Comparison of Clinicopathological Features and Prognosis between <i>ALK</i> Rearrangements and <i>EGFR</i> Mutations in Surgically Resected Early-stage Lung Adenocarcinoma

Li, Pupu; Gao, Qiongqiong; Jiang, Xiaoming; Zhan, Zhongli; Qu, Yan; Li, Zhaona; Huang, Chun

doi:10.7150/jca.26947

Cited by 25 publications

(24 citation statements)

References 50 publications

(59 reference statements)

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“…As demonstrated by several studies, EGFR mutations are associated with female sex, w/d histological grade such as lepidic adenocarcinoma, and Asian ethnicity . However, the current study, wherein EGFR ‐mutated adenocarcinoma was divided into two subtypes (i.e., mucinous adenocarcinoma and nonmucinous adenocarcinoma), clearly revealed that EGFR ‐mutated mucinous adenocarcinoma was related to more males and smokers as well as lower histological grades than that without mucin.…”

Section: Discussioncontrasting

confidence: 60%

Mucinous lung adenocarcinoma, particularly referring to EGFR‐mutated mucinous adenocarcinoma

Wakejima

Inamura

Ninomiya

et al. 2019

Pathology International

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EGFR-mutated adenocarcinoma. Among 1159 surgically resected invasive adenocarcinomas, 189 mucinous adenocarcinomas (16%) were identified. Among these, 20%, 34% and 9.5% were EGFR mutated, KRAS mutated and ALK rearranged, respectively. Compared with EGFR-mutated nonmucinous adenocarcinoma, EGFR-mutated mucinous adenocarcinoma had no female predominance, lower grades of histological differentiation and lower TTF-1 and higher HNF-4a expressions. Moreover, for the first time, we indicated that mucin production was an independent prognostic factor for EGFR-mutated adenocarcinomas and the mucin-staining pattern of negative MUC5AC and positive MUC5B was characteristic in these adenocarcinomas. We suggest that EGFRmutated mucinous adenocarcinoma has a different tumorigenic pathway than nonmucinous EGFR-mutated adenocarcinoma. K E Y W O R D S adenocarcinoma, EGFR mutation, HNF-4a, KRAS mutation, lung, MUC1, MUC5B, mucin, TTF-1

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Section: Discussioncontrasting

confidence: 60%

Mucinous lung adenocarcinoma, particularly referring to EGFR‐mutated mucinous adenocarcinoma

Wakejima

Inamura

Ninomiya

et al. 2019

Pathology International

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“…In spite of this, the improved efficacy of the integrated model by adding clinical characteristics for lesions in the primary cohort suggests that clinical information was effective to improve the radiomic-based model for detecting ALK-mutated status. Adding more ALK-associated clinical variables such as carcinoembryonic antigen (CEA) level and histological growth pattern may further enhance the performance of the model (35,36). Previously, the best predictive model for the detection of ALK mutations was from Yamamoto's study (AUC = 0.846), in which it contained age as the only selected clinical feature and several conventional CT features (14).…”

Section: Discussionmentioning

confidence: 99%

Clinical, Conventional CT and Radiomic Feature-Based Machine Learning Models for Predicting ALK Rearrangement Status in Lung Adenocarcinoma Patients

Song

Zhu

Mao³

et al. 2020

Front. Oncol.

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Objectives: To predict the anaplastic lymphoma kinase (ALK) mutations in lung adenocarcinoma patients non-invasively with machine learning models that combine clinical, conventional CT and radiomic features. Methods: This retrospective study included 335 lung adenocarcinoma patients who were randomly divided into a primary cohort (268 patients; 90 ALK-rearranged; and 178 ALK wild-type) and a test cohort (67 patients; 22 ALK-rearranged; and 45 ALK wild-type). One thousand two hundred and eighteen quantitative radiomic features were extracted from the semi-automatically delineated volume of interest (VOI) of the entire tumor using both the original and the pre-processed non-enhanced CT images. Twelve conventional CT features and seven clinical features were also collected. Normalized features were selected using a sequential of the F-test-based method, the density-based spatial clustering of applications with noise (DBSCAN) method, and the recursive feature elimination (RFE) method. Selected features were then used to build three predictive models (radiomic, radiological, and integrated models) for the ALK-rearranged phenotype by a soft voting classifier. Models were evaluated in the test cohort using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity, and the performances of three models were compared using the DeLong test. Results: Our results showed that the addition of clinical information and conventional CT features significantly enhanced the validation performance of the radiomic model in the primary cohort (AUC = 0.83-0.88, P = 0.01), but not in the test cohort (AUC = 0.80-0.88, P = 0.29). The majority of radiomic features associated with ALK mutations reflected information around and within the high-intensity voxels of lesions. The presence of the cavity and left lower lobe location were new imaging phenotypic patterns Song et al. Radiomic-Based Model for ALK Mutations in association with ALK-rearranged tumors. Current smoking was strongly correlated with non-ALK-mutated lung adenocarcinoma. Conclusions: Our study demonstrates that radiomics-derived machine learning models can potentially serve as a non-invasive tool to identify ALK mutation of lung adenocarcinoma.

