an acceptable concordance, if at all. Here we introduce a statistical approach to the assessment of test performance when the test is read by multiple observers, as would occur in the real world. By plotting the number of observers against the estimated overall agreement proportion, we can obtain a curve that plateaus to the average observer concordance. Diagnostic tests that are well-defined and easily judged show high concordance and plateau with few interobserver comparisons. More challenging tests do not plateau until many interobserver comparisons are made, and typically reach a lower plateau or even 0. We further propose a statistical test of whether the overall agreement proportion will drop to 0 with a large number of pathologists. The proposed analytical framework can be used to evaluate the difficulty in the interpretation of pathological test criteria and platforms, and to determine how pathology-based subjective tests will perform in the real world. The method could also be used outside of pathology, where concordance of a diagnosis or decision point relies on the subjective application of multiple criteria. We apply this method in two recent PD-L1 studies to test whether the curve of overall agreement proportion will converge to 0 and determine the minimal sufficient number of observers required to estimate the concordance plateau of their reads.

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.

An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy.

Prostate cancer is a leading cause of morbidity and mortality for adult males in the US. The diagnosis of prostate carcinoma is usually made on prostate core needle biopsies obtained through a transrectal approach. These biopsies may account for a significant portion of the pathologists' workload, yet variability in the experience and expertise, as well as fatigue of the pathologist may adversely affect the reliability of cancer detection. Machine-learning algorithms are increasingly being developed as tools to aid and improve diagnostic accuracy in anatomic pathology. The Paige Prostate AI-based digital diagnostic is one such tool trained on the digital slide archive of New York's Memorial Sloan Kettering Cancer Center (MSKCC) that categorizes a prostate biopsy whole-slide image as either "Suspicious" or "Not Suspicious" for prostatic adenocarcinoma. To evaluate the performance of this program on prostate biopsies secured, processed, and independently diagnosed at an unrelated institution, we used Paige Prostate to review 1876 prostate core biopsy whole-slide images (WSIs) from our practice at Yale Medicine. Paige Prostate categorizations were compared to the pathology diagnosis originally rendered on the glass slides for each core biopsy. Discrepancies between the rendered diagnosis and categorization by Paige Prostate were each manually reviewed by pathologists with specialized genitourinary pathology expertise. Paige Prostate showed a sensitivity of 97.7% and positive predictive value of 97.9%, and a specificity of 99.3% and negative predictive value of 99.2% in identifying core biopsies with cancer in a data set derived from an independent institution. Areas for improvement were identified in Paige Prostate's handling of poor quality scans. Overall, these results demonstrate the feasibility of porting a machine-learning algorithm to an institution remote from its training set, and highlight the potential of such algorithms as a powerful workflow tool for the evaluation of prostate core biopsies in surgical pathology practices.

A new tool for technical standardization of the Ki67 immunohistochemical assay.

Ki67, a nuclear proliferation-related protein, is heavily used in anatomic pathology but has not become a companion diagnostic or a standard-of-care biomarker due to analytic variability in both assay protocols and interpretation. The International Ki67 Working Group in breast cancer has published and has ongoing efforts in the standardization of the interpretation of Ki67, but they have not yet assessed technical issues of assay production representing multiple sources of variation, including antibody clones, antibody formats, staining platforms, and operators. The goal of this work is to address these issues with a new standardization tool. We have developed a cell line microarray system in which mixes of human Karpas 299 or Jurkat cells (Ki67+) with Sf9 (Spodoptera frugiperda) (Ki67-) cells are present in incremental standardized ratios. To validate the tool, six different antibodies, including both ready-to-use and concentrate formats from six vendors, were used to measure Ki67 proliferation indices using IHC protocols for manual (bench-top) and automated platforms. The assays were performed by three different laboratories at Yale and analyzed using two image analysis software packages, including QuPath and Visiopharm. Results showed statistically significant differences in Ki67 reactivity between each antibody clone. However, subsets of Ki67 assays using three clones performed in three different labs show no significant differences. This work shows the need for analytic standardization of the Ki67 assay and provides a new tool to do so. We show here how a cell line standardization system can be used to normalize the staining variability in proliferation indices between different antibody clones in a triple negative breast cancer cohort. We believe that this cell line standardization array has the potential to improve reproducibility among Ki67 assays and laboratories, which is critical for establishing Ki67 as a standard-of-care assay.

BRCA1 Protein Expression Predicts Survival in Glioblastoma Patients from an NRG Oncology RTOG Cohort.

PURPOSE: Glioblastoma, the most common malignant brain tumor, was associated with a median survival of <1 year in the pre-temozolomide (TMZ) era. Despite advances in molecular and genetic profiling studies identifying several predictive biomarkers, none has been translated into routine clinical use. Our aim was to investigate the prognostic significance of a panel of diverse cellular molecular markers of tumor formation and growth in an annotated glioblastoma tissue microarray (TMA). METHODS AND MATERIALS: A TMA composed of archived glioblastoma tumors from patients treated with surgery, radiation, and non-TMZ chemother-apy, was provided by RTOG. RAD51, BRCA-1, phosphatase and tensin homolog tumor suppressor gene (PTEN), and miRNA-210 expression levels were assessed using quantitative in situ hybridization and automated quantitative protein analysis. The objectives of this analysis were to determine the association of each biomarker with overall survival (OS), using the Cox proportional hazard model. Event-time distributions were estimated using the Kaplan-Meier method and compared by the log-rank test. RESULTS: A cohort of 66 patients was included in this study. Among the 4 biomarkers assessed, only BRCA1 expression had a statistically significant correlation with survival. From univariate analysis, patients with low BRCA1 protein expression showed a favorable outcome for OS (p = 0.04; hazard ratio = 0.56) in comparison with high expressors, with a median survival time of 18.9 versus 4.8 months. CONCLUSIONS: BRCA1 protein expression was an important survival predictor in our cohort of glioblastoma patients. This result may imply that low BRCA1 in the tumor and the consequent low level of DNA repair cause vulnerability of the cancer cells to treatment.

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.

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.