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A.L. Moreira
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P2.01 - Poster Session with Presenters Present (ID 461)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Biology/Pathology
- Presentations: 1
- Moderators:
- Coordinates: 12/06/2016, 14:30 - 15:45, Hall B (Poster Area)
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P2.01-026 - A Mass Spectrometry Based Stem Cell-Oriented Phylogeny of Intra-Tumoral NSCLC Subclones (ID 4385)
14:30 - 14:30 | Author(s): A.L. Moreira
- Abstract
Background:
Sub-clones within a cancer diverge due to ongoing accumulation of mutations. We sought to characterize the intratumor heterogeneity and phylogenetic relationships among different histological patterns present in lung adenocarcinomas based on mass spectrometric analysis of tumor subclones.
Methods:
MALDI-TOF mass spectrometry was used to generate proteomics data from different histological regions of 35 resected lung tumors, as well as from 3 basal cell and 3 mesenchymal cell samples. A total of 1985 different histological regions were analyzed from the 35 resected tumors along with the 3 samples each of airway basal cells and mesenchymal stem cells. For each of the 1991 samples, a spectral profile was generated with expression data from 217 peptide mass peaks to allow comparison of the proteomics profiles from the different histological regions from each cancer to the basal and mesenchymal stem cell profiles. Weighted protein co-expression networks were analyzed by using WGCNA package in R. Global and histologic specific networks were generated through using a power adjacency function which defines the similarity between any pairs of proteins The network modules were decided by using average linkage hierarchical clustering and a dynamic tree-cut algorithm. Networks of the different histologies and normal were compared and visualized by heat map methods.
Results:
The clinically more aggressive histologies ( micropapillary/solid) clustered with stem cells and away from normal alveolar tissue (Fig 1) and had severe loss in peptide connectivities (Fig 3). Applying t-SNE dimensionality reduction method showed that subclones from one specimen cluster differently from each other suggesting underlying heterogeneity, with more heterogenous tumors being associated with worse prognosis (Fig 2). Figure 1
Conclusion:
Construction of a phylogenetic tree of lung ACA subclones oriented to stem cells demonstrated that the degree of disruption of a subclone correlated with the degree of similarity of the subclone to stem cells, and with prognosis.
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P3.01 - Poster Session with Presenters Present (ID 469)
- Event: WCLC 2016
- Type: Poster Presenters Present
- Track: Biology/Pathology
- Presentations: 3
- Moderators:
- Coordinates: 12/07/2016, 14:30 - 15:45, Hall B (Poster Area)
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P3.01-018 - Reproducibility in Classification of Small Lung Adenocarcinomas: An International Interobserver Study (ID 5222)
14:30 - 14:30 | Author(s): A.L. Moreira
- Abstract
Background:
The 2015 WHO classification for lung adenocarcinoma (ACA) provides criteria for diagnosis of adenocarcinoma in-situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (INV). Differentiating these entities can be difficult, and as understanding of prognostic significance increases, inconsistent classification is problematic.
Methods:
Sixty cases of lung ACAs (<2cm) were reviewed by an international panel of 6 lung pathologists. One slide reflecting overall morphology of each case was digitally scanned to an internet browser-based viewer. In round one, the panel independently reviewed each case to assess predominant pattern, invasive component size, and final diagnosis (AIS, MIA or INV). After a consensus conference among participants, a second round of independent review of the cases was performed. Additionally, a discussion on interpretation of elastic stain for evaluation of invasion will precede a third round of review with assessment of a concomitant elastic stain for each case. Statistical analysis was performed for each round.
Results:
In round one, the overall kappa value for AIS versus MIA and INV was 0.34 (fair agreement), and that for AIS and MIA versus INV was 0.44 (moderate agreement). The raters had 100% agreement on final diagnosis in 10 cases (AIS, n=2; MIA, n=2; INV, n=6). In 28 cases with poor agreement on final diagnosis and invasive measurement, inconsistent measurement of multifocal invasion led to wide variance in 5 cases, and subjectivity in pattern recognition led to variance in 23 cases. Misinterpretation of the WHO criteria for MIA resulted in 18 instances of misclassification across all raters. A case with a predominant mucinous lepidic pattern had a range of diagnoses (AIS, n=1; MIA, n=1; INV, n=4). In round two, the overall kappa value for AIS versus MIA and INV is 0.40 (fair agreement), and that for AIS and MIA versus INV is 0.36 (moderate agreement). The raters had 100% agreement on final diagnosis in 12 cases (AIS, n=3; MIA n=4; INV, n=5). Misinterpretation of the WHO criteria for MIA was seen in 6 instances. The intraobserver kappa coefficient ranged widely from 0.259 to 0.859.
