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MA09 - Lung Cancer Surgical and Molecular Pathology (ID 908)
- Event: WCLC 2018
- Type: Mini Oral Abstract Session
- Track: Pathology
- Presentations: 1
- Coordinates: 9/24/2018, 15:15 - 16:45, Room 202 BD
MA09.03 - Multiple Pathological Variables Predict Efficacy of Adjuvant Chemotherapy in Primary Lung Adenocarcinoma (ID 13761)
15:25 - 15:30 | Author(s): Madhumita Das
Adjuvant chemotherapy has become established as a vital complement to surgery over the last decade, and improves survival by targeting micrometastatic disease which is clinically inaparrent at the time of surgery. However, in comparison to other common malignancies, the guidelines for the administration of adjuvant chemotherapy in lung cancer are rudimentary, being based solely upon clinical stage II and above at the time of surgery. We set out to discover pathological factors with the potential to better identify patients who are likely to benefit from this vital therapy.a9ded1e5ce5d75814730bb4caaf49419 Method
662 cases of primary lung adenocarcinoma treated with surgery with curative intent were identified from 2005-2014; 109 received adjuvant chemotherapy. Comprehensive survival/recurrence data, pathological data, and treatment history data were collected. Detailed histopathological data (growth pattern, vascular invasion, pleural stage) were collected by review of scanned histopathological images.
Multivariate Cox regression survival models were used to identify interactions between clinicopathological variables and adjuvant chemotherapy. A propensity score matching approasch was used to reduce selection biases in the data.4c3880bb027f159e801041b1021e88e8 Result
The existing stage criteria for the recommendation of adjuvant chemotherapy are stage pN1/2 and size>40mm; only nodal invasion interacts with chemotherapy in an OS model (interaction term HR=0.67 P=0.017). However, signficant interactions are seen with predominant growth pattern (HR=0.47 P=0.001 ), pleural stage (HR=0.62 P=0.002 ), and vascular invasion (HR=0.56 P=0.033).
We reduced selection bias by balancing treated and untreated groups by propensity matching for all prognostic variables. In the matched dataset, patients with predominantly in situ tumours experience no benefit of chemotherapy (HR=1.81 P=0.18), while higher-grade cases show substantial benefit (HR=0.53 P=0.01). Similar benefits were seen for patients with increasing pleural stage and vascular invasion.
In a multivariate model designed to identify which variable(s) had the most ability to predict treatment efficacy, only tumour growth pattern showed a significant interaction with chemotherapy treatment (HR=0.51 P=0.01 ).8eea62084ca7e541d918e823422bd82e Conclusion
We find that the existing stage-based criteria for adjuvant chemotherapy can be much improved. Low-grade cases experienced only negative effects of chemotherapy, while higher-grade cases showed a benefit. Pleural stage and vascular invasion were also significantly predictive. We suggest that the current criteria may be leading to substantial over- and under-treatment. A nuanced algorithm for the identification of patients likely to benefit from chemotherapy, which includes these additional pathoogical measures, may significantly improve patient outcomes. This would be especially impactful to the majority of surgical patients for whom no personalised therapy is as yet available.6f8b794f3246b0c1e1780bb4d4d5dc53
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P1.09 - Pathology (Not CME Accredited Session) (ID 941)
- Event: WCLC 2018
- Type: Poster Viewing in the Exhibit Hall
- Presentations: 1
- Coordinates: 9/24/2018, 16:45 - 18:00, Exhibit Hall
P1.09-29 - In Situ Growth Pattern in Lung Adenocarcinoma Is Divisible into Distinct Categories with Divergent Biological and Survival Implications (ID 13872)
16:45 - 18:00 | Author(s): Madhumita Das
The morphological stepwise progression of lung adenocarcinomas is well established, but little is known about the molecular events that underlie this. In particular, in situ patterns of growth are frequently seen in adenocarcinomas, and often it is not clear if this truly always represents early-stage preinvasive disease. Therefore we set out to better characterise in situ tumour growth, and to identify molecular and biological correlates of tumour invasion.a9ded1e5ce5d75814730bb4caaf49419 Method
We constructed a retrospective cohort of 964 locally held adenocarcinomas, with patient data and tissue microarrays (TMAs). Immunohistochemistry for Ki67 and epithelial-mesenchymal transition markers was applied to TMAs and quantified.
In situ and adjacent invasive areas of 23 early tumours were subjected to further in situ assays and laser capture microdissection. Genomic DNA was extracted and driver genes were panel sequenced.
We morphologically identified two distinct types of in situ tumour growth in early mixed pattern tumours: a low-grade precursor ('C1'- after the classic Noguchi classification) associated with higher-grade invasive disease, and a high-grade lepidic outgrowth ('C2') associated with invasive growth of similar cytological grade.
C1 and C2-type in situ tumour growth are sharply separated by their proliferation rate (P=0.005) and their propensity for nodal metastasis (P=0.03), suggesting that this distinction is likely to be important in future grading/growth pattern classification. Furthermore, molecular analysis supports the classification; invasive areas of C1 tumours show driver mutations which are absent from neighbouring in situ disease (4/18 cases), indicating molecular progression, while in 5 sequenced C2 cases no evidence of molecular progression was seen.
The difference between low-grade precursor and high-grade in situ patterns was further investigated in our full set of 964 tumours. We find that the prognostic power of proliferation rate (Ki67) is driven almost entirely by its effects in in situ areas of tumour growth. Proliferation rate in invasive tumour areas at most weakly predictive of patient outcome.8eea62084ca7e541d918e823422bd82e Conclusion
We make several key findings:
i) In situ disease in lung adenocaricnoma is divided into two biologically and prognostically distinct groups, with implications for our understanding of stepwise progression in lung cancer
ii) These two groups can easily be separated on the basis of cellular proliferation rate
ii) We identify mutations in key driver genes that are explicitly asociated with the transition from in situ to invasive growth
iii) Proliferation rate is a potentially valuable prognostic marker, but this may be restricted to its ability to separate these two key biologically distinct growth patterns6f8b794f3246b0c1e1780bb4d4d5dc53