Genotyping and genomic profiling of non-small-cell lung cancer: implications for current and future therapies

High throughput virtual screening and validation of Plant-Based EGFR L858R kinase inhibitors against Non-Small cell lung Cancer: An integrated approach Utilizing GC-MS, network Pharmacology, Docking, and molecular dynamics

Lung cancer ranks as the 2nd most common cancer globally. It's the most prevalent cancer in men and the 2nd most common in women. The prominent events in EGFR-mutated non-small-cell lung cancer (NSCLC) include the emergence of the L858R mutation within EGFR exon 21. Despite the promising efficacy of EGFR inhibitors in managing lung cancer, the development of acquired resistance poses a significant hurdle. In the current investigation, we focused on the screening of two phytochemicals, namely Dehydrocostus lactone and Mokkolactone, derived from the Saussurea lappa plant, as potential inhibitors targeting EGFR L858R mutant lung cancer. The chloroform and ethanol extract of the plant demonstrated anti-proliferative activity through the Resazurin chemosensitivity assay, exhibiting an IC50 value of 37.90 ± 0.29 µg/ml with selectivity index 2.4. Through a GC-MS study, we identified 11 phytochemicals for further insilico analysis. These compounds underwent ADMET assessment followed by drug likeliness analysis before being subjected to molecular docking against EGFR L858R, identified through protein-protein interaction network analysis. All phytochemicals exhibited binding energy scores ranging from -6.9 to -8.1 kcal/mol. Dehydrocostus lactone and Mokkolactone were specifically identified for their binding profile. Findings from 100 ns molecular dynamics simulations demonstrated their enhanced stability compared to the reference ligand DJK. This was evident in the root mean square deviation (RMSD) values, ranging from 0.23 ± 0.01 nm to 0.30 ± 0.05 nm, the radius of gyration values, from 1.71 ± 0.01 nm to 1.72 ± 0.01 nm, and the solvent accessible surface area values, from 155.39 ± 2.40 nm2 to 159.32 ± 2.14 nm2. Additionally, favourable characteristics were observed in terms of hydrogen bonding, principal component analysis, and free energy landscape analysis. Examination of their electronic structure via density functional theory revealed efficient properties, with the highest occupied molecular orbital-least unoccupied molecular orbital energy gap values ranging from -3.984 eV to -6.547 eV. Further, in vivo analysis is required to gain a more comprehensive understanding and efficacy of these identified phytochemicals against lung cancer.

Computational-Based Polyphenol Therapy for Nonsmall Cell Lung Cancer: Naringin Coamorphous Systems for Solubility and Bioavailability Enhancement

In this research, we utilized molecular simulations to create co-amorphous materials (CAMs) of ceritinib (CRT) with the objective of improving its solubility and bioavailability. We identified naringin (NRG) as a suitable co-former for CRT CAMs based on binding energy and intermolecular interactions through computational modeling. We used the solvent evaporation method to produce CAMs of CRT and NRG, expecting to enhance both solubility and bioavailability simultaneously. The solid-state characterization using techniques like differential scanning calorimeter, X-ray powder diffraction, and Fourier-transform infrared spectroscopy affirmed the formation of a single amorphous phase and the presence of intermolecular interactions between CRT and NRG in the CAMs. These materials remained physically stable for up to six months under dry conditions at 40 °C. Moreover, the CAMs demonstrated significant improvements in the solubility and dissolution of CRT (specifically in the ratio CRT:NRG 1:2). This, in turn, led to an increase in cytotoxicity, apoptotic cells, and G0/G1 phase inhibition in A549 cells compared to CRT alone. Furthermore, CRT permeability is also improved twofold, as estimated by the everted gut sac method. The enhanced solubility of CAMs also positively affected the pharmacokinetic parameters. When compared to the physical mixture, the CAMs of CRT:NRG 2:1 exhibited a 2.1-fold increase in CRT exposure (AUC0-t) and a 2.4-fold increase in plasma concentration (Cmax).

An Inducible CRISPR-dCas9-Based Transcriptional Repression System for Cancer Therapy

Gene therapy has been adapted for improving malignant tumor treatment. However, pharmacotherapies targeting cancer remain limited and are generally inapplicable for rare disease patients. Oleanolic acid (OA) is a plant-derived triterpenoid that is frequently used in Chinese medicine as a safe but slow-acting treatment for many disorders. Here, the congruent pharmacological activities of OA and CRISPR-dCas9 in targeting AURKA or KDM1A and improving disease-specific prognosis and used a synthetic-biology-inspired design principle to engineer a therapeutic gene circuit that enables a concerted action of both drugs are utilized. In particular, the OA-triggered CRISPR-dCas9 transcriptional repression system rapidly and simultaneously attenuated lung and thyroid cancer. Collectively, this work shows that rationally engineered synthetic gene circuits are capable of treating multifactorial diseases in a synergistic manner by multiplexing the targeting efficiencies of single therapeutics.

Early Detection and Interception of Lung Cancer

Recent advances in lung cancer treatment have led to dramatic improvements in 5-year survival rates. And yet, lung cancer remains the leading cause of cancer-related mortality, in large part, because it is often diagnosed at an advanced stage, when cure is no longer possible. Lung cancer screening (LCS) is essential for intercepting the disease at an earlier stage. Unfortunately, LCS has been poorly adopted in the United States, with less than 5% of eligible patients being screened nationally. This article will describe the data supporting LCS, the obstacles to LCS implementation, and the promising opportunities that lie ahead.

The Effect of Intracranial Control After Intracranial Local Therapy on the Prognosis of Patients with Brain Metastasis of Lung Adenocarcinoma

Purpose

The aim of the present study was to assess the clinical outcomes and prognostic factors of lung adenocarcinoma patients with brain metastases (BMs) after intracranial local therapy.

Patients and Methods

A total of 83 lung adenocarcinoma patients with BMs who underwent craniotomy combined with radiotherapy or intracranial radiotherapy alone were retrospectively analyzed. The intracranial tumor response was determined according to the Response Assessment in Neuro-Oncology of Brain Metastases (RANO-BM) criteria. The median overall survival (OS), intracranial progression-free survival (iPFS), and related prognostic factors were analyzed with the Kaplan‒Meier estimator method and Cox proportional hazards regression model.

Results

Among 83 patients, 20 patients received craniotomy combined with radiotherapy, and 63 patients received intracranial radiotherapy alone. Following intracranial local therapy, 11 patients (13.3%) achieved complete response (CR); among them, 8 patients underwent neurosurgical resection. In addition, 32 patients (38.55%) achieved partial response (PR), 32 patients (38.55%) experienced stable disease (SD), and 8 (9.6%) experienced progressive disease (PD). The median follow-up period was 25.4 months (range 0.8-49.6 months). The median follow-up time for the iPFS was 16.2 months (range 0.6-41.2 months). The median OS, iPFS were 28.2 months and 24.7 months. Epidermal growth factor receptor (EGFR) / anaplastic lymphoma kinase (ALK) mutations (HR 3.216, 95% confidence interval (CI) 1.269-8.150, p = 0.014) and iPFS (HR 0.881, 95% CI 0.836-0.929, p < 0.001) were found to be beneficial factors for OS. An intracranial-tumor CR was associated with a longer iPFS (PR: HR 0.052, 95% CI 0.009-0.297, p = 0.001; SD: HR 0.081, 95% CI 0.025-0.259, p < 0.001; PD: HR 0.216, 95% CI 0.077-0.606, p = 0.004).

Conclusion

Prolonged iPFS was associated with better OS in lung adenocarcinoma patients with BMs following intracranial local therapy, and mutations of EGFR / ALK or an intracranial-tumor CR are independent prognostic factors for prolonged survival.

Pharmacogenetics in Italy: current landscape and future prospects

Pharmacogenetics investigates sequence of genes that affect drug response, enabling personalized medication. This approach reduces drug-induced adverse reactions and improves clinical effectiveness, making it a crucial consideration for personalized medical care. Numerous guidelines, drawn by global consortia and scientific organizations, codify genotype-driven administration for over 120 active substances. As the scientific community acknowledges the benefits of genotype-tailored therapy over traditionally agnostic drug administration, the push for its implementation into Italian healthcare system is gaining momentum. This evolution is influenced by several factors, including the improved access to patient genotypes, the sequencing costs decrease, the growing of large-scale genetic studies, the rising popularity of direct-to-consumer pharmacogenetic tests, and the continuous improvement of pharmacogenetic guidelines. Since EMA (European Medicines Agency) and AIFA (Italian Medicines Agency) provide genotype information on drug leaflet without clear and explicit clinical indications for gene testing, the regulation of pharmacogenetic testing is a pressing matter in Italy. In this manuscript, we have reviewed how to overcome the obstacles in implementing pharmacogenetic testing in the clinical practice of the Italian healthcare system. Our particular emphasis has been on germline testing, given the absence of well-defined national directives in contrast to somatic pharmacogenetics.

Ultra-fast UPLC-MS/MS approach for estimating X-376 in human liver microsomes: Evaluation of metabolic stability via in silico software and in vitro analysis

X-376 is a novel anaplastic lymphoma kinase (ALK) inhibitor that is capable of penetrating the blood brain barrier. This makes it suitable for use in patients with ALK-positive non-small cell lung cancer (NSCLC) who have metastases in the central nervous system. This study developed a highly sensitive, fast, eco-friendly, and reliable UPLC-MS/MS approach to quantify X-376 in human liver microsomes (HLMs). This approach was used to evaluate X-376's metabolic stability in HLMs in vitro. The UPLC-MS/MS analytical technique validation followed US-FDA bio-analytical method validation guidelines. StarDrop software, containing P450 metabolic and DEREK modules, was utilized to scan X-376's chemical structure for metabolic lability and hazardous warnings. X-376 and Encorafenib (ENF as internal standard) were resoluted on the Eclipse Plus C18 column utilizing an isocratic mobile phase method. The X-376 calibration curve was linear from 1 to 3000 ng/mL. The precision and accuracy of this study's UPLC-MS/MS approach were tested for intra- and inter-day measurements. Inter-day accuracy was -1.32% to 9.36% while intra-day accuracy was -1.5% to 10.00%. The intrinsic clearance (Clint) and in vitro half-life (t1/2) of X-376 were 59.77 mL/min/kg and 13.56 min. The high extraction ratio of X-376 supports the 50 mg twice-daily dose for ALK-positive NSCLC and CNS metastases patients. In silico software suggests that simple structural changes to the piperazine ring or group substitution in drug design may improve metabolic stability and safety compared to X-376.

Evolving Precision First-Line Systemic Treatment for Patients with Unresectable Non-Small Cell Lung Cancer

First-line systemic therapy for patients with advanced or metastatic non-small cell lung cancer (NSCLC) has rapidly evolved over the past two decades. First, molecularly targeted therapy for a growing number of gain-of-function molecular targets has been shown to improve progression-free survival (PFS) and overall survival (OS) with favorable toxicity profiles compared to platinum-containing chemotherapy and can be given as first-line systemic therapy in ~25% of patients with NSCLC. Actionable genetic alterations include EGFR, BRAF V600E, and MET exon 14 splicing site-sensitizing mutations, as well as ALK-, ROS1-, RET-, and NTRK-gene fusions. Secondly, inhibitors of programmed cell death protein 1 or its ligand 1 (PD-1/L1) such as pembrolizumab, atezolizumab, or cemiplimab monotherapy have become a standard of care for ~25% of patients with NSCLC whose tumors have high PD-L1 expression (total proportion score (TPS) ≥50%) and no sensitizing EGFR/ALK alterations. Lastly, for the remaining ~50% of patients who are fit and whose tumors have no or low PD-L1 expression (TPS of 0-49%) and no sensitizing EGFR/ALK aberrations, platinum-containing chemotherapy with the addition of a PD-1/L1 inhibitor alone or in combination of a cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibitor improves PFS and OS compared to chemotherapy alone. The objectives of this review are to summarize the current data and perspectives on first-line systemic treatment in patients with unresectable NSCLC and propose a practical algorithm for implementing precision biomarker testing at diagnosis.

