[A new one in the lung and pleura neoplasms classification (WHO, 2021, 5th edition)]. / Novoe v Klassifikatsii novoobrazovanii legkikh i plevry (VOZ, 2021 g., 5-e izdanie).

The article contains an overview of the new WHO classification of thoracic tumors (2021). As in the previous edition of 2015, considerable attention is paid to neoplasms of the lungs and pleura. The article presents current data on molecular genetic features and morphological manifestations of a number of new lung tumors, with a detailed histological and immunohistochemical data. Thoracis undifferentiated tumor with SMARCA4 deficiency and bronchiolar adenoma are described. Emphasis is placed on the algorithms of morphological diagnostics, including a complete description of the tumor and facilitating the study in the practice of a pathologist. The main morphological criteria of mesothelial tumors of the pleura are given; describes in detail the procedure for assessing the degree of malignancy of diffuse epithelioid pleural mesothelioma and non-mucinous lung adenocarcinomas.

Classification and Detection of Mesothelioma Cancer Using Feature Selection-Enabled Machine Learning Technique.

Cancer of the mesothelium, sometimes referred to as malignant mesothelioma (MM), is an extremely uncommon form of the illness that almost always results in death. Chemotherapy, surgery, radiation therapy, and immunotherapy are all potential treatments for multiple myeloma; however, the majority of patients are identified with the disease at an advanced stage, at which time it is resistant to these therapies. After obtaining a diagnosis of advanced multiple myeloma, the average length of time that a person lives is one year after hearing this news. There is a substantial link between asbestos exposure and mesothelioma (MM). Using an approach that enables feature selection and machine learning, this article proposes a classification and detection method for mesothelioma cancer. The CFS correlation-based feature selection approach is first used in the feature selection process. It acts as a filter, selecting just the traits that are relevant to the categorization. The accuracy of the categorization model is improved as a direct consequence of this. After that, classification is carried out with the help of naive Bayes, fuzzy SVM, and the ID3 algorithm. Various metrics have been utilized during the process of measuring the effectiveness of machine learning strategies. It has been discovered that the choice of features has a substantial influence on the accuracy of the categorization.

Deep-learning based classification distinguishes sarcomatoid malignant mesotheliomas from benign spindle cell mesothelial proliferations.

Sarcomatoid mesothelioma is an aggressive malignancy that can be challenging to distinguish from benign spindle cell mesothelial proliferations based on biopsy, and this distinction is crucial to patient treatment and prognosis. A novel deep learning based classifier may be able to aid pathologists in making this critical diagnostic distinction. SpindleMesoNET was trained on cases of malignant sarcomatoid mesothelioma and benign spindle cell mesothelial proliferations. Performance was assessed through cross-validation on the training set, on an independent set of challenging cases referred for expert opinion ('referral' test set), and on an externally stained set from outside institutions ('externally stained' test set). SpindleMesoNET predicted the benign or malignant status of cases with AUC's of 0.932, 0.925, and 0.989 on the cross-validation, referral and external test sets, respectively. The accuracy of SpindleMesoNET on the referral set cases (92.5%) was comparable to the average accuracy of 3 experienced pathologists on the same slide set (91.7%). We conclude that SpindleMesoNET can accurately distinguish sarcomatoid mesothelioma from benign spindle cell mesothelial proliferations. A deep learning system of this type holds potential for future use as an ancillary test in diagnostic pathology.

Deep learning-based classification of mesothelioma improves prediction of patient outcome.

Malignant mesothelioma (MM) is an aggressive cancer primarily diagnosed on the basis of histological criteria1. The 2015 World Health Organization classification subdivides mesothelioma tumors into three histological types: epithelioid, biphasic and sarcomatoid MM. MM is a highly complex and heterogeneous disease, rendering its diagnosis and histological typing difficult and leading to suboptimal patient care and decisions regarding treatment modalities2. Here we have developed a new approach-based on deep convolutional neural networks-called MesoNet to accurately predict the overall survival of mesothelioma patients from whole-slide digitized images, without any pathologist-provided locally annotated regions. We validated MesoNet on both an internal validation cohort from the French MESOBANK and an independent cohort from The Cancer Genome Atlas (TCGA). We also demonstrated that the model was more accurate in predicting patient survival than using current pathology practices. Furthermore, unlike classical black-box deep learning methods, MesoNet identified regions contributing to patient outcome prediction. Strikingly, we found that these regions are mainly located in the stroma and are histological features associated with inflammation, cellular diversity and vacuolization. These findings suggest that deep learning models can identify new features predictive of patient survival and potentially lead to new biomarker discoveries.