Conclusion:
Interobserver agreement on diagnosis of small lung ACAs between raters was fair to moderate, with minimal improvement after a consensus conference. Inconsistent measurement of multifocal invasion, subjectivity in pattern recognition, misinterpretation of the WHO criteria, and subjective interpretation of mucinous ACA have contributed to interobserver discordance. A third round of evaluation is currently ongoing to assess for improvement and the utility of elastic stains.
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P3.01-021 - Reproducibility of Comprehensive Histologic Assessment and Refining Histologic Criteria in P Staging of Multiple Tumour Nodules (ID 5365)
14:30 - 14:30 | Author(s): A.L. Moreira
- Abstract
Background:
Multiple tumor nodules (MTNs) are being encountered, with increasing frequency with the 8[th] TNM staging system recommending classification as separate primary lung cancers (SPLC) or intrapulmonary metastases (IM). Pathological staging requires assessment of morphological features, with criteria of Martini and Melamed supplanted by comprehensive histologic assessment of tumour type, predominant pattern, other histologic patterns and cytologic features. With publication of the 2015 WHO classification of lung tumours, we assessed the reproducibility of comprehensive histologic assessment and also sought to identify the most useful histological features.
Methods:
We conducted an online survey in which pathologists reviewed a sequential cohort of resected multifocal tumours to determine whether they were SPLC, IM, or a combination. Specific histological features for each nodule were entered into the database by the observing pathologist (tumour type, predominant adenocarcinoma pattern, and histological features including presence of lepidic growth, intra-alveolar cell clusters, cell size, mitotic rate, nuclear pleomorphism, nucleolar size and pleomorphism, nuclear inclusions, necrosis pattern, vascular invasion, mucin content, keratinization, clear cell change, cytoplasmic granules¸ lymphocytosis, macrophage response, acute inflammation and emperipolesis). Results were statistically analyzed for concordance with submitting diagnosis (gold standard) and among pathologists. Consistency of each feature was correlated with final determination of SPLC vs. IM status (p staging) by chi square analysis and Fisher exact test.
Results:
Seventeen pathologists evaluated 126 tumors from 48 patients. Kappa score on overall assessment of primary v. metastatic status was 0.60. There was good agreement as measured by Cohen’s Kappa (0.64, p<0.0001) between WHO histological patterns in individual cases with SPLC or IM status but proportions for histology and SPT or IM status were not identical (McNemar's test, p<0.0001) and additional histological features were assessed. There was marked variation in p values among the specific histological features. The strongest correlations (<0.05) between p staging status and histological features were with nuclear pleomorphism, cell size, acinus formation, nucleolar size, mitotic rate, nuclear inclusions, intra-alveolar clusters and necrosis pattern. Correlation between lymphocytosis, mucin content, lepidic growth, vascular invasion, macrophage response, clear cell change, acute inflammation keratinization and emperipolesis did not reach a p value of 0.05.
Conclusion:
Comprehensive histologic assessment shows good reproducibility between practicing lung pathologists. In addition to main tumour type and predominant patterns, nuclear pleomorphism, cell size, acinus formation, nucleolar size, and mitotic rate appear to be useful in distinguishing between SPLC and IM.
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P3.01-059 - A Stem-Cell Oriented Phylogeny of Non-Small Cell Lung Cancers (ID 4387)
14:30 - 14:30 | Author(s): A.L. Moreira
- Abstract
Background:
The degree of histologic cellular differentiation of a lung cancer has been associated with prognosis but is subjectively assessed. We hypothesized that information about tumor differentiation of individual cancers could be derived objectively from cancer gene expression data, and would allow creation of a cancer phylogenetic framework that would correlate with clinical, histologic and molecular characteristics of the cancers, as well as predict prognosis.
Methods:
We utilized mRNA expression data from NSCLC samples to explore the utility of ordering samples by their distance in gene expression from that of stem cells. A differentiation baseline was obtained by including expression data of human embryonic stem cells (hESC) and human mesenchymal stem cells (hMSC) for solid tumors, and of hESC and CD34+ cells for liquid tumors.
Results:
We found that the correlation distance (the degree of similarity) between the gene expression profile of a tumor sample and that of stem cells oriented lung cancers in a clinically coherent fashion. Cancers most similar to stem cells in gene expression are in general undifferentiated, larger, more likely to be node positive and more FDG avid on PET imaging. Most importantly,patients with cancers with gene expression patterns most similar to that of stem cells had poorer overall survival. Figure 1
Conclusion:
A stem cell oriented phylogeny of lung cancers objectively orients cancers by level of differentiation in a clinically coherent fashion. Lung cancers most similar to stem cells in expression are associated with a poorer prognosis after treatment.
