Non-small cell lung carcinoma (NSCLC): Implications on molecular pathology and advances in early diagnostics and therapeutics.

Continuous revision of the histologic and stage-wise classification of lung cancer by the World Health Organization (WHO) provides the foundation for therapeutic advances by promoting molecular targeted and immunotherapies and ensuring accurate diagnosis. Cancer epidemiologic data provide helpful information for cancer prevention, diagnosis, and management, supporting health-care interventions. Global cancer mortality projections from 2016 to 2060 show that cancer will overtake ischemic heart diseases (IHD) as the leading cause of death (18.9 million) immediately after 2030, surpassing non-small cell lung cancer (NSCLC), which accounts for 85 percent of lung cancers. The clinical stage at the diagnosis is the main prognostic factor in NSCLC therapies. Advanced early diagnostic methods are essential as the initial stages of cancer show reduced mortality compared to the advanced stages. Sophisticated approaches to proper histological classification and NSCLC management have improved clinical efficiency. Although immune checkpoint inhibitors (ICIs) and targeted molecular therapies have refined the therapeutic management of late-stage NSCLC, the specificity and sensitivity of cancer biomarkers should be improved by focusing on prospective studies, followed by their use as therapeutic tools. The liquid biopsy candidates such as circulating tumor cells (CTCs), circulating cell-free tumor DNA (cfDNA), tumor educated platelets (TEP), and extracellular vesicles (EVs) possess cancer-derived biomolecules and aid in tracing: driver mutations leading to cancer, acquired resistance caused by various generations of therapeutic agents, refractory disease, prognosis, and surveillance. [Abstract copyright: © 2022 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd.

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Non-small cell lung carcinoma (NSCLC): Implications on molecular pathology and advances in early diagnostics and therapeutics

Continuous revision of the histologic and stage-wise classification of lung cancer by the World Health Organization (WHO) provides the foundation for therapeutic advances by promoting molecular targeted and immunotherapies and ensuring accurate diagnosis. Cancer epidemiologic data provide helpful information for cancer prevention, diagnosis, and management, supporting health-care interventions. Global cancer mortality projections from 2016 to 2060 show that cancer will overtake ischemic heart diseases (IHD) as the leading cause of death (18.9 million) immediately after 2030, surpassing non-small cell lung cancer (NSCLC), which accounts for 85 percent of lung cancers. The clinical stage at the diagnosis is the main prognostic factor in NSCLC therapies. Advanced early diagnostic methods are essential as the initial stages of cancer show reduced mortality compared to the advanced stages. Sophisticated approaches to proper histological classification and NSCLC management have improved clinical efficiency. Although immune checkpoint inhibitors (ICIs) and targeted molecular therapies have refined the therapeutic management of late-stage NSCLC, the specificity and sensitivity of cancer biomarkers should be improved by focusing on prospective studies, followed by their use as therapeutic tools. The liquid biopsy candidates such as circulating tumor cells (CTCs), circulating cell-free tumor DNA (cfDNA), tumor educated platelets (TEP), and extracellular vesicles (EVs) possess cancer-derived biomolecules and aid in tracing: driver mutations leading to cancer, acquired resistance caused by various generations of therapeutic agents, refractory disease, prognosis, and surveillance