Pathologic Considerations and Standardization in Mesothelioma Clinical Trials.

The accurate diagnosis of mesothelioma is critical for the appropriate clinical management of this cancer. Many issues complicate making the diagnosis of mesothelioma including the presence of reactive mesothelial cells in benign pleural effusions, the heterogeneity of mesothelioma histopathology, the relatively high incidence of other epithelial malignancies that metastasize to the pleura, and primary sarcomas that arise within the pleura. Given the rapidly evolving field of molecular profiling and the need for translational correlates in mesothelioma clinical trials, the National Cancer Institute (NCI)-International Association for the Study of Lung Cancer-Mesothelioma Applied Research Foundation Clinical Trials Planning Meeting was convened in March 2017 to develop a consensus on standard pathology guidelines for future NCI-sponsored clinical trials in mesothelioma. This consensus statement covers recommendations for specimen handling, pathologic classification and diagnosis, biobanking, and tissue correlative studies.

BAP1 haploinsufficiency predicts a distinct immunogenic class of malignant peritoneal mesothelioma.

BACKGROUND: Malignant peritoneal mesothelioma (PeM) is a rare and fatal cancer that originates from the peritoneal lining of the abdomen. Standard treatment of PeM is limited to cytoreductive surgery and/or chemotherapy, and no effective targeted therapies for PeM exist. Some immune checkpoint inhibitor studies of mesothelioma have found positivity to be associated with a worse prognosis. METHODS: To search for novel therapeutic targets for PeM, we performed a comprehensive integrative multi-omics analysis of the genome, transcriptome, and proteome of 19 treatment-naïve PeM, and in particular, we examined BAP1 mutation and copy number status and its relationship to immune checkpoint inhibitor activation. RESULTS: We found that PeM could be divided into tumors with an inflammatory tumor microenvironment and those without and that this distinction correlated with haploinsufficiency of BAP1. To further investigate the role of BAP1, we used our recently developed cancer driver gene prioritization algorithm, HIT'nDRIVE, and observed that PeM with BAP1 haploinsufficiency form a distinct molecular subtype characterized by distinct gene expression patterns of chromatin remodeling, DNA repair pathways, and immune checkpoint receptor activation. We demonstrate that this subtype is correlated with an inflammatory tumor microenvironment and thus is a candidate for immune checkpoint blockade therapies. CONCLUSIONS: Our findings reveal BAP1 to be a potential, easily trackable prognostic and predictive biomarker for PeM immunotherapy that refines PeM disease classification. BAP1 stratification may improve drug response rates in ongoing phases I and II clinical trials exploring the use of immune checkpoint blockade therapies in PeM in which BAP1 status is not considered. This integrated molecular characterization provides a comprehensive foundation for improved management of a subset of PeM patients.

Modification of existing patient-reported outcome measures: qualitative development of the MD Anderson Symptom Inventory for malignant pleural mesothelioma (MDASI-MPM).