Using Vision Transformer for high robustness and generalization in predicting EGFR mutation status in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma is a common cause of cancer-related deaths worldwide, and accurate EGFR genotyping is crucial for optimal treatment outcomes. Conventional methods for identifying the EGFR genotype have several limitations. Therefore, we proposed a deep learning model using non-invasive CT images to predict EGFR mutation status with robustness and generalizability.

METHODS

A total of 525 patients were enrolled at the local hospital to serve as the internal data set for model training and validation. In addition, a cohort of 30 patients from the publicly available Cancer Imaging Archive Data Set was selected for external testing. All patients underwent plain chest CT, and their EGFR mutation status labels were categorized as either mutant or wild type. The CT images were analyzed using a self-attention-based ViT-B/16 model to predict the EGFR mutation status, and the model's performance was evaluated. To produce an attention map indicating the suspicious locations of EGFR mutations, Grad-CAM was utilized.

RESULTS

The ViT deep learning model achieved impressive results, with an accuracy of 0.848, an AUC of 0.868, a sensitivity of 0.924, and a specificity of 0.718 on the validation cohort. Furthermore, in the external test cohort, the model achieved comparable performances, with an accuracy of 0.833, an AUC of 0.885, a sensitivity of 0.900, and a specificity of 0.800.

CONCLUSIONS

The ViT model demonstrates a high level of accuracy in predicting the EGFR mutation status of lung adenocarcinoma patients. Moreover, with the aid of attention maps, the model can assist clinicians in making informed clinical decisions.

A novel subtype based on driver methylation-transcription in lung adenocarcinoma

AIMS

To identify driver methylation genes and a novel subtype of lung adenocarcinoma (LUAD) by multi-omics and elucidate its molecular features and clinical significance.

METHODS

We collected LUAD patients from public databases, and identified driver methylation genes (DMGs) by MethSig and MethylMix algrothms. And novel driver methylation multi-omics subtypes were identified by similarity network fusion (SNF). Furthermore, the prognosis, tumor microenvironment (TME), molecular features and therapy efficiency among subtypes were comprehensively evaluated.

RESULTS

147 overlapped driver methylation were identified and validated. By integrating the mRNA expression and methylation of DMGs using SNF, four distinct patterns, termed as S1-S4, were characterized by differences in prognosis, biological features, and TME. The S2 subtype showed unfavorable prognosis. By comparing the characteristics of the DMGs subtypes with the traditional subtypes, S3 was concentrated in proximal-inflammatory (PI) subtype, and S4 was consisted of terminal respiratory unit (TRU) subtype and PI subtype. By analyzing TME and epithelial mesenchymal transition (EMT) features, increased immune infiltration and higher expression of immune checkpoint genes were found in S3 and S4. While S4 showed higher EMT score and expression of EMT associated genes, indicating S4 may not be as immunosensitive as the S3. Additionally, S3 had lower TIDE and higher IPS score, indicating its increased sensitivity to immunotherapy.

CONCLUSION

The driver methylation-related subtypes of LUAD demonstrate prognostic predictive ability that could help inform treatment response and provide complementary information to the existing subtypes.

Pneumonic-type lung adenocarcinoma with KRAS G12V mutation and sustained response to Afatinib

BACKGROUND

Pneumonic-type lung adenocarcinoma (P-ADC) is a rare and challenging subtype of primary lung cancer that can be difficult to distinguish from pneumonia based on radiological images. Furthermore, no drugs are currently available that specifically target KRAS G12V.

CASE PRESENTATION

Here we report a case of P-ADC with typical and informative imaging features throughout the course of the disease, including patchy shadows, high-density lesions with aerated bronchus, diffuse ground-glass opacities, and nodular shadows from computed tomography (CT) scan. The KRAS G12V mutation was detected using Next-generation sequencing (NGS). An individualized Afatinib-based therapeutic schedule was prescribed and achieved sustained response after multiple lines of treatment had failed.

CONCLUSION

Our case highlights the typical and dynamic changes in imaging features of P-ADC and provides an indicative treatment strategy for KRAS G12V-mutated lung adenocarcinoma.

Clinical efficacy and safety analysis of aumolertinib in real-world treatment of EGFR-mutated advanced non-small-cell lung cancer

Background: This study aims to determine the efficacy and safety profile of aumolertinib in the real-word treatment setting for advanced non-small-cell lung cancer (NSCLC) patients harboring epidermal growth factor receptor (EGFR) mutations. Methods: We retrospectively analyzed the clinical data of 173 EGFR-mutated advanced NSCLC patients who received aumolertinib treatment at Henan Cancer Hospital from April 2020 to December 2022. Progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan-Meier survival curves, while a Cox regression model was used for multifactorial analysis and prognostic factor assessment. Results: Among patients administered first-line aumolertinib (n = 77), the objective remission rate (ORR) of 77.92% was observed, along with a disease control rate (DCR) of 100%. The median progression-free survival (mPFS) was 24.97 months, which did not reach the median overall survival (mOS). The patients treated with aumolertinib after progression on prior EGFR-tyrosine kinase inhibitor (TKI) therapy (n = 96) exhibited an ORR of 46.88%, a DCR of 89.58%, an mPFS of 15.17 months, and an mOS of 21.27 months. First-line treatment multivariate Cox regression analysis demonstrated a statistically significant impact of elevated creatine kinase on PFS (p = 0.016) and a similar significant influence of co-mutation on OS (p = 0.034). Furthermore, subsequent-line treatment multivariate Cox regression analysis showed a statistically significant impact of elevated creatine kinase on median PFS (p = 0.026) and a significant effect on the number of metastatic organs (p = 0.017), co-mutation (p = 0.035), and elevated creatine kinase (p = 0.014) on median OS. Conclusion: Aumolertinib has shown clinical significance and can safely be used in the real-world setting for patients with EGFR mutation-positive NSCLC.

