JAK-STAT inhibition impairs K-RAS-driven lung adenocarcinoma progression

Oncogenic KRAS has been difficult to target and currently there is no KRASbased targeted therapy available for patients suffering from KRASdriven lung adenocarcinoma (AC). Alternatively, targeting KRASdownstream effectors, KRAScooperating signaling pathways or cancer hallmarks, such as tumorpromoting inflammation, has been shown to be a promising therapeutic strategy. Since the JAKSTAT pathway is considered to be a central player in inflammationmediated tumorigenesis, we investigated here the implication of JAKSTAT signaling and the therapeutic potential of JAK1/2 inhibition in KRASdriven lung AC. Our data showed that JAK1 and JAK2 are activated in human lung AC and that increased activation of JAKSTAT signaling correlated with disease progression and KRAS activity in human lung AC. Accordingly, administration of the JAK1/2 selective tyrosine kinase inhibitor ruxolitinib reduced proliferation of tumor cells and effectively reduced tumor progression in immunodeficient and immunocompetent mouse models of KRASdriven lung AC. Notably, JAK1/2 inhibition led to the establishment of an antitumorigenic tumor microenvironment, characterized by decreased levels of tumorpromoting chemokines and cytokines and reduced numbers of infiltrating myeloid derived suppressor cells, thereby impairing tumor growth. Taken together, we identified JAK1/2 inhibition as promising therapy for KRASdriven lung AC.(VLID)510233

Ki67 index is an independent prognostic factor in epithelioid but not in non-epithelioid malignant pleural mesothelioma: a multicenter study

BACKGROUND: Estimating the prognosis in malignant pleural mesothelioma (MPM) remains challenging. Thus, the prognostic relevance of Ki67 was studied in MPM. METHODS: Ki67 index was determined in a test cohort of 187 cases from three centres. The percentage of Ki67-positive tumour cells was correlated with clinical variables and overall survival (OS). The prognostic power of Ki67 index was compared with other prognostic factors and re-evaluated in an independent cohort (n=98). RESULTS: Patients with Ki67 higher than median (>15%) had significantly (P<0.001) shorter median OS (7.5 months) than those with low Ki67 (19.1 months). After multivariate survival analyses, Ki67 proved to be-beside histology and treatment-an independent prognostic marker in MPM (hazard ratio (HR): 2.1, P<0.001). Interestingly, Ki67 was prognostic exclusively in epithelioid (P<0.001) but not in non-epithelioid subtype. Furthermore, Ki67 index was significantly lower in post-chemotherapy samples when compared with chemo-naive cases. The prognostic power was comparable to other recently published prognostic factors (CRP, fibrinogen, neutrophil-to-leukocyte ratio (NLR) and nuclear grading score) and was recapitulated in the validation cohort (P=0.048). CONCLUSION: This multicentre study demonstrates that Ki67 is an independent and reproducible prognostic factor in epithelioid but not in non-epithelioid MPM and suggests that induction chemotherapy decreases the proliferative capacity of MPM

Circulating fibrinogen is a prognostic and predictive biomarker in malignant pleural mesothelioma.

Background:To investigate the clinical utility of pretreatment plasma fibrinogen levels in malignant pleural mesothelioma (MPM) patients.Methods:A retrospective multicenter study was performed in histologically proven MPM patients. All fibrinogen levels were measured at the time of diagnosis and clinical data were retrospectively collected after approval of the corresponding ethics committees.Results:In total, 176 MPM patients (mean age: 63.5 years+/-10.4 years, 38 females and 138 males) were analysed. Most patients (n=154, 87.5%) had elevated (>/=390 mg dl-1) plasma fibrinogen levels. When patients were grouped by median fibrinogen, patients with low level (</=627 mg dl-1) had significantly longer overall survival (OS) (19.1 months, confidence interval (CI) 14.5-23.7 months) when compared with those with high level (OS 8.5; CI 6.2-10.7 months). In multivariate survival analyses, fibrinogen was found to be an independent prognostic factor (hazard ratio 1.81, CI 1.23-2.65). Most interestingly, fibrinogen (cutoff 75th percentile per 750 mg dl-1) proved to be a predictive biomarker indicating treatment benefit achieved by surgery within multimodality therapy (interaction term: P=0.034). Accordingly, only patients below the 75th percentile benefit from surgery within multimodality therapy (31.3 vs 5.3 months OS).Conclusions:Fibrinogen is a novel independent prognostic biomarker in MPM. Most importantly, fibrinogen predicted treatment benefit achieved by surgery within multimodality therapy.British Journal of Cancer advance online publication, 16 January 2014; doi:10.1038/bjc.2013.815 www.bjcancer.com

Assessment of the current and emerging criteria for the histopathological classification of lung neuroendocrine tumours in the lungNENomics project

Background: Six thoracic pathologists reviewed 259 lung neuroendocrine tumours (LNETs) from the lungNENomics project, with 171 of them having associated survival data. This cohort presents a unique opportunity to assess the strengths and limitations of current World Health Organization (WHO) classification criteria and to evaluate the utility of emerging markers. Patients and methods: Patients were diagnosed based on the 2021 WHO criteria, with atypical carcinoids (ACs) defined by the presence of focal necrosis and/or 2-10 mitoses per 2 mm2. We investigated two markers of tumour proliferation: the Ki-67 index and phospho-histone H3 (PHH3) protein expression, quantified by pathologists and automatically via deep learning. Additionally, an unsupervised deep learning algorithm was trained to uncover previously unnoticed morphological features with diagnostic value. Results: The accuracy in distinguishing typical from ACs is hampered by interobserver variability in mitotic counting and the limitations of morphological criteria in identifying aggressive cases. Our study reveals that different Ki-67 cut-offs can categorise LNETs similarly to current WHO criteria. Counting mitoses in PHH3+ areas does not improve diagnosis, while providing a similar prognostic value to the current criteria. With the advantage of being time efficient, automated assessment of these markers leads to similar conclusions. Lastly, state-of-the-art deep learning modelling does not uncover undisclosed morphological features with diagnostic value. Conclusions: This study suggests that the mitotic criteria can be complemented by manual or automated assessment of Ki-67 or PHH3 protein expression, but these markers do not significantly improve the prognostic value of the current classification, as the AC group remains highly unspecific for aggressive cases. Therefore, we may have exhausted the potential of morphological features in classifying and prognosticating LNETs. Our study suggests that it might be time to shift the research focus towards investigating molecular markers that could contribute to a more clinically relevant morpho-molecular classification.</p

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting