Pooled systemic efficacy and safety data from the pivotal phase II studies (NP28673 and NP28761) of alectinib in ALK-positive non-small cell lung cancer [PDF]
et al,, Govindan, Ramaswamy
core +1 more source
ABSTRACT Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are indicated for advanced lung adenocarcinoma patients harboring susceptible EGFR mutations. The aim of this retrospective study was to compare the effectiveness of different generations of EGFR TKIs.
Chia‐Yu Kuo +9 more
wiley +1 more source
Targeting PLK1 potentiates the antitumor efficacy of EGFR-TKIs through inhibiting the JAK1/STAT3 pathway. [PDF]
Li C +7 more
europepmc +1 more source
miR-34a inhibits tumorigenesis of NSCLC via targeting SIRT6.
Libo Ruan +4 more
openalex +1 more source
10MO: Preventing moderate to severe dermatologic adverse events in first-line EGFR-mutant advanced NSCLC treated with amivantamab plus lazertinib: Early success of the COCOON trial [PDF]
N. Girard +19 more
openalex +1 more source
ABSTRACT Non‐small cell lung cancer (NSCLC) is the most common type of lung cancer, with a 5‐year survival rate of less than 20% and a high risk of recurrence despite advances in treatment. This study aimed to identify new therapeutic targets to increase the effectiveness of NSCLC treatments.
Rui‐Shi Wei +5 more
wiley +1 more source
Protein glycosylation in lung cancer from a mass spectrometry perspective
Abstract Lung cancer is a severe disease for which better diagnostic and therapeutic approaches are urgently needed. Increasing evidence implies that aberrant protein glycosylation plays a crucial role in the pathogenesis and progression of lung cancer.
Mirjam Balbisi +2 more
wiley +1 more source
Targeting Mesenchymal-Epidermal Transition (MET) Aberrations in Non-Small Cell Lung Cancer: Current Challenges and Therapeutic Advances. [PDF]
Deng F, Ma W, Wei S.
europepmc +1 more source
Data‐Independent Acquisition Mass Spectrometry in Tumor Classification and Cancer Biomarker Research
Abstract Cancer treatment is far from optimal also because current classification systems do not reflect the complex molecular status of the tumor and its phenotype in sufficient detail. To construct molecular tumor classifiers, omics tools provide complex molecular data reflecting many aspects from genotype to phenotype.
Jan Simonik +3 more
wiley +1 more source