PURPOSE: Malignant pleural mesothelioma (MPM) is an aggressive cancer of the lung pleura. The MD Anderson Symptom Inventory (MDASI) is a patient-reported outcome (PRO) measure of symptom burden, the combined impact of disease-related and treatment-related symptoms on functioning. Validated PRO measures may require modification for use in specific study populations. We sought to modify the MDASI for patients with MPM and create a fit-for-purpose symptom-burden measure for use in a clinical trial, according to US Food and Drug Administration guidance on PRO utilization to support labeling claims. METHODS: A literature review for MPM symptoms was conducted. Patients with MPM were qualitatively interviewed about experiences of disease and treatment. Descriptive analysis identified symptoms and interference with functioning to define MPM-related symptom burden. An expert panel rated the relevance of identified symptoms to patients with MPM. Patients who received the investigational drug in a previous Phase I study were interviewed for drug-specific symptoms. RESULTS: Literature review and interviews of 20 patients identified 31 MPM-related symptoms. A conceptual model of MPM-related symptom burden was developed. After expert-panel relevance review, five MPM-specific items and the 13 core MDASI symptoms met criteria for inclusion in a provisional MDASI-MPM for psychometric testing. Interviews with six patients identified six drug-specific symptoms; three were mentioned by multiple patients. Of these three, one was not in the core MDASI. CONCLUSIONS: The MDASI-MPM has established content validity and, with the addition of one symptom item, is ready for psychometric testing as fit-for-purpose for a clinical trial of an investigational agent.

Reproducibility of Malignant Pleural Mesothelioma Histopathologic Subtyping.

CONTEXT: - Malignant pleural mesothelioma (MPM) is a rare tumor with poor prognosis. Several studies have analyzed potential prognostic markers, but histologic type remains the single most important prognostic factor. Histologic subtypes of epithelioid MPM seem to have prognostic and therapeutic implications. Interobserver agreement in histologic pattern classification should be high. OBJECTIVE: - To assess interobserver and intraobserver reproducibility in histologic differentiation between the main types of MPMs, and in further subtyping of epithelioid-type mesothelioma. DESIGN: - One representative hematoxylin-eosin-stained slide was selected from the archive for each of 200 patients with MPM. They were reviewed independently by 3 pathologists and classified according to the current World Health Organization classification of pleural tumors. After the first round of evaluations, a consensus meeting was organized where problems were addressed and representative images for each histologic category were selected. Two months later, cases were reevaluated by all 3 pathologists. RESULTS: - After the first round, overall interobserver agreement for histologic subtyping of mesothelioma was fair (κ, 0.36). The agreement was increased to substantial (κ, 0.63) in the second round. Improvement was found in interobserver agreement for all types of MPM and for most epithelioid subtypes. CONCLUSIONS: - Moderate to substantial agreement in histologic typing and subtyping of MPM can be achieved. However, training with additional clarification of diagnostic criteria, their strict application, and help from consensus-based illustrative images is needed.

[Molecular heterogeneity of malignant pleural mesotheliomas]. / Hétérogénéité moléculaire des mésothéliomes pleuraux malins.

Malignant pleural mesothelioma (MPM) is predominantly an occupational cancer, most often linked to asbestos exposure. Malignant pleural mesothelioma prognosis is poor with a short survival median, due to the aggressiveness of tumor cells and the weak efficiency of conventional anti-cancer therapies. Clinical, histological, and molecular data suggest tumor heterogeneity between patients as it was also shown for other cancer types. Consequently, there is an urgent need to develop new therapies that take into account this heterogeneity and the molecular characteristics of malignant pleural mesothelioma, in particular by identifying new anti-cancer drugs targeting the molecular specificities of each malignant pleural mesothelioma. Malignant pleural mesothelioma is characterized by numerous molecular alterations at the chromosomal, genetic and epigenetic levels. Molecular classification based on gene expression profile has firstly defined two tumor groups, C1 and C2, and more recently, four groups. By integrating genetic and transcriptomic analysis, a C2LN tumor subgroup of the C2 group has been identified and characterized. In addition to tumor heterogeneity between patients, intra-tumor heterogeneity is supported by several evidences. Most therapeutic strategies that take into account the tumor molecular characteristics have focused on targeted therapies based on mutated genes. A more appropriate strategy would be to consider better-defined tumor groups on the basis of several molecular alterations types as it has been proposed for the C2LN subgroup. A robust definition of homogeneous tumor groups sharing common molecular characteristics is necessary for the development of effective precision medicine for malignant pleural mesothelioma.

Reproducibility for histologic parameters in peritoneal mesothelioma.

