Editorial: Emerging Biomarkers for NSCLC: Recent Advances in Diagnosis and Therapy

Abnormalities in the KRAS Gene and Treatment Options for NSCLC Patients with the G12C Mutation in This Gene-A Literature Review and Single-Center Experience

Mutations in the KRAS gene are among the most common mutations observed in cancer cells, but they have only recently become an achievable goal for targeted therapies. Two KRAS inhibitors, sotorasib and adagrasib, have recently been approved for the treatment of patients with advanced non-small cell lung cancer with the KRAS G12C mutation, while studies on their efficacy are still ongoing. In this work, we comprehensively analyzed RAS gene mutations' molecular background, mutation testing, KRAS inhibitors' effectiveness with an emphasis on non-small cell lung cancer, the impact of KRAS mutations on immunotherapy outcomes, and drug resistance problems. We also summarized ongoing trials and analyzed emerging perspectives on targeting KRAS in cancer patients.

Deep Learning for Lung Cancer Diagnosis, Prognosis and Prediction Using Histological and Cytological Images: A Systematic Review

Lung cancer is one of the deadliest cancers worldwide, with a high incidence rate, especially in tobacco smokers. Lung cancer accurate diagnosis is based on distinct histological patterns combined with molecular data for personalized treatment. Precise lung cancer classification from a single H&E slide can be challenging for a pathologist, requiring most of the time additional histochemical and special immunohistochemical stains for the final pathology report. According to WHO, small biopsy and cytology specimens are the available materials for about 70% of lung cancer patients with advanced-stage unresectable disease. Thus, the limited available diagnostic material necessitates its optimal management and processing for the completion of diagnosis and predictive testing according to the published guidelines. During the new era of Digital Pathology, Deep Learning offers the potential for lung cancer interpretation to assist pathologists' routine practice. Herein, we systematically review the current Artificial Intelligence-based approaches using histological and cytological images of lung cancer. Most of the published literature centered on the distinction between lung adenocarcinoma, lung squamous cell carcinoma, and small cell lung carcinoma, reflecting the realistic pathologist's routine. Furthermore, several studies developed algorithms for lung adenocarcinoma predominant architectural pattern determination, prognosis prediction, mutational status characterization, and PD-L1 expression status estimation.

CircRNA OXCT1 promotes the malignant progression and glutamine metabolism of non-small cell lung cancer by absorbing miR-516b-5p and upregulating SLC1A5

Previous study has demonstrated the high expression of circular RNA 3-oxoacid CoA-transferase 1 (circ-OXCT1) in lung adenocarcinoma tumor tissues. However, the role and possible mechanism of circ-OXCT1 in non-small cell lung cancer (NSCLC) progression was unclear.Quantitative real-time PCR (qRT-PCR), western blotting and immunohistochemistry (IHC) staining assay were performed to detect the expression of circ-OXCT1, microRNA-516b-5p (miR-516b-5p), solute carrier family 1 member 5 (SLC1A5) and other indicated protein markers. Cell proliferation was measured by Cell counting kit 8 (CCK8), colony formation and 5-Ethynyl-2'-deoxyuridine (EdU) assays. Flow cytometry was employed to detect the rate of apoptotic cells. Cell migration and invasion were measured using transwell assay. The relative glutamine uptake and α-ketoglutarate (α-KG) production was determined using commercial kits. Interaction between miR-516b-5p and circ-OXCT1 or SLC1A5 was predicted by bioinformatics analysis and confirmed via luciferase reporter and RNA immunoprecipitation (RIP) assays. In vivo assay was implemented to demonstrate the effect of circ-OXCT1 in tumor growth.Circ-OXCT1 and SLC1A5 were upregulated and miR-516b-5p was downregulated in NSCLC tissues and cells. Functional experiments revealed that circ-OXCT1 silencing suppressed cell proliferation, migration and invasion, but promoted cell apoptosis in vitro. Circ-OXCT1 knockdown repressed tumor formation in vivo. Besides, miR-516b-5p was a target of circ-OXCT1, and miR-516b-5p inhibitor could relieve circ-OXCT1 absence-mediated effects in NSCLC cells. SLC1A5 was identified as a target of miR-516b-5p. Circ-OXCT1 promoted SLC1A5 expression by target binding with miR-516b-5p.Circ-OXCT1 facilitated NSCLC progression via miR-516b-5p-dependent regulation of SLC1A5, which provided a possible circRNA-targeted therapy for NSCLC.

