Faculty Bibliography

Currently there is no established guidance on how to process and evaluate resected lung cancer specimens following neoadjuvant therapy in the setting of clinical trials and clinical practice. There is also a lack of precise definitions on the degree of pathologic response, including major pathologic response (MPR) or complete pathologic response (CPR). In other cancers such as osteosarcoma, colorectal, breast and esophageal carcinomas, there have been multiple studies investigating pathologic assessment of the effects of neoadjuvant therapy including some detailed recommendations on how to handle these specimens. A comprehensive mapping approach to gross and histologic processing of osteosarcomas following induction therapy has been used for over 40 years. The purpose of this article is to outline detailed recommendations on how to process lung cancer resection specimens and to define pathologic response including MPR and CPR following neoadjuvant therapy. A standardized approach is recommended to assess the percentages of: 1) viable tumor, 2) necrosis and 3) stroma (including inflammation and fibrosis) with a total adding up to 100%. This is recommended for all systemic therapies including chemotherapy, chemoradiation, molecular targeted therapy, immunotherapy or any future novel therapies yet to be discovered whether administered alone or in combination. Specific issues may differ for certain therapies such as immunotherapy, but the grossing process should be similar and the histologic evaluation should contain these basic elements. Standard pathologic response assessment should allow for comparisons between different therapies and correlations with disease free survival and overall survival in ongoing and future trials. The International Association for the Study of Lung Cancer (IASLC) has an effort to collect such data from existing and future clinical trials. These recommendations are intended as guidance for clinical trials, although it is hoped they can be viewed as suggestion for good clinical practice outside of clinical trials, to improve consistency of pathologic assessment of treatment response.

The recent development of immune checkpoint inhibitors (ICI) has led to promising advances in the treatment of non-small cell and small cell lung cancer patients with advanced or metastatic disease. Most of ICI target the PD-1/PD-L1 axis with the aim of restoring anti-tumor immunity. Multiple clinical trials for ICI have examined a predictive value of PD-L1 protein expression in tumor cells and/or tumor-infiltrating immune cells by immunohistochemistry (IHC), for which different assays with specific IHC platforms were applied. Of those, some PD-L1 IHC assays have been validated for the prescription of the corresponding agent for first- or second-line treatment. However, not all laboratories are equipped with the dedicated platforms and many laboratories have set up in-house or laboratory developed tests, which are more affordable than generally expensive clinical trial-validated assays. Although PD-L1 IHC test is now deployed in the most pathology laboratories, its appropriate implementation and interpretation are critical as a predictive biomarker and can be challenging due to the multiple antibody clones and platforms or assays available and given the typically small size of samples provided. As many articles have been published since the issue of the IASLC Atlas of PD-L1 immunohistochemistry testing in lung cancer, this review by the IASLC pathology committee provides updates on the indications of ICI for lung cancer in 2019, and discusses important considerations on pre-analytical, analytical and post-analytical aspects of PD-L1 IHC testing, including specimen type, validation of assays, external quality assurance and training.

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.

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: 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

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: 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

INTRODUCTION/BACKGROUND:Molecular and immunologic breakthroughs are transforming the management of thoracic cancer, although advances have not been as marked for malignant pleural mesothelioma (MPM) where pathologic diagnosis has been essentially limited to three histologic subtypes. METHODS:A multidisciplinary group (pathologists, molecular biologists, surgeons, radiologists and oncologists), sponsored by EURACAN/IASLC met in 2018, to critically review the current classification. RESULTS:Recommendations include: 1) classification should be updated to include architectural patterns, and stromal and cytologic features that refine prognostication 2) subject to data accrual, malignant mesothelioma in situ could be an additional category, 3) grading of epithelioid MPMs should be routinely undertaken, 4) favorable/unfavorable histologic characteristics should be routinely reported, 5) clinically relevant molecular data (PD-L1, BAP1, CDKN2A) should be incorporated into reports, if undertaken, 6) other molecular data should be accrued as part of future trials 7) resection specimens (i.e. extended pleurectomy/decortication and extrapleural pneumonectomy) should be pathologically staged with smaller specimens being clinically staged, 8) ideally, at least 3 separate areas should be sampled from the pleural cavity, including areas of interest identified on pre-surgical imaging, 9) image-acquisition protocols/imaging terminology should be standardized to aid research/refine clinical staging, 10) multidisciplinary tumor boards should include pathologists to ensure appropriate treatment options are considered, 11) all histologic subtypes should be considered potential candidates for chemotherapy, 12) patients with sarcomatoid or biphasic mesothelioma should not be excluded from first line clinical trials unless there is a compelling reason, 13) tumor subtyping should be further assessed in relation to duration of response to immunotherapy, 14) systematic screening of all patients for germline mutations is not recommended, in the absence of a family history suspicious for BAP1 syndrome. CONCLUSION/CONCLUSIONS:These multidisciplinary recommendations for pathology classification and application will allow more informative pathologic reporting and potential risk stratification, to support clinical practice, research investigation and clinical trials.