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Objective: To determine the impact of not keeping the collecting device in liquid-based cytology. Loss of material was computed from a pair of subsamples from the same cervical scrape. One subsample was obtained by rinsing the collecting device in one vial and the other by discarding it in another vial. Homogeneity of endocervical component was assessed between subsamples.Materials and Methods: Loss of material was analyzed with a two-way analysis of variance whose two factors were G (five gynecologists) and R (number of rinsing rotations in the first vial). Endocervical clusters were counted on slides prepared from all subsamples.Results: Globally, 37% of cellular material is lost when the collecting device is discarded. Loss of material is different among gynecologists. The more intense the rinsing process, the less the loss, but the latter is never zero and is poorly predictable. The discarded subsample often contains a greater amount of endocervical clusters.Conclusions: Discarding collecting device in liquid-based cytology reproduces one of the flaws of the conventional smear technique. Losing cellular material may have an impact on cervical cancer detection, but this still has to be evaluated with further investigations. [ABSTRACT FROM AUTHOR]

Since 2014, programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) checkpoint inhibitors have been approved by various regulatory agencies for the treatment of multiple cancers including melanoma, lung cancer, urothelial carcinoma, renal cell carcinoma, head and neck cancer, classical Hodgkin lymphoma, colorectal cancer, gastroesophageal cancer, hepatocellular cancer, and other solid tumors. Of these approved drug/disease combinations, a subset also has regulatory agency-approved, commercially available companion/complementary diagnostic assays that were clinically validated using data from their corresponding clinical trials. The objective of this document is to provide evidence-based guidance to assist clinical laboratories in establishing fit-for-purpose PD-L1 biomarker assays that can accurately identify patients with specific tumor types who may respond to specific approved immuno-oncology therapies targeting the PD-1/PD-L1 checkpoint. These recommendations are issued as 38 Guideline Statements that address (i) assay development for surgical pathology and cytopathology specimens, (ii) reporting elements, and (iii) quality assurance (including validation/verification, internal quality assurance, and external quality assurance). The intent of this work is to provide recommendations that are relevant to any tumor type, are universally applicable and can be implemented by any clinical immunohistochemistry laboratory performing predictive PD-L1 immunohistochemistry testing.

Pembrolizumab is an FDA-approved immune-checkpoint (IC) inhibitor that targets programmed cell death protein PD-1, and recent phase III trials have demonstrated its superiority over chemotherapy in the treatment of patients with advanced non-small cell lung cancer (NSCLC). Eligibility for treatment with Pembrolizumab is based on demonstration of PD-L1 expression on tumoral cells using the approved companion test 22C3 PharmDx (Dako). Access to the drug depends on a tumor proportion score (TPS) expressing the PD-L1 protein above predetermined cutoffs. The scoring interpretation guide requires a minimum of 100 viable cells to be considered adequate for evaluation. Recent studies have questioned the adequacy of the sampling process when small biopsies are utilized. To further explore this concern, the viable tumor area of 426 consecutive NSCLC biopsies and surgical excisions submitted for PD-L1 assessment was measured and recorded with corresponding PD-L1 expression. About 14.6% of all biopsies measured <2 mm creating 2 groups (<2 mm and ≥2 mm) whose PD-L1 categories distribution [negative (<1%), low expressor (≥1% and <50%), and positive (≥50%)] were compared. Results were significantly different between both groups (χ test; P=0.0012). To help understand this difference, 1,407,000 in silico simulated biopsies of various sizes were performed on 201 numerical tumors created from digitalized full sections and analyzed. Not only the same results shown in actual biopsies were reproduced, but the model calculated that up to 35% of very small biopsies were misclassified including a mixture of false negative and false positive results. The percentage decreased to 10% with a threshold of 5 mm. In era of precision medicine, appropriate sampling is more than ever critical to achieve accurate assessment of the NSCLC PD-L1. Ignored in most clinical trials, recording of biopsy size would permit refining data analysis and increase predictive accuracy of current and future biomarkers.