Histologic subtype is recognized as a prognostic factor in malignant pleural mesothelioma. Specifically, epithelial morphology is associated with a better prognosis than other subtypes, and the same association is observed in peritoneal malignant mesothelioma. Recently, prognostic differences based on morphologic subtypes of epithelial peritoneal malignant mesothelioma were reported. Herein, we report the interobserver variability across four pathologists at three institutions. The authors independently reviewed 67 cases of malignant peritoneal epithelioid mesotheliomas and subclassified them according to their epithelial subtype: papillary, tubulopapillary, trabecular, micropapillary, solid and/or pleomorphic. The cases were also evaluated by each author for several other histopathologic parameters including depth of invasion, nuclear grade, lymphocytic host response, mitotic count/index, presence of lymphovascular invasion, and stromal desmoplasia. The interobserver agreement for histopathologic parameters was highest for mitotic rate (κ=0.36) and primary epithelial subtype (κ=0.32). The interobserver variability for solid subtype pattern was moderate (κ=0.49). We found that the interobserver variability for most histopathologic parameters is poor.

The IASLC Mesothelioma Staging Project: Proposals for the M Descriptors and for Revision of the TNM Stage Groupings in the Forthcoming (Eighth) Edition of the TNM Classification for Mesothelioma.

INTRODUCTION: The M component and TNM stage groupings for malignant pleural mesothelioma (MPM) have been empirical. The International Association for the Study of Lung Cancer developed a multinational database to propose evidence-based revisions for the eighth edition of the TNM classification of MPM. METHODS: Data from 29 centers were submitted either electronically or by transfer of existing institutional databases. The M component as it currently stands was validated by confirming sufficient discrimination (by Kaplan-Meier analysis) with respect to overall survival (OS) between the clinical M0 (cM0) and cM1 categories. Candidate stage groups were developed by using a recursive partitioning and amalgamation algorithm applied to all cM0 cases. RESULTS: Of 3519 submitted cases, 2414 were analyzable and 84 were cM1 cases. Median OS for cM1 cases was 9.7 months versus 13.4 months (p = 0.0013) for the locally advanced (T4 or N3) cM0 cases, supporting inclusion of only cM1 in the stage IV group. Exploratory analyses suggest a possible difference in OS for single- versus multiple-site cM1 cases. A recursive partitioning and amalgamation-generated survival tree on the OS outcomes restricted to cM0 cases with the newly proposed (eighth edition) T and N components indicates that optimal stage groupings for the eighth edition will be as follows: stage IA (T1N0), stage IB (T2-3N0), stage II (T1-2N1), stage IIIA (T3N1), stage IIIB (T1-3N2 or any T4), and stage IV (any M1). CONCLUSIONS: This first evidence-based revision of the TNM classification for MPM leads to substantial changes in the T and N components and the stage groupings.

The IASLC Mesothelioma Staging Project: Proposals for Revisions of the T Descriptors in the Forthcoming Eighth Edition of the TNM Classification for Pleural Mesothelioma.

INTRODUCTION: The current T component for malignant pleural mesothelioma (MPM) has been predominantly informed by surgical data sets and consensus. The International Association for the Study of Lung Cancer undertook revision of the seventh edition of the staging system for MPM with the goal of developing recommendations for the eighth edition. METHODS: Data elements including detailed T descriptors were developed by consensus. Tumor thickness at three pleural levels was also recorded. An electronic data capture system was established to facilitate data submission. RESULTS: A total of 3519 cases were submitted to the database. Of those eligible for T-component analysis, 509 cases had only clinical staging, 836 cases had only surgical staging, and 642 cases had both available. Survival was examined for T categories according to the current seventh edition staging system. There was clear separation between all clinically staged categories except T1a versus T1b (hazard ratio = 0.99, p = 0.95) and T3 versus T4 (hazard ratio = 1.22, p = 0.09), although the numbers of T4 cases were small. Pathological staging failed to demonstrate a survival difference between adjacent categories with the exception of T3 versus T4. Performance improved with collapse of T1a and T1b into a single T1 category; no current descriptors were shifted or eliminated. Tumor thickness and nodular or rindlike morphology were significantly associated with survival. CONCLUSIONS: A recommendation to collapse both clinical and pathological T1a and T1b into a T1 classification will be made for the eighth edition staging system. Simple measurement of pleural thickness has prognostic significance and should be examined further with a view to incorporation into future staging.