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“…Supporting this hypothesis, also early stages ALK+ lung cancers appeared to be more spread than what initially thought: a recent retrospective analysis, performed on resected lung adenocarcinoma with clinical N0 (absence of computed tomography or positron emission tomography detectable lymph node involvement), revealed an higher percentage of pathological N1 or N2 stage (37%) in ALK+ cases compared to other subgroups (EGFR+, KRAS+ or WT) (22). ALK+ lung cancer patients are younger, never or light smoker, diagnosed mainly on advanced stage of the disease, bearing adenocarcinoma histology with peculiar aspects: solid or sheet-like pattern, with "signet-ring" cells and invasive mucinous aspects, similar to other fusionpositive subgroups (i.e., ROS+ or RET+) (13,(17)(18)(19); thus, identifying a subgroup of tumors with morphological aspects denoting itself a more aggressive phenotype (23,24).…”

Section: Alk Rearrangement Frequency (Early and Late Stage)mentioning

confidence: 92%

“…Identification of the right comparator group seems to be relevant: results of an European platform screening, conducted mainly in a smoker population, identifies ALK positivity (either by IHC or FISH) as predictor of better OS, whereas in other studies, evaluating never-smoker populations, the presence of ALK translocations resulted to be associated with poor disease free survival (DFS) (25)(26)(27). Similarly, other studies conducted on resected lung cancers highlight the association between ALK positivity and reduced recurrence free survival (RFS) or DFS compared to EGFR+ patients, although no differences in OS have been reported (13,28,29). Multiple factors can potentially jeopardize the prognostic interpretation of ALK fusions in surgical patients: retrospective nature of these studies, heterogeneity of comparator (smokers/never-smokers, oncogenic drivers, different stages) and limited number of ALK+ patients.…”

Section: Alk Rearrangement Frequency (Early and Late Stage)mentioning

confidence: 95%

“…Genomic complexity of lung adenocarcinoma is well characterized, supporting the evidence of different tumor entities with different biology, natural history and clinical behavior (11). Within oncogene-addicted tumors itself, fusions-positive lung cancers retain peculiar aspects, compared to mutation-driven cancers (e.g., EGFR+) (12,13). Thus, a deep understating of ALK fusionsrelated clinical implications in early stage of the disease is mandatory, to precisely determine their prognostic relevance and, consequently, promote therapeutic strategies' implementation that could impact on PFS and, more relevant, on overall survival (OS).…”

Section: Introductionmentioning

confidence: 99%

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Expanding anaplastic lymphoma kinase therapeutic indication to early stage non-small cell lung cancer

Tabbò

Novello

2019

Transl. Lung Cancer Res.

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Oncogene-addicted non-small cell lung cancer (NSCLC) patients have been witnessing overwhelming therapeutic improvements, especially in advanced disease management, due to the advent of more potent tyrosine kinase inhibitors (TKIs). However, the concrete chance to cure anaplastic lymphoma kinase (ALK)-rearranged patients remains prerogative of surgical and peri-operative medical approaches to early disease stage. Clinical investigations in the adjuvant setting of genotype-restricted lung cancers (i.e., EGFR+, ALK+, etc.) are under-represented owing to the need of large patients' enrollment and solid overall survival (OS) data, which solely can show real long-term impact of these therapeutic interventions. Current available radiological and molecular technologies will widely increase the number of surgical early stage patients, including ALK+, spurring the development of rational approaches aimed to prevent disease recurrence and prolong patients' survival. Ongoing clinical trials, evaluating crizotinib and alectinib as adjuvant treatments, will gauge the real impact of TKIs in terms of patients' disease free survival (DFS) and OS; other peri-operative investigations (e.g., neo-adjuvant strategies) will add information about ALK inhibitors' tumor growth restraint capacities and early adaptation mechanisms to ALK targeting. Nevertheless, multiple questions are and will remain unanswered: if should be treated indifferently all ALK+ patients or, alternatively, should be stratified in different risk groups based on the detectable residual disease [i.e., minimal residual disease (MRD) after surgery]; whether ALK inhibitors administration could facilitate the accumulations of persister cells driving resistance mechanisms to targeted therapies; if alternative strategies, as combined treatments targeting different molecular hubs, could enhance disease control and cancer eradication.

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Comparison of Clinicopathological Features and Prognosis between ALK Rearrangements and EGFR Mutations in Surgically Resected Early-stage Lung Adenocarcinoma

Cited by 25 publications

References 50 publications

Mucinous lung adenocarcinoma, particularly referring to EGFR‐mutated mucinous adenocarcinoma

Mucinous lung adenocarcinoma, particularly referring to EGFR‐mutated mucinous adenocarcinoma

Clinical, Conventional CT and Radiomic Feature-Based Machine Learning Models for Predicting ALK Rearrangement Status in Lung Adenocarcinoma Patients

Expanding anaplastic lymphoma kinase therapeutic indication to early stage non-small cell lung cancer

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