A new automated MYC IHC classifier based on bivariate logistic regression is presented. The predictor relies on image analysis developed with the open-source ImageJ platform. From a histologic section immunostained for MYC protein, 2 dimensionless quantitative variables are extracted: (a) relative distance between nuclei positive for MYC IHC based on euclidean minimum spanning tree graph and (b) coefficient of variation of the MYC IHC stain intensity among MYC IHC-positive nuclei. Distance between positive nuclei is suggested to inversely correlate MYC gene rearrangement status, whereas coefficient of variation is suggested to inversely correlate physiological regulation of MYC protein expression. The bivariate classifier was compared with 2 other MYC IHC classifiers (based on percentage of MYC IHC positive nuclei), all tested on 113 lymphomas including mostly diffuse large B-cell lymphomas with known MYC fluorescent in situ hybridization (FISH) status. The bivariate classifier strongly outperformed the "percentage of MYC IHC-positive nuclei" methods to predict MYC+ FISH status with 100% sensitivity (95% confidence interval, 94-100) associated with 80% specificity. The test is rapidly performed and might at a minimum provide primary IHC screening for MYC gene rearrangement status in diffuse large B-cell lymphomas. Furthermore, as this bivariate classifier actually predicts "permanent overexpressed MYC protein status," it might identify nontranslocation-related chromosomal anomalies missed by FISH.

There is a pressing need for an objective decision tool to guide therapy for breast cancer patients that are estrogen receptor positive and HER2/neu negative. This subset of patients contains a mixture of luminal A and B tumors with good and bad outcomes, respectively. The 2 main current tools are on the basis of immunohistochemistry (IHC) or gene expression, both of which rely on the expression of distinct molecular groups that reflect hormone receptors, HER2/neu status, and most importantly, proliferation. Despite the success of a proprietary molecular test, definitive superiority of any method has not yet been demonstrated. Ki67 IHC scoring assessments have been shown to be poorly reproducible, whereas molecular testing is costly with a longer turnaround time. This work proposes an objective Ki67 index using image analysis that addresses the existing methodological issues of Ki67 quantitation using IHC on paraffin-embedded tissue. Intrinsic bias related to numerical assessment performed on IHC is discussed as well as the sampling issue related to the "peel effect" of tiny objects within a thin section. A new nonbiased stereological parameter (VV) based on the Cavalieri method is suggested for use on a double-stained Ki67/cytokeratin IHC slide. The assessment is performed with open-source ImageJ software with interobserver concordance between 3 pathologists being high at 93.5%. Furthermore, VV was found to be a superior method to predict an outcome in a small subset of breast cancer patients when compared with other image analysis methods being used to determine the Ki67 labeling index. Calibration methodology is also discussed to further this IHC approach.

We investigate the association between phosphorylated histone H3 (PhH3) and Oncotype DX recurrence score (RS). All invasive breast carcinoma with RS results from our city between 2007 and 2010 (n=47) were reviewed. Whole-tumor sections were stained for PhH3. Mitotic and PhH3 counts were performed and clinical charts reviewed. PhH3 correlated well with RS (r=0.69, P<0.001). Other correlations were: PhH3 versus mitotic count (r=0.87, P<0.001), PhH3 versus mitotic score (r=0.71, P<0.001), PhH3 versus modified Bloom-Richardson-Elston (MBR) grade (r=0.65, P<0.001), RS versus mitotic count (r=0.62, P<0.001), RS versus mitotic score (r=0.44, P=0.002), and RS versus MBR grade (r=0.49, P=0.001). Significant correlation between PhH3 and RS remained after controlling for mitotic count (r=0.39, P=0.007), mitotic score (r=0.60, P<0.001), MBR grade (r=0.56, P<0.001), and all 3 (r=0.37, P=0.014) by partial correlation. Two patients died of metastasis at 12 and 38 months after diagnosis. One had intermediate RS, and 1 high RS; both were in the top-third of PhH3 count. All other patients are alive and recurrence free. Correlation between PhH3 and RS was statistically significant in our cohort, and remained significant after controlling for traditional measures of proliferation. Given that RS has an established strong relationship with prognosis and therapy responsiveness, PhH3 may thus also be an important prognostic/predictive marker in breast cancer., Competing Interests: The authors declare no conflict of interest.