The IASLC Mesothelioma Staging Project: Proposals for Revisions of the N Descriptors in the Forthcoming Eighth Edition of the TNM Classification for Pleural Mesothelioma.

INTRODUCTION: Nodal categories for malignant pleural mesothelioma are derived from the lung cancer staging system and have not been adequately validated. The International Association for the Study of Lung Cancer developed a multinational database to generate evidence-based recommendations to inform the eighth edition of the TNM classification of malignant pleural mesothelioma. METHODS: Data from 29 centers were entered prospectively (n = 1566) or by transfer of retrospective data (n = 1953). Survival according to the seventh edition N categories was evaluated using Kaplan-Meier survival curves and Cox proportional hazards regression analysis. Survival was measured from the date of diagnosis. RESULTS: There were 2432 analyzable cases: 1603 had clinical (c) staging, 1614 had pathologic (p) staging, and 785 had both. For clinically staged tumors there was no separation in Kaplan-Meier curves between cN0, cN1 or cN2 (cN1 versus cN0 hazard ratio [HR] = 1.06, p = 0.77 and cN2 versus cN1 HR = 1.04, p = 0.85). For pathologically staged tumors, patients with pN1 or pN2 tumors had worse survival than those with pN0 tumors (HR = 1.51, p < 0.0001) but no survival difference was noted between those with pN1 and pN2 tumors (HR = 0.99, p = 0.99). Patients with both pN1 and pN2 nodal involvement had poorer survival than those with pN2 tumors only (HR = 1.60, p = 0.007) or pN0 tumors (HR = 1.62, p < 0.0001). CONCLUSIONS: A recommendation to collapse both clinical and pN1 and pN2 categories into a single N category comprising ipsilateral, intrathoracic nodal metastases (N1) will be made for the eighth edition staging system. Nodes previously categorized as N3 will be reclassified as N2.

Pathology analysis for mesothelioma study in the United Kingdom: Current practice and historical development.

Following up on the largest case-control study of malignant mesothelioma yet performed, investigators at the London School of Hygiene and Tropical Medicine assessed 1732 male and 670 female cases as of May 2013. Epidemiological findings of a subset of these were published previously, excluding patients who died or who refused to be interviewed. Pathology reports were collected for subjects, including those both eligible and ineligible for epidemiology study based on vital status. The current investigation examined 860 cases having pathology reports available. Sixty-one cases were diagnosed using cytology only, often with equivocal diagnoses, while 799 reported at least a biopsy of the tumor. Of these, 748 had pathology sufficiently detailed for evaluation. These reports were examined for basis of diagnosis, differences between study cases and ineligible cases, pathology characteristics, and immunohistochemical and other tests used. The most prominent subtype was epithelioid (64% of study cases but only 49% of ineligible cases). Biphasic subtype was present in 10% of study cases and 16% of those ineligible. Sarcomatoid subtype was present in 7% of study cases and 19% of ineligible cases, most of whom died. Twelve percent of study cases displayed no specified subtype, versus 7% of ineligible cases. Of recorded immunohistochemical stains specific for mesothelial cell origin, calretinin (95%) and CK 5/6 or CK5 alone (84%) were by far the most common. Calretinin and CK 5/6 or CK 5 alone were also most sensitive and positive in 92% of cases presenting with surgical pathology report. Ninety percent of cases had at least one immunohistochemical marker for possible lung carcinoma applied, with BER-Ep4 and TTF-1 the most frequent at 68% and CEA at 58%. TTF-1 and CEA were positive in 1% or less of cases. Patterns of use and positive and negative results for each of these as well as other immunohistochemical stains are presented and discussed, along with a brief historical description of their development and use. Possible effects of the pathologic analysis on the results of previously published and future epidemiological studies are discussed.

