Prognosis of resected, early-stage, lung adenocarcinoma patients

Lung cancer is the leading cause of cancer related death worldwide; despite recent treatment developments survival rates remain poor and are closely related to the patient’s clinical stage. Even among patients with early-stage lung cancer, which is amenable to surgical resection, prognosis is highly variable; some go on to live disease-free for many years whereas others quickly recur. Although post-operative chemotherapy is available it has associated morbidities and it is unclear which patients would benefit; therefore, there is a need for more effective stratification of patients. The adenocarcinoma sub-type of lung cancer is known to be morphologically heterogeneous however the majority of observed growth patterns, assessed by light microscopy, can be characterised into one of five formations: lepidic, papillary, acinar, solid and micropapillary. The morphology of each tumour has been proposed as a marker of prognosis and several studies have published a link between the most prevalent growth pattern and prognosis; suggesting those with predominantly solid or micropapillary tumours to have the least favourable outcomes. Indeed, it is now recommended that the proportion of each growth pattern and the predominant growth pattern should be reported for all resected lung adenocarcinomas; although no differential treatments have been recommended based on this assessment. The aim of this study was to determine whether combining the analysis of clinicopathological; morphological; and candidate protein, molecular genetic and transcriptomic characteristics in a single cohort of 208 early-stage, resected, adenocarcinomas with clinical follow-up could be used to identify a subset of patients at high risk of recurrence. Comprehensive morphological analysis was carried out including the presence, proportion and number of individual growth patterns; the predominant growth pattern as well as features previously associated with tumour grade (the presence of large numbers of mitotic figures, apoptotic bodies, inflammatory cells, prominent nucleoli, pleomorphic tumour cells, dyscohesive tumour cells and large amounts of necrosis and scar tissue within the tumour). In addition, gene expression was assessed using a panel of 31 cell-cycle related genes, EGFR and KRAS mutation status was determined, and EGFR and TTF1 protein expression investigated. In this study the predominant growth pattern defined by histopathology showed no ability to identify a group of patients with a poorer prognosis either in univariable or multivariable analysis. Univariable analysis identified nodal status [hazard ratio of N1 compared to N0 was 2.16 (95% CI 1.48 to 3.16, p< 0.0005)], clinical stage [hazard ratios of stage IIa and IIb compared to stage Ia were 3.15 (95% CI 1.73 to 5.73, p< 0.0005) and 2.22 (95% CI 1.10 to 4.48, p= 0.025) respectively], the presence of a significant amount of the papillary growth pattern [the hazard ratio of those with less than 8.5% papillary pattern was 0.657 (95% CI 0.44 to 0.98, p= 0.035)], and overall tumour grade score (including an assessment of necrosis, mitosis, apoptosis, nucleoli, scar tissue and inflammatory cells) [hazard ratio 1.71 (95% CI 1.14 to 2.56, p= 0.008)] as significantly associated with prognosis. Multivariable analysis using Cox’s proportional hazards model identified clinical stage (p< 0.0005), the presence of a significant amount of the papillary growth pattern (p= 0.048) and the presence of large numbers of mitotic figures (p=0.029) and apoptotic bodies (p= 0.015) as independently associated with disease specific survival; although after correction for type I errors only clinical stage remained significantly associated with prognosis with patients with stage Ia disease having a significantly better outcomes [hazard ratio 0.418 (95% CI 0.20 to 0.86)]. Classification and regression tree analysis (CART) was used to further explore the data and to develop decision trees for the prognostication of early-stage lung adenocarcinoma patients. Receiver operating characteristic analysis based on 5- year survival showed a minimal improvement in the area under the curve between a model utilizing currently available clinicopathologic characteristics only [nodal status and lesion size, (area under the curve 0.704, 95% CI 0.631 to 0.777)] and one including growth pattern characteristics [area under the curve 0.725, 95% CI 0.654 to 0.796]. The greatest improvement in prognostic accuracy was observed when gene expression analysis was included in the analysis [area under the curve 0.749, 95% CI 0.673 to 0.825]; however even this showed very little impact compared to routinely used clinicopathologic variables. This analysis suggests that the recommended characterisation of lung adenocarcinoma histology is not a robust predictor of patient outcomes; even a broader model which also included indicators of tumour grade and molecular characteristics was unable to identify a model sufficiently robust to implement into clinical practice and thereby potentially alter patient treatment. Currently routinely collected clinical characteristics; including nodal status, size and clinical stage; continue to provide the most robust method of prognostication and detailed and time-consuming morphological analysis offers no significant benefit to the patient

Evaluation of PD-L1 expression in various formalin-fixed paraffin embedded tumour tissue samples using SP263, SP142 and QR1 antibody clones

Background & objectives: Cancer cells can avoid immune destruction through the inhibitory ligand PD-L1. PD-1 is a surface cell receptor, part of the immunoglobulin family. Its ligand PD-L1 is expressed by tumour cells and stromal tumour infltrating lymphocytes (TIL). Methods: Forty-four cancer cases were included in this study (24 triple-negative breast cancers (TNBC), 10 non-small cell lung cancer (NSCLC) and 10 malignant melanoma cases). Three clones of monoclonal primary antibodies were compared: QR1 (Quartett), SP 142 and SP263 (Ventana). For visualization, ultraView Universal DAB Detection Kit from Ventana was used on an automated platform for immunohistochemical staining Ventana BenchMark GX. Results: Comparing the sensitivity of two different clones on same tissue samples from TNBC, we found that the QR1 clone gave higher percentage of positive cells than clone SP142, but there was no statistically significant difference. Comparing the sensitivity of two different clones on same tissue samples from malignant melanoma, the SP263 clone gave higher percentage of positive cells than the QR1 clone, but again the difference was not statistically significant. Comparing the sensitivity of two different clones on same tissue samples from NSCLC, we found higher percentage of positive cells using the QR1 clone in comparison with the SP142 clone, but once again, the difference was not statistically significant. Conclusion: The three different antibody clones from two manufacturers Ventana and Quartett, gave comparable results with no statistically significant difference in staining intensity/ percentage of positive tumour and/or immune cells. Therefore, different PD-L1 clones from different manufacturers can potentially be used to evaluate the PD- L1 status in different tumour tissues. Due to the serious implications of the PD-L1 analysis in further treatment decisions for cancer patients, every antibody clone, staining protocol and evaluation process should be carefully and meticulously validated

In Vitro and In Vivo Models of Colorectal Cancer for Clinical Application

The Special Issue "In Vitro and In Vivo Models of Colorectal Cancer for Clinical Application", edited by Marta Baiocchi and Ann Zeuner for Cancers, collects original research papers and reviews, depicting the current state and the perspectives of CRC models for preclinical and translational research. Original research papers published in this issue focus on some of the hottest topics in CRC research, such as circulating tumor cells, epigenetic regulation of stemness states, new therapeutic targets, molecular CRC classification and experimental CRC models such as organoids and PDXs. Additionally, four reviews on CRC stem cells, immunotherapy and drug discovery provide an updated viewpoint on key topics linking benchtop to bedside research in CRC