"How Long Have I Got?" in Stage IV NSCLC Patients With at Least 3 Months Up to 10 Years Survival, Accuracy of Long-, Intermediate-, and Short-Term Survival Prediction Is Not Good Enough to Answer This Question

Background

Most lung cancer patients worldwide [stage IV nonsmall cell lung cancer (NSCLC)] have a poor survival: 25%–30% die <3 months. Yet, of those surviving >3 months, 10%–15% (70,000–105,000 new patients worldwide per year) survive (very) long. Surprisingly, little scientific attention has been paid to the question, which factors cause the good prognosis in these NSCLC stage IV long survivors. Therefore, “How long do I still have?” currently cannot be accurately answered. We evaluated in a large group of 737 stage IV NSCLC patients surviving 3.2–120.0 months, the accuracies of short- and long-term survival predictive values of baseline factors, radiotherapy (RT), platinum-based chemotherapy (PBT), and tyrosine kinase inhibitor targeted therapy (TKI-TT).

Methods

This is a noninterventional study of 998 consecutive first-onset stage IV NSCLC patients. A total of 737 (74%) survived 3.2–120.0 months, 47 refused RT, PBT, and TKI-TT. Single and multivariate survival analysis and receiver operating curve (ROC) analysis were used with dead of disease (DOD) or alive with disease (AWD) as endpoints.

Results

The median survival (16.1 months) of 47 patients who refused PBT, RT, and TKI-TT was significantly worse than those with RT, PBT, and/or TKI-TT (23.3 months, HR = 1.60, 95% CI = 1.06–2.42, p = 0.04). Of these latter 690 patients, 42% were females, 58% males, median age 63 years (range 27–85), 1-, 2-, 5-, and 10-year survival rates were 74%, 49%, 16%, and 5%. In total, 16% were alive with disease (AWD) at the last follow-up. Pathology subtype (adenocarcinoma vs. all others), performance score, TNM substage, the number of PBT cycles and TKI-TT had independent predictive value. However, with the multivariate combination of these features, identification results of short-term nonsurvivors and long-term survivors were poor.

Conclusions

In stage IV NSCLC patients with >3 months survival, baseline features, and systemic therapeutic modalities have strong survival predictive value but do not accurately identify short- and long-term survivors. The predictive value of other features and interventions discussed should be investigated in the worldwide very large group of stage IV NSCLC patients with >3 months survival.

High Circulating Sonic Hedgehog Protein Is Associated With Poor Outcome in EGFR-Mutated Advanced NSCLC Treated With Tyrosine Kinase Inhibitors

Introduction

Growing preclinical evidence has suggested that the Sonic hedgehog (Shh) pathway is involved in resistance to tyrosine kinase inhibitor (TKI) therapy for EGFR-mutated (EGFRm) non-small cell lung cancer (NSCLC). However, little is known concerning the prognostic value of this pathway in this context.

Materials and Methods

We investigated the relationship between plasma levels of Shh and EGFRm NSCLC patients’ outcome with EGFR TKIs. We included 74 consecutive patients from two institutions with EGFRm advanced NSCLC treated by EGFR TKI as first-line therapy. Plasma samples were collected longitudinally for each patient and were analyzed for the expression of Shh using an ELISA assay. The activation of the Shh–Gli1 pathway was assessed through immunohistochemistry (IHC) of Gli1 and RT-qPCR analysis of the transcripts of Gli1 target genes in 14 available tumor biopsies collected at diagnosis (baseline).

Results

Among the 74 patients, only 61 had baseline (diagnosis) plasma samples, while only 49 patients had plasma samples at the first evaluation. Shh protein was detectable in all samples at diagnosis (n = 61, mean = 1,041.2 ± 252.5 pg/ml). Among the 14 available tumor biopsies, nuclear expression of Gli1 was observed in 57.1% (8/14) of patients’ biopsies. Shh was significantly (p < 0.05) enriched in youth (age < 68), male, nonsmokers, patients with a PS > 1, and patients presenting more than 2 metastatic sites and L858R mutation. Higher levels of Shh correlated with poor objective response to TKI, shorter progression-free survival (PFS), and T790M-independent mechanism of resistance. In addition, the rise of plasma Shh levels along the treatment was associated with the emergence of drug resistance in patients presenting an initial good therapy response.

Conclusion

These data support that higher levels of plasma Shh at diagnosis and increased levels of Shh along the course of the disease are related to the emergence of TKI resistance and poor outcome for EGFR-TKI therapy, suggesting that Shh levels could stand both as a prognostic and as a resistance biomarker for the management of EGFR-mutated NSCLC patients treated with EGFR-TKI.