Habitat-Based Radiomics for Predicting EGFR Mutations in Exon 19 and 21 From Brain Metastasis

RATIONALE AND OBJECTIVES

To explore and externally validate habitat-based radiomics for preoperative prediction of epidermal growth factor receptor (EGFR) mutations in exon 19 and 21 from MRI imaging of non-small cell lung cancer (NSCLC)-originated brain metastasis (BM).

METHODS

A total of 170, 62 and 61 patients from center 1, center 2 and center 3, respectively were included. All patients underwent contrast-enhanced T1-weighted (T1CE) and T2-weighted (T2W) MRI scans. Radiomics features were extracted from the tumor active (TA) and peritumoral edema (PE) regions in each MRI slice. The most important features were selected by the least absolute shrinkage and selection operator regression to develop radiomics signatures based on TA (RS-TA), PE (RS-PE) and their combination (RS-Com). Receiver operating characteristic (ROC) curve analysis was performed to access performance of radiomics models for both internal and external validation cohorts.

RESULTS

10, four and six most predictive features were identified to be strongly associated with the EGFR mutation status, exon 19 and exon 21, respectively. The RSs derived from the PE region outperformed those from the TA region for predicting the EGFR mutation, exon 19 and exon 21. The RS-Coms generated the highest performance in the primary training (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.955 vs. 0.946 vs. 0.928), internal validation (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.879 vs. 0.819 vs. 0.882), external validation 1 (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.830 vs. 0.825 vs. 0.822), and external validation 2 (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.812 vs. 0.818 vs. 0.800) cohort.

CONCLUSION

The developed habitat-based radiomics model can be used to accurately predict the EGFR mutation subtypes, which may potentially guide personalized treatments for NSCLC patients with BM.

Efficacy of befotertinib in non-small cell lung cancer harboring uncommon compound EGFR mutations G719X and S768I: a case report

The discovery of epidermal growth factor receptor (EGFR) somatic mutations and the availability of tyrosine kinase inhibitors (TKIs) as targeted therapies have transformed the treatment landscape for advanced non-small cell lung cancer (NSCLC). p.G719X and p.S768I mutations, often present in the form of complex mutations, are considered rare. This study firstly reported the treatment outcome of a locally advanced unresectable NSCLC patient with a rare complex EGFR p.G719X/p.S768I mutations who received befotertinib. After treatment, the patient achieved partial response (PR), and no severe adverse events were observed. This case report supported befotertinib as a promising treatment option for advanced NSCLC patients with the rare p.G719X/p.S768I complex mutations.

High expression of B7-H3 on monocyte/macrophages in tumor microenvironment promotes lung cancer progression by inhibiting apoptosis

Monocyte/macrophages constitute a significant population of tumor-infiltrating immune cells and play a crucial role in tumor growth, invasion, and metastasis. B7-H3, has immune regulatory functions, however, it is unclear whether B7-H3 expressed on monocyte/macrophages plays a significance role in tumor progression. We found B7-H3 was high-expressed on monocyte/macrophages in tumor microenvironment compared with adjacent tissues in lung cancer, and its expression level was positively correlated with the number of monocyte/macrophages. Furthermore, the expression of B7-H3 was related to clinical stage and lymph node metastasis. Moreover, miR-29a-3p negatively regulated B7-H3, and the expression of B7-H3 on THP-1-derived macrophages was regulated by secreting exosomes containing miR-29a-3p. In addition, knockdown of B7-H3 promoted macrophage apoptosis under hypoxia. Mechanistically, B7-H3 enhanced the antiapoptotic ability of macrophage by up-regulating HIF-1ɑ via activating NF-κB. Taken together, these results imply that B7-H3 as a therapeutic target could hold promise for enhancing anti-tumor immune responses in individuals diagnosed with lung cancer.

Case report: First evidence of impressive efficacy of modulated dose selpercatinib in a young Caucasian with ANK3-RET fusion-positive NSCLC

Over the past decade, molecular characterization has led to change the management of advanced non-small cell lung cancer (NSCLC) harboring driver mutations. Rearranged during transfection (RET) gene fusions, occurring in 1% to 2% of NSCLC, have emerged as an oncogenic druggable target. Systemic targeted therapies with highly selective RET inhibitors (RETi), selpercatinib and pralsetinib, represent a recent clinical breakthrough. While the development of RETi has improved survival, with their increasing use, it is crucial to be aware of the risks of rare but serious adverse events (AEs). A particular challenge for clinicians in applying targeted therapies is not only diagnosing but also interpreting rare mutations. Herein, we report a case of a 43-year-old Caucasian advanced NSCLC patient diagnosed with a rare RET gene fusion, ANK3::RET, identified with Next Generation Sequencing (NGS). Selpercatinib has been initiated at the recommended initial dose after one incomplete chemotherapy cycle due to a severe infusion reaction, but it subsequently required a dose adjustment following grade 3 (G3) AEs. During treatment, we used a particular selpercatinib dosage (160 mg in the morning and 80 mg in the evening) with good tolerance and without compromising effectiveness. Our finding broadens the range of RET fusion types in not-Asian NSCLC. To the best of our knowledge, our case demonstrates, for the first time, a clinical and radiological response to frontline highly selective RETi selpercatinib, expanding the spectrum of potential oncogenic RET fusion partners in newly diagnosed NSCLC patients. Furthermore, to our knowledge, this is the first case describing a RET fusion-positive (RET+) NSCLC patient treated with a modified selpercatinib dosage outside the drug data sheet and demonstrating a safe and effective use.

