Faculty Bibliography

In the 21st century, there has been a dramatic shift in the management of advanced-stage lung carcinoma, and this has coincided with an increasing use of minimally invasive tissue acquisition methods. Both have had significant downstream effects on cytology and small biopsy specimens. Current treatments require morphologic, immunohistochemical, and/or genotypical subtyping of non-small cell lung carcinoma. To meet these objectives, standardized classification of cytology and small specimen diagnoses, immunohistochemical algorithms, and predictive biomarker testing guidelines have been developed. This review provides an overview of current classification, biomarker testing, methods of small specimen acquisition and triage, clinical management strategies, and emerging technologies.

OBJECTIVES/OBJECTIVE:Recent investigations have shown strong correlations between cytology and surgical non-small cell lung carcinoma (NSCLC) specimens in programmed death-ligand 1 (PD-L1) immunohistochemical (IHC) evaluations. Our study aims to evaluate the reproducibility of PD-L1 IHC scoring in NSCLC cytology cell blocks (CBs) and to assess the impact of CB cellularity, method of sample collection, and observer subspecialty on scoring agreement. METHODS:PD-L1 IHC was performed on 54 NSCLC cytology CBs and was scored independently by seven cytopathologists (three of seven with expertise in pulmonary pathology). Three-tier scoring of negative (<1%), low positive (1%-49%), and high positive (≥50%) and interrater agreement were assessed. RESULTS:Total and majority agreement among cytopathologists was achieved in 48% and 98% of cases, respectively, with κ = 0.608 (substantial agreement; 95% confidence interval, 0.50-0.72). Cytopathologists with pulmonary pathology expertise agreed in 67% of cases (κ = 0.633, substantial agreement), whereas the remaining cytopathologists agreed in 56% of cases (κ = 0.62, substantial agreement). CB cellularity (P = .36) and sample collection type (P = .59) had no statistically significant difference between raters. CONCLUSIONS:There is substantial agreement in PD-L1 IHC scoring in cytology CB specimens among cytopathologists. Additional expertise in pulmonary pathology, sample collection type, and CB cellularity have no statistically significant impact on interobserver agreement.

Immune checkpoint inhibitor therapies have revolutionized the management of patients with non-small cell lung carcinoma (NSCLC) and have led to unprecedented improvements in response rates and survival in a subset of a patients with this fatal disease. However, the available therapies work only for a minority of patients, are associated with substantial societal cost, and may lead to significant immune-related adverse events. Therefore, patient selection must be optimized through use of relevant biomarkers. PD-L1 protein expression by immunohistochemistry is widely used today for selection of PD-1 inhibitor therapy in NSCLC patients, however this approach lacks both robust sensitivity and specificity for predicting response. Tumor mutation burden (TMB), or the number of somatic mutations derived from next generation sequencing techniques, has been widely explored as an alternative or complementary biomarker for response to immune checkpoint inhibitors. In theory, a higher TMB increases the probability of tumor neoantigen production and, therefore, likelihood of immune recognition and tumor cell killing. While TMB alone is a simplistic surrogate of this complex interplay, it is a quantitative variable that can be relatively readily measured using currently available sequencing techniques. A large number of clinical trials and retrospective analyses employing both tumor and blood-based sequencing tools have examined the performance of TMB as a predictive biomarker and in many cases show a correlation between high TMB and immune checkpoint inhibitor response rates and progression-free survival. Many challenges remain prior to implementation of TMB as a biomarker in clinical practice. These include: identification of therapies whose response is best informed by TMB status; robust definition of a predictive TMB cutpoint; acceptable sequencing panel size and design; need for robust technical and informatic rigor to generate precise and accurate TMB measurements across different laboratories. Finally, effective prediction of response to immune checkpoint inhibitor therapy will likely require integration of TMB with a host of other potential biomarkers, including tumor genomic driver alterations, tumor-immune milieu, and other features of the host immune system. This perspective piece will review the current clinical evidence for TMB as a biomarker and address the technical sequencing considerations and ongoing challenges to use of TMB in routine practice.