The IASLC Mesothelioma Staging Project: Improving Staging of a Rare Disease Through International Participation.

For nearly 40 years, there was no generally accepted staging system for malignant pleural mesothelioma. In 1994, members of the International Mesothelioma Interest Group, in collaboration with the International Association for the Study of Lung Cancer, proposed a TNM staging system based on analyses of outcomes in retrospective surgical series and small clinical trials. Subsequently accepted by the American Joint Commission on Cancer and the Union for International Cancer Control for the sixth editions of their staging manuals, this system has since been the international staging standard. However, it has significant limitations, particularly with respect to clinical staging and to the categories for lymph node staging. Here we provide an overview of the development of the International Association for the Study of Lung Cancer malignant pleural mesothelioma staging database, which was designed to address these limitations through the development of a large international data set. Analyses of this database, described in papers linked to this overview, are being used to inform revisions in the eighth editions of the American Joint Commission on Cancer and Union for International Cancer Control staging systems.

[Comparing the results of pathologic diagnosis of mesothelioma between Chinese and Japanese experts].

OBJECTIVE: To compare the results of pathological diagnosis of 41 patients with malignant mesothelioma between Chinese and Japanese experts, and to provide a basis for the standard for diagnosis of mesothelioma. METHODS: The medical information and tissue samples of 41 patients with malignant mesothelioma were collected in a hospital in Zhejiang Province from 2003 to 2010. The expression levels of calretinin, Wilms' tumor suppressor gene (WT1), podoplanin (D2-40), cytokeratins (CK5/6, AE1/AE3, and CAM5.2), epithelial membrane antigen, carcinoembryonic antigen, BerEP4, MOC31, thyroid transcription factor-1, estrogen receptor, and progesterone receptor in tumor tissues were measured using immunohistochemical staining by Japanese experts, and the pathological classification and diagnosis were made. The results of diagnosis, pathological classification, immunohistochemical marker selection, and slide review were compared between Chinese and Japanese experts. RESULTS: Twenty-nine (70.7%) cases were diagnosed as mesothelioma by Japanese experts, among whom 12 (41.4%) cases were pleura mesothelioma, and 17 (58.6%) cases were peritoneal mesothelioma. Ten (24.4%) cases were confirmed without mesothelioma, and 2 (4.9%) cases were not confirmed due to insufficient information. Thirty-two (78.0%) cases were diagnosed as mesothelioma by Chinese experts, among whom 8 (25.0%) cases were pleura mesothelioma, and 24 (75.0%) cases were peritoneal mesothelioma. One (2.4%) case was confirmed without mesothelioma, and 8 (19.5%) cases were not confirmed. There were significant differences in the results of diagnosis between Chinese and Japanese experts. However, their pathological classifications of mesothelioma were similar. Significant differences in immunohistochemical marker selection and slide review were also found between Chinese and Japanese experts. CONCLUSION: The diagnostic skills of those pathological experts in this hospital remain to be further improved for mesothelioma diagnosis. A panel of immunohistochemical markers including at least 2 mesothelioma-positive and 2 mesothelioma-negative markers are recommended for the diagnosis of malignant mesothelioma.

Detection of malignant mesothelioma using nuclear structure of mesothelial cells in effusion cytology specimens.

Mesothelioma is a form of cancer generally caused from previous exposure to asbestos. Although it was considered a rare neoplasm in the past, its incidence is increasing worldwide due to extensive use of asbestos. In the current practice of medicine, the gold standard for diagnosing mesothelioma is through a pleural biopsy with subsequent histologic examination of the tissue. The diagnostic tissue should demonstrate the invasion by the tumor and is obtained through thoracoscopy or open thoracotomy, both being highly invasive surgical operations. On the other hand, thoracocentesis, which is removal of effusion fluid from the pleural space, is a far less invasive procedure that can provide material for cytological examination. In this study, we aim at detecting and classifying malignant mesothelioma based on the nuclear chromatin distribution from digital images of mesothelial cells in effusion cytology specimens. Accordingly, a computerized method is developed to determine whether a set of nuclei belonging to a patient is benign or malignant. The quantification of chromatin distribution is performed by using the optimal transport-based linear embedding for segmented nuclei in combination with the modified Fisher discriminant analysis. Classification is then performed through a k-nearest neighborhood approach and a basic voting strategy. Our experiments on 34 different human cases result in 100% accurate predictions computed with blind cross validation. Experimental comparisons also show that the new method can significantly outperform standard numerical feature-type methods in terms of agreement with the clinical diagnosis gold standard. According to our results, we conclude that nuclear structure of mesothelial cells alone may contain enough information to separate malignant mesothelioma from benign mesothelial proliferations.