The role of sex and gender in the diagnosis and treatment of lung cancer: the 6th ICAPEM Annual Symposium

The incidence and mortality of lung cancer in women are rising, with both increasing by 124% between 2003 and 2019. The main risk factor for lung cancer is tobacco use, but indoor radon gas exposure is one of the leading causes in nonsmokers. The most recent evidence demonstrates that multiple factors can make women more susceptible to harm from these risk factors or carcinogens. For this consensus statement, the Association for Lung Cancer Research in Women (ICAPEM) invited a group of lung cancer experts to perform a detailed gender-based analysis of lung cancer. Clinically, female patients have different lung cancer profiles, and most actionable driver alterations are more prevalent in women, particularly in never-smokers. Additionally, the impact of certain therapies seems to be different. In the future, it will be necessary to carry out specific studies to improve the understanding of the role of certain biomarkers and gender in the prognosis and evolution of lung cancer.

Cellular Mass Response to Therapy Correlates With Clinical Response for a Range of Malignancies

PURPOSE

Cancer patients with advanced-stage disease have poor prognosis, typically having limited options for efficacious treatment, and genomics-based therapy guidance continues to benefit only a fraction of patients. Next-generation ex vivo approaches, such as cell mass-based response testing (MRT), offer an alternative precision medicine approach for a broader population of patients with cancer, but validation of clinical feasibility and potential impact remain necessary.

MATERIALS AND METHODS

We evaluated the clinical feasibility and accuracy of using live-cell MRT to predict patient drug sensitivity. Using a unified measurement workflow with a 48-hour result turnaround time, samples were subjected to MRT after treatment with a panel of drugs in vitro. After completion of therapeutic course, clinical response data were correlated with MRT-based predictions of outcome. Specimens were collected from 104 patients with solid (n = 69) and hematologic (n = 35) malignancies, using tissue formats including needle biopsies, malignant fluids, bone marrow aspirates, and blood samples. Of the 81 (78%) specimens qualified for MRT, 41 (51%) patients receiving physician-selected therapies had treatments matched to MRT.

RESULTS

MRT demonstrated high concordance with clinical responses with an odds ratio (OR) of 14.80 (P = .0003 [95% CI, 2.83 to 102.9]). This performance held for both solid and hematologic malignances with ORs of 20.67 (P = .0128 [95% CI, 1.45 to 1,375.57]) and 8.20 (P = .045 [95% CI, 0.77 to 133.56]), respectively. Overall, these results had a predictive accuracy of 80% (P = .0026 [95% CI, 65 to 91]).

CONCLUSION

MRT showed highly significant correlation with clinical response to therapy. Routine clinical use is technically feasible and broadly applicable to a wide range of samples and malignancy types, supporting the need for future validation studies.

m6A modification patterns are associated with copy number burden and tumor immune landscape in thyroid cancer

BACKGROUND

The association involving N6-methyladenosine (m6A) modification, molecular subtype and specific immune cell group in tumor microenvironment has been the focus of recent studies. The underlying function of m6A modification in thyroid cancer (TC) remains elusive.

METHODS

The m6A modification regulations, molecular character and tumor immune profile of 461 TC patients were explored and then the correlation between them were comprehensively evaluated. The m6Ascore was established using principal component analysis (PCA) to quantify the m6A pattern of individual TC patients. The prognostic significance of the m6Ascore was evaluated by multivariate Cox regression analysis.

RESULTS

Four m6Aclusters (mc1, 2, 3, 4)-characterized by differences in extent of aneuploidy, expression of immunomodulatory genes, mRNA or lncRNA expression pattern and prognosis were identified. T Preliminary validation of m6Ascore was a potential independent prognostic factor of TC involving in mc3. Finally, the prognostic value of the m6Ascore and its association with copy number variation (CNV) and tumor immune microenvironment (TIME) of TC in mc3 were verified.

CONCLUSIONS

The correlation between m6A modification, the copy number burden and tumor immune landscape in TC was demonstrated. A m6Acluster-mc3 with low m6Ascore and high CNV molecular subtype was identified with poor clinical prognosis, low infiltrating immunocyte and weak effector T cell. A three-gene clinical prognosis model for TC based on 4 m6a cluster expression was established. Understanding of TIME is enhanced by comprehensive assessment of m6A patterns in individual TC patients and gives a new insight toward improved immunotherapy strategies for TC cancer patients.

Molecular profiling and feasibility using a comprehensive hybrid capture panel on a consecutive series of non-small-cell lung cancer patients from a single centre

BACKGROUND

Targeted next-generation sequencing (NGS) is recommended to screen actionable genomic alterations (GAs) in patients with non-small-cell lung cancer (NSCLC). We determined the feasibility to detect actionable GAs using TruSight™ Oncology 500 (TSO500) in 200 consecutive patients with NSCLC.

MATERIALS AND METHODS

DNA and RNA were sequenced on an Illumina® NextSeq 550 instrument and processed using the TSO500 Docker pipeline. Clinical actionability was defined within the molecular tumour board following European Society for Medical Oncology (ESMO) guidelines for oncogene-addicted NSCLC. Overall survival (OS) was estimated as per the presence of druggable GAs and treatment with targeted therapy.