Background: Molecular screening for therapeutically targetable alterations is considered standard of care in the management of non-small cell lung cancer. However, most molecular assays utilize tumor tissue, which may not always be available. This has led to the development of "liquid biopsies": Plasma-based Next Generation Sequencing (NGS) tests that use circulating tumor DNA as a substrate to identify relevant targets. In this study, we sought to determine the level of agreement between the two tests as they are used in clinical practice and to investigate the utility of concurrent plasma/tissue testing.
Design(s): We identified 47 cases of lung adenocarcinoma diagnosed over the past 2 years, who received concurrent testing (within 24 weeks) with both our institution's tissue (DNA and RNA based) NGS assay and a commercial plasma-based NGS assay. The results were reviewed to establish concordance in the identification of mutations or fusions deemed clinically relevant or for which a targeted therapy was available.
Result(s): Patients in our cohort represented both new diagnoses (31 cases, 66%) and disease progression on treatment (16 cases, 34%). The majority (83%) had stage 4 disease. Tissue NGS identified clinically relevant mutations in 39 cases (83%), including in 14 (88%) of the previously treated cases. By comparison, plasma NGS identified clinically relevant mutations in 20 cases (43%, p<0.001), including 6 treated cases (38%, p=0.01). Tissue NGS identified therapeutic targets in 55% of cases and 75% of previously treated cases; while plasma NGS identified targets in 28% and 25% respectively (p<0.001 and p=0.01 respectively). All clinically relevant mutations identified by plasma NGS were also detected by tissue NGS, while plasma NGS detected only 51% those identified by tissue NGS. Discrepant cases involved hotspot mutations and actionable fusions including those in EGFR, KRAS, and ROS1 (Table 1).(Table presented)
Conclusion(s): Tissue NGS detects more clinically relevant alterations and therapeutic targets compared to plasma NGS, especially in the post-treatment setting, suggesting that tissue NGS should be the preferred method for molecular testing of lung adenocarcinoma. Additionally, all clinically relevant mutations identified by plasma NGS were also detected by tissue NGS, suggesting that tissue/plasma cotesting provides little additional benefit over tissue NGS alone. Plasma NGS can detect clinically relevant targets, and still plays an important role when tissue testing is impractical or not possible

Background: There is considerable interobserver variability in the pathological diagnosis of UIP and other ILD. The variability in finding "ground truth" presents a difficult problem during the development of deep learning platforms designed to diagnose ILD using AI. We describe the use of a smartphone application that allows for the collection of multiple opinions from sixteen pulmonary pathologists from nine countries as a novel method for finding "ground truth" for UIP diagnoses.
Design(s): Whole slide images from 14 consecutive interstitial lung disease cases were scanned by Aperio CS2 at 20x objective and sliced into multiple individual 7x7mm images, resulting in 355 JPEG image patches. These individual images were randomized and shown over the internet to 16 expert pathologists from 9 countries using the novel smartphone application, BonBon system. Expert lung pathologists were asked to classify each image into one of 8 categories: UIP/IPF; CTD/UIP; CHP/UIP; UIP/other cause; Non-UIP; "not sure"; "normal"; and "exclude". Images classified as "exclude" by any of the experts were deleted from analysis. All individual diagnostic classes selected for individual images were grouped by case, and the predominant class for each case, was used as "diagnosis". All diagnoses were analyzed using clustering analysis and Kaplan Meier statistics using JMP. Interobserver agreement was calculated by Fleiss kappa coefficient using R.
Result(s): The diagnosis of each of the 14 cases by each of the 16 pathologists showed that interobserver agreement using the 7 categories was poor (k=0.19). None of the cases were classified as CHP-UIP or UIP/others by a majority of pathologists. In order to simplify the diagnoses into more clinically relevant classes, the categories UIP/IPF, CHP-UIP, and UIP/others were grouped into UIP and Non-UIP and CTD-UIP into Non-UIP as shown in Figure 1. Clustering analysis stratified the diagnoses of each case into 3 clusters as shown in Figure 2A (k= 0.77, 0.63, and 0.03, respectively), validating cluster A and B were meaningful. Log rank test showed significant survival difference between UIP and Non-UIP groups only for cases in cluster A (P=0.017) (Fig 2B) but not for cases in cluster B (Fig 2 C). Eventually, 269 H&E images with high agreement of UIP and non-UIP group were selected as "ground truth" for AI training. (Figure presented)
Conclusion(s): Classification of image patches from WSI over APP offers a useful method to standardize UIP diagnosis and to develop diagnostic AI