[Morphological diagnostics of malignant pleural mesothelioma]. / Morphologische Diagnostik maligner Pleuramesotheliome.

The World Health Organization (WHO) classification differentiates between pleural tumors of mesothelial and mesenchymal origin as well as lymphoproliferative disorders, with malignant mesotheliomas forming the most common pleural primary tumor. Histologically, epithelioid (40-60 %), sarcomatoid (20-40 %), and biphasic mesotheliomas (20-40 %) are distinguished. The certain morphological diagnosis of a malignant pleural mesothelioma requires the establishment of mesothelial differentiation by means of an appropriate panel of antibodies to exclude pleural dissemination of a pulmonary or extrapulmonary epithelial malignancy and also requires the establishment of at least focal invasive growth to distinguish from reactive mesothelial proliferation. The exclusion of a malignant pleural mesothelioma may induce further differential diagnostic considerations, e. g. concerning the assignment to a certain primary tumor after the establishment of carcinomatous pleuritis.

[Pleural mesothelioma. Cytology and molecular diagnostics]. / Pleuramesotheliom. Zytologie und molekulare Diagnostik.

The definitive diagnosis of malignant mesothelioma (MM) in effusion cytology is often avoided or reluctantly made by cytology alone. The most probable reason for this skepticism is the lack of expertise in cytology among many pathologists and clinicians. When an effusion specimen is composed of cells with unequivocal cytological features of malignancy that have the morphology and immunophenotype of mesothelial cells, the cytological diagnosis of MM is straightforward. However, in the daily routine difficult cases of atypical mesothelial cells are often encountered and additional methods are required to establish an accurate diagnosis. In contrast to reactive mesothelial cells cells of MMs often harbor chromosomal aberrations, most frequently a polysomy in combination with a 9p21 deletion. These chromosomal aberrations can easily be detected by multitarget fluorescence in situ hybridization (FISH); therefore, FISH allows a reliable distinction between reactive mesothelial cells and MM cells. In order to be able to discriminate between MM and adenocarcinoma, an immunocytochemical panel consisting of different mesothelial and epithelial markers is very helpful. In most inconclusive cases of atypical mesothelial cells the combination of morphology, immunocytochemistry and FISH allows a better distinction between reactive mesothelial cells and MM in effusion cytology.

Malignant Pleural Mesothelioma : Rationale for a New TNM Classification.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a rare but aggressive thoracic malignancy with a poor prognosis. In this regard, a well-defined staging system is of utmost importance in order to correctly diagnose and assign an appropriate treatment to the patient. METHODS: The current TNM-staging system (7th edition) enables to either clinically or pathologically stage the severity of the disease according to extension of the tumor (T), number of nodes (N) and presence of metastases (M). Patients with stage I-III are considered for surgery, while palliative treatment is indicated for stage IV patients according to the current classification. RESULTS: Despite its widespread use, the validity of this staging system is questioned due to the low prevalence, histological variety and retrospective nature of the previous study design. In addition, the role of specific treatment modalities including surgery, has yet to be determined, especially for treatment of early-stage disease. In this regard, the International Association for the Study of Lung Cancer (IASLC) initiated the multi-centre, prospective "Mesothelioma Staging Project" in order to address limitations of the 7th edition and to optimize the staging system in accordance to current needs. CONCLUSIONS: An improved staging system will contribute to the design of prospective multi-institutional clinical trials investigating novel treatment strategies for mesothelioma. In this way comparison of outcome between different medical centres also becomes feasible.