RESULTS

Most patients were males (69.5%) and former or current smokers (86.5%). Median age was 64 years. The most common histological type and tumour stage were lung adenocarcinoma (81%) and stage IV (64%), respectively. Sequencing was feasible in most patients (93.5%) and actionable GAs were found in 26.5% of patients. A high concordance was observed between single-gene testing and TSO500 NGS panel. Patients harbouring druggable GAs and receiving targeted therapy achieved longer OS compared to patients without druggable GAs. Conversely, patients with druggable GAs not receiving targeted therapy had a trend toward shorter OS compared with driver-negative patients.

CONCLUSIONS

Hybrid capture sequencing using TSO500 panel is feasible to analyse clinical samples from patients with NSCLC and is an efficient tool for screening actionable GAs.

The Prognosis of Advanced Non-Small Cell Lung Cancer Patients with Precision-Targeted Therapy Guided by NGS Testing or Routine Testing

Purpose

We aim to observe the potential survival benefits of driver gene-guided targeted therapy in advanced non-small cell lung cancer (NSCLC) patients compared to non-targeted therapy. Additionally, the study aims to assess whether Next-generation sequencing technology (NGS)-guided targeted therapy can provide survival advantages for advanced NSCLC patients compared to conventional Epidermal growth factor receptor (EGFR)/anaplastic lymphoma kinase (ALK) gene detection.

Methods

Clinical data, genetic testing results, and treatment information of 1663 advanced lung cancer patients diagnosed by pathology from January 2013 to June 2019 in Jiangsu University Affiliated Lianyungang Hospital were collected. Propensity score matching survival analysis was used to evaluate the differences in overall survival(OS) between groups.

Results

In the unadjusted survival curve, targeted therapy patients had significantly longer median OS than non-targeted therapy patients (28.3 months vs 15.4 months, Hazard ratio (HR) = 0.5426, 95% confidence interval (CI) 0.4768-0.6176, P < 0.0001); the conclusion was the same after propensity score matching analysis, with targeted therapy group patients having significantly prolonged OS median (27.5 months vs 14.8 months, HR = 0.5572, 95% CI 0.4796-0.6474, P < 0.0001). In the unadjusted survival curve, the NGS group had a significantly prolonged median OS compared to the conventional gene detection group (23.4 months vs 21.2 months, HR = 1.243, 95% CI = 1.017-1.519, P = 0.0495). However, after propensity score matching analysis, no statistically significant difference existed in the median OS between the two patient groups (23.1 months vs 21.5 months, HR = 1.288, 95% CI = 0.9557-1.735, P = 0.0926). Further analysis demonstrated no advantage in the five-, three-, and two-year survival rates of the NGS group compared to conventional gene detection group patients. However, the one-year survival rate of the NGS group was significantly increased (83.2% vs 68.1%, HR = 0.4890, 95% CI = 0.3170-0.7544, P = 0.0015).

Conclusion

Driver gene-guided targeted precision therapy significantly prolonged the median OS of advanced NSCLC patients compared to non-targeted therapy. NGS detection did not improve the median OS of advanced NSCLC patients compared to conventional EGFR/ALK gene detection but increased the one-year survival rate of patients.

Factors leading to disparity in lung cancer diagnosis among black/African American communities in the USA: a qualitative study

OBJECTIVE

This study has two objectives: first, to explore the diagnostic experiences of black/African American (BAA) patients with lung cancer to pinpoint pitfalls, suboptimal experiences and instances of discrimination leading to disparities in outcomes compared with patients of other ethnic backgrounds, especially white patients. The second objective is to identify the underlying causes contributing to health disparities in the diagnosis of lung cancer among BAA patients.

METHODS

We employed a phenomenological research approach, guiding in-depth interviews with patients self-identifying as BAA diagnosed with lung cancer, as well as caregivers, healthcare professionals and community advocates knowledgeable about BAA experiences with lung cancer. We performed thematic analysis to identify experiences at patient, primary care and specialist levels. Contributing factors were identified using the National Institute of Minority Health and Health Disparities (NIMHD) health disparity model.

RESULTS

From March to November 2021, we conducted individual interviews with 19 participants, including 9 patients/caregivers and 10 providers/advocates. Participants reported recurring and increased pain before seeking treatment, treatment for non-cancer illnesses, delays in diagnostic tests and referrals, poor communication and bias when dealing with specialists and primary care providers. Factors contributing to suboptimal experiences included reluctance by insurers to cover costs, provider unwillingness to conduct comprehensive testing, provider bias in recommending treatment, high healthcare costs, and lack of healthcare facilities and qualified staff to provide necessary support. However, some participants reported positive experiences due to their insurance, availability of services and having an empowered support structure.

CONCLUSIONS

BAA patients and caregivers encountered suboptimal experiences during their care. The NIMHD model is a useful framework to organise factors contributing to these experiences that may be leading to health disparities. Additional research is needed to fully capture the extent of these experiences and identify ways to improve BAA patient experiences in the lung cancer diagnosis pathway.

Comparison of Different ROS1 Immunohistochemistry Clones and Consistency with Fluorescence In Situ Hybridization Results in Non-Small Cell Lung Carcinoma

Background

The study of ROS1 rearrangement in non-small cell lung carcinoma (NSCLC) has gained importance as it enables personalized treatment of NSCLC with tyrosine kinase inhibitors. Therefore, it is important that the ROS1 assessment tests become more standardized. In this study, we compared the two immunohistochemistry (IHC) antibodies (D4D6 and SP384 clones) and consistency with the fluorescence in situ hybridization (FISH) results in NSCLC.

Aims

To investigate the effectiveness of the commonly used two IHC antibodies (SP384 and D4D6 clones) to detect ROS1 rearrangement in NSCLC.