Background: Spread through air spaces (STAS) has been reported to be associated with a worse prognosis in adenocarcinoma of lung. Recently it has been proposed that STAS be reported on frozen sections (FS) as an indication for more aggressive surgery (lobectomy vs sublobar resection). We undertook this study to evaluate the reliability of STAS assessment on FS compared to FS controls (FSC) and non-frozen remaining tumor (RT).
Design(s): Cases of adenocarcinoma that had FS of the tumor were identified retrospectively from two institutions. For each case, the following was recorded: Presence(+)/absence(-) of STAS on FS, FSC, and RT; and % of tumor patterns: Lepidic(L), acinar(A), papillary(P), micropapillary(M), solid(S). Grades were defined as follows: G1=L predominant with A/P G2=A/P predominant with <20% M/S G3=M/S predominant or >=20% M/S Cross-tabulations and Spearman's correlations (rs) were performed in SPSS (see Table). rs 0.3-<0.5 = low correlation.
Result(s): 165 cases were found. In 2 cases the tumor was only present on FS/FSC slides. STAS+ was present on FS in 47/165(28%), of which 28/47(60%) had STAS+ on FSC (rs=0.39) and 22/46(48%) had STAS+ on RT (rs=0.34) (1 tumor was only present on FS/FSC). Of the 40 STAS+ cases on RT, 18/40(45%) did not have STAS (STAS-) on FS (rs=0.34). 118/165 of cases were STAS- on FS; of these, 18/117(15%) were STAS+ on RT (rs=0.34) (1 tumor was only present on FS/FSC). Fig 1. Of the 47 cases with STAS+ on FS, 4(15%) were G1, 15(32%) were G2, and 28(60%) were G3 (rs =0.30). Of the 15 G2 cases with STAS+ on FS, 7 had 10% to <20% high grade pattern (M/S). Of the 28 G3 cases with STAS+ on FS, 13 had >= 30% high grade pattern. Of the 40 cases with STAS+ on RT, 1(2.5%) case was G1, 7(18%) cases were G2, and 32(80%) cases were G3 (rs=0.46). Fig 2. (Table presented)
Conclusion(s): The correlations among FS, FSC, and RT are low. FS STAS+ cases remain STAS+ only in 60% of FSC and 48% of RT. STAS shows higher correlation with grade on RT than it does on FS. These results show a lack of reliability in the assessment of STAS on FS, and do not support the proposal of reporting STAS in FS to make intraoperative clinical decisions, as doing so may subject patients to unnecessarily aggressive surgery

Background: When the first diagnosis of a well-differentiated neuroendocrine neoplasm (WDNEN) is made on a biopsy, crush artifact may impede mitotic counting, and the Ki-67 proliferative index (KPI) plays a more important role in grading. Few studies have examined the reliability of KPI in the grading of metastatic (met) WDNEN.
Design(s): Cases were retrieved from 2008-19. For each primary (1degree) and met, a 40x hotspot image of a Ki-67 stained slide was taken. KPI was analyzed by the ImmunoRatio Plugin using ImageJ software. All were validated by independent manual counting. In 1 case, crush artifact precluded use of ImageJ. If multiple mets were present, the largest was selected. Cytology and cases with fewer than 100 cells were omitted. Tumors were graded as G1(KPI<3%), G2(KPI 3-20%), or G3(KPI>20%). Grade and KPI were compared between each 1degree and met.
Result(s): 67 cases, including 38 mets from 29 1degree WDNEN, were evaluated. There were 12, 2, 2, 1, 17, and 4 mets from lung, thymus, middle ear, pancreas, small bowel, & colon respectively. The greatest variations in KPI from 1degree to met were seen in lung compared to all other sites. In 24/38(63%) of all mets, the grade was the same as 1degree. In 14/38(37%) of all mets, the grade was different: 4/14(29%) were lower while 10/14(71%) were higher than 1degree. In mets from lung, 2 had lower, 6 had the same, & 4 had higher grade. In mets from middle ear, the grades increased. In mets from small bowel 2 had lower, 12 had the same, and 3 had higher grade. In mets from colon 3 had the same and 1 had higher grade. And in mets from thymus & pancreas, the grades remained the same. See Fig 1. 3 mets were diagnosed before 1degree (2 days to 2 months). Mets with higher grade than 1degree tended to have longer time interval between 1degree and met, but this was not significant at the 95% confidence level (Kruskal-Wallis test, p=0.08). 28 mets were regional and 10 were distant. There was no correlation between met site and grade change (Person Chi-square, p=0.33). Also see Table 1. (Table presented)
Conclusion(s): Our study showed that in most met WDNEN (63%), the grade remained the same as the 1degree. The grade was higher in 10/38(26%) and lower in 4/38(11%). There was a trend toward higher grade in mets that occurred at a longer time interval after the 1degree. Fig 2 shows a potential diagnostic pitfall when the met shows much higher KPI than 1degree. In conclusion, if a met WDNEN is suspected as a firsttime diagnosis, KPI must be used cautiously for classification of WDNEN since over/under-grading may occur

The outbreak of the novel coronavirus disease 2019 (COVID-19) and consequent social distancing practices have disrupted essential clinical research functions worldwide. Ironically, this coincides with an immediate need for research to comprehend the biology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the pathology of COVID-19. As the global crisis has already led to over 15,000 deaths out of 175,000 confirmed cases in New York City and Nassau County, NY alone, it is increasingly urgent to collect patient biospecimens linked to active clinical follow up. However, building a COVID-19 biorepository amidst the active pandemic is a complex and delicate task. To help facilitate rapid, robust, and regulated research on this novel virus, we report on the successful model implemented by New York University Langone Health (NYULH) within days of outbreak in the most challenging hot spot of infection globally. Using an amended institutional biobanking protocol, these efforts led to accrual of 11,120 patients presenting for SARS-CoV-2 testing, 4267 (38.4%) of whom tested positive for COVID-19. The recently reported genomic characterization of SARS-CoV-2 in the New York City Region, which is a crucial development in tracing sources of infection and asymptomatic spread of the novel virus, is the first outcome of this effort. While this growing resource actively supports studies of the New York outbreak in real time, a worldwide effort is necessary to build a collective arsenal of research tools to deal with the global crisis now, and to exploit the virus's biology for translational innovation that outlasts humanity's current dilemma.

Cytology serves a fundamental role in the evaluation of the lower respiratory tract. Cytological specimens are often the first diagnostic attempt for the evaluation of radiographic alterations. The categorization of the pathological process as infectious, inflammatory or neoplastic is critical in guiding further clinical management of the affected patient. Therefore it is imperative that cytopathologists use a standardized approach to sample handling and reporting in order to establish clear communication with the treating physician. The Papanicolaou Society of cytopathology has been an active leader in this field and has proposed several guidelines for sampling, handling, and reporting of lower respiratory tract cytology. These guidelines have been updated to incorporate new emerging concepts and technologies in the field. Respiratory medicine is a fast growing area with constant new challenges, thus requiring an ever demanding adaptation from cytopathologists and cytology specific guidelines.

Cardiac amyloid A (AA) amyloidosis is rare. We present the case of a 72-year-old woman with obstructive hypertrophic cardiomyopathy (HCM) and biopsy-proven renal AA amyloidosis whose dyspnea and exercise intolerance had worsened over the previous year. Her AA amyloidosis was suspected to be secondary to chronic diverticulitis for which she had undergone hemicolectomy and sigmoidectomy 3 years prior. Echocardiographic findings were consistent with worsening left ventricular outflow tract obstruction at rest. Cardiac magnetic resonance imaging revealed patchy areas of midwall late gadolinium enhancement. Right ventricular endomyocardial biopsy did not reveal amyloid deposition, and cardiac technetium-99m pyrophosphate scintigraphy did not suggest transthyretin amyloidosis. The patient underwent septal myectomy with resection of an accessory papillary muscle. Pathological examination of the myectomy specimen was consistent with HCM. In addition, there was a thick layer of diffuse endocardial and vascular amyloid deposition that was identified as AA type by laser-microdissection with liquid chromatography-coupled tandem-mass spectrometry. This case report highlights the presence of 2 distinct disease processes occurring simultaneously and the importance of tissue diagnosis of AA amyloidosis, a condition that is not commonly associated with HCM.