Study Design

A retrospective cohort study.

Methods

The study included 103 samples diagnosed with NSCLC, confirmed using IHC and FISH ROS1 results (14 positives, four discordant, and 85 consecutive negatives), with sufficient tissue samples (≥ 50 tumor cells). All samples were initially tested with ROS1-IHC antibodies (D4D6 and SP384 clones); their ROS1 status was then analyzed using the FISH method. Finally, samples with discordant IHC and FISH results were confirmed using the reverse transcription polymerase chain reaction method.

Results

The sensitivity of SP384 and D4D6 clones of ROS1 antibody was 100% with a ≥ 1 + cut-off. When the ≥ 2 + cut-off was used, the sensitivity rate for the SP384 clone was 100%, whereas the sensitivity for the D4D6 clone was 42.86%. ROS1 FISH rearranged samples were positive for both clones, but SP384 had generally higher intensity than D4D6. The mean IHC score was + 2 for SP384 and + 1.17 for D4D6. SP384 mostly tended to have a higher IHC score intensity, which made the evaluation easier than D4D6. SP384 has a higher sensitivity than D4D6. However, false positives were found in both clones. There was no significant correlation between ROS1 FISH-positivity percentage with SP384 (p = 0.713, p = 0.108) and D4D6 (p = 0.26, p = -0.323) IHC staining intensity. The staining patterns of both clones were similar (homogeneity/heterogeneity).

Conclusion

Our findings show that the SP384 clone is more sensitive than D4D6. However, SP384 can also cause false positive results like D4D6. Knowing the variable diagnostic performance of different ROS1 antibodies before using them in clinical applications is necessary. IHC-positive results should be confirmed using FISH.

Detection of the gene mutation of epidermal growth factor receptor in lung adenocarcinoma by radiomic features from a small amount of PET data

OBJECTIVE

The purpose of this work was to identify the potential mutation of epidermal growth factor receptor in nonsmall cell adenocarcinoma by noninvasive method, and to explore whether the same or better effect can be achieved using a small amount of single-mode PET image data.

METHOD

A total of 115 patients were recruited and the results of their 18F-FDG PET images and gene detection after resection were obtained; 117 original radiation features and 744 wavelet transform features were extracted from PET images. Several methods were used to reduce the dimension of the data, and four classifier models were established to classify it. The above process was repeated to reduce the total amount of data and the area under the receiver operating characteristic curve (AUC) value that changed with the reduction of the data and the stability of the results was recorded.

RESULTS

The classifier with the best comprehensive performance under this dataset was logistic regression, whose AUC value is 0.843. And similar results can be obtained from only 30 cases of data.

CONCLUSION

A similar or better result could be achieved using a small number of single-mode PET images. In addition, significant results could be obtained using only the PET images of 30 patients.

A computational-based approach to fabricate Ceritinib co-amorphous system using a novel co-former Rutin for bioavailability enhancement

In this study, we used molecular simulations to design Ceritinib (CRT) co-amorphous materials (CAMs) with concurrent improvement in solubility and bioavailability. Computational modeling enabled us to select the co-former by estimating the binding energy and intermolecular interactions. Rutin (RTH) was selected as a co-former for CRT CAMs using the solvent evaporation method to anticipate simultaneous improvement of solubility and bioavailability. The solid state characterization using DSC, XRPD, FT-IR, and a significant shift in Gordon Taylor experimental Tg values of co-amorphous materials revealed single amorphous phase formation and intermolecular interactions between CRT and RTH. The co-amorphous materials exhibited physical stability for up to 4 months under dry conditions (40 °C). Further, co-amorphous materials maintained the supersaturation for 24 hrs and improved solubility as well as dissolution of CRT. CRT:RTH 1:1 CAMs improved the permeability of CRT by 2 fold, estimated by employing the everted gut sac method. The solubility advantage of CAMs was also reflected in pharmacokinetic parameters, with a 3.1-fold and 2-fold improvement of CRT:RTH 2:1 in CRT exposure (AUC 0-t) and plasma concentration (Cmax) compared to the physical mixture, respectively.

Synergistic markers based on inter-covariate association estimate treatment option with lower propensity to covariates

Background

Propensity constitutes a common problem in identifying clinical outcome prediction model whose covariates include the treatment option, which is assumed to be randomly assigned but indeed dependent of other covariates in the training data. The genuine effect of treatment option cannot be elucidated under the influence of propensity. Existing approaches, such as matched-pairs study design, still cannot solve the problem for imbalanced or small datasets.

Methods

This work proposed an anti-propensity estimate of treatment option, which is generated by support vector classifier based on two synergistic markers that represent the lower and upper limits of inter-covariate association level. The algorithm for generating the synergistic markers was illustrated and the performance was evaluated on a public dataset of gene expression levels, which were obtained from surgically excised tumor samples in non-small cell lung cancer (NSCLC) patients where treatment option, i.e., adjuvant therapy or not, was known.

Results

Six covariates represented by the expression levels of ZNF217, ERCC3, PMS1, PIK3CB, BARD1, and MAPK1, were selected to generate two synergistic markers and classifier for estimating the adjuvant therapy option with substantially attenuated propensity. The estimation accuracy attained an area under the receiver-operating characteristics curve, 0.78, in the test set.

Conclusions

The proposed synergistic markers demonstrated a parsimonious and anti-propensity estimation of treatment option, which is ready for the further evaluation and application in the clinical outcome prediction model.

Successful treatment of lung adenocarcinoma complicated with a rare compound EGFR mutation L833V/H835L using aumolertinib: a case report and literature review

Background: The deletion of exon 19 and the Leu858Arg mutation of exon 21 are the most frequently observed mutations in the epidermal growth factor receptor (EGFR) gene, and patients with these mutations have shown significant benefits from EGFR-tyrosine kinase inhibitors (TKIs). However, there exists a small subgroup of patients with uncommon/rare mutations of EGFR, including compound mutations, which display a high degree of heterogeneity in terms of clinical features and variable sensitivities to EGFR-TKIs. The understanding of these uncommon mutations and their response to targeted therapy is still unclear and requires further investigation. Case presentation: We presented a case of a never-smoking patient with lung adenocarcinoma and brain metastasis. Initially, she received chemotherapy plus immune checkpoint inhibitor as first-line therapy as no EGFR mutations were detected by amplification-refractory mutation system-polymerase chain reaction. However, disease progressed rapidly. Subsequently, next-generation sequencing was carried out and revealed a rare compound mutation, L833V/H835L, in exon 21 of EGFR. As a result, she was switched to second-line therapy with the third-generation TKI aumolertinib, which demonstrated good efficacy. The patient was evaluated for a remarkable progression-free survival of 18 months and an overall survival of 29 months. Conclusion: The present study supports that aumolertinib might be a good treatment option for advanced NSCLC patients with EGFR L833V/H835L mutation, particularly in patients with brain metastasis. Furthermore, conducting a comprehensive screening for gene mutations is crucial in effectively identifying potential oncogenic driver mutations and guiding mutation-targeted therapy decisions in clinical practice.

Prediction of prognosis and immunotherapy response in lung adenocarcinoma based on CD79A, DKK1 and VEGFC

Background

Tumor immune microenvironment (TIME) is crucial for tumor initiation, progression, and metastasis; however, its relationship with lung adenocarcinoma (LUAD) is unknown. Traditional predictive models screen for biomarkers that are too general and infrequently associated with immune genes.

Methods

RNA sequencing data of LUAD patients and immune-related gene sets were retrieved from public databases. Using the common genes shared by The Cancer Genome Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort), differential gene expression analysis, survival analysis, Lasso regression analysis, and univariate and multivariate Cox regression analyses were performed to generate a novel risk score model. LUAD cohort in International Cancer Genome Consortium (ICGC), GSE68465 cohort in Gene Expression Omnibus (GEO) and an immunohistochemical assay were used to validate the key genes constructed risk score. The LUAD-related prognosis, clinical indicators, immune infiltrate characteristics, response to immunotherapy, and response to chemotherapeutic agents in different risk groups were evaluated by CIBERSORT, ImmuCellAI, pRRophetic and other tools.

Results

The risk score model was constructed using CD79a molecule (CD79A), Dickkopf WNT signaling pathway inhibitor 1 (DKK1), and vascular endothelial growth factor C (VEGFC). High risk score was identified as a negative predictor for overall survival (OS) in subgroup analyses with tumor stage, TNM classification, therapy outcome, and ESTIMATE scores (P < 0.05). Low risk score was positively associated with plasma cells, memory B cells, CD8 T cells, regulatory T cells and γδT cells (P < 0.05). In low-risk group, programmed cell death 1 receptor (PD1), cytotoxic T-lymphocyte associated protein 4 (CTLA4), and lymphocyte activating 3 (LAG3) and indoleamine 2,3-dioxygenase (IDO) were more robustly expressed (P < 0.05). The treatment responses of immune checkpoint blockade (ICB) therapy and chemotherapy were likewise superior in low-risk group (P < 0.05). In immunohistochemical analysis, the tumor group had significantly higher levels of CD79A, DKK1, and VEGFC than the adjacent normal group (P < 0.01).

Conclusions

CD79A, DKK1 and VEGFC are important differential genes related to LUAD, risk score could reliably predict prognosis, composition of TIME and immunotherapy responses in LUAD patients. The excellent performance of the risk model shows its strong and broad application potential.

Primary Pulmonary Carcinomas with Spindle and/or Giant Cell Features: A Review with Emphasis in Classification and Pitfalls in Diagnosis

Primary carcinomas of the lung are vastly represented by the conventional types of adenocarcinomas or squamous cell carcinomas. However, there are other types of non-small cell carcinomas that although uncommon represent a meaningful group that often pose a problem not only in diagnosis but also in classification. Spindle cell and/or giant cell carcinomas, although uncommon represent an important group of primary lung carcinomas. Important to highlight is that current criteria are rather ambiguous and likely not up to date, which renders the classification of these tumors somewhat more obscure. In addition, with the daily use of immunohistochemical stains, the classification of these tumors may also pose a different problem in the proper allocation of these tumors. Proper classification is highly important in the selection process that takes place using such material for molecular analysis. The current molecular characteristics of these tumors are limited and lack more in-depth studies and analyses that can provide specific targets for the treatment of patients with these tumors. The current review attempts to highlight the shortcomings in the current classification and definitions of these neoplasms as well as the more current view regarding these tumors when the use of immunohistochemical stains is employed.

Molecular profiling and prognostic biomarkers in chinese non-small cell lung cancer cohort

INTRODUCTION

Comprehensive information about the genome analysis and its prognostic values of NSCLC patients in Chinese population are still needed.

PATIENTS

A total of 117 Chinese patients with NSCLC were enrolled in this study. Tumor tissues or blood were collected and sequenced by targeted next-generation sequencing of 556 cancer related genes. The associations between clinical outcomes and clinical characteristics, TMB, mutated genes, treatment therapies were analyzed using Kaplan-Meier methods and further evaluated using multivariable Cox proportional hazards regression model.

RESULTS

A total of 899 mutations were identified by targeted NGS. The most frequently mutations included EGFR (47%), TP53 (46%), KRAS (18%), LRP1B (12%) and SPTA1 (10%). Patients with mutant TP53, PREX2, ARID1A, PTPRT and PIK3CG had lower median overall survival (OS) than those patients with wild-type (P = 0.0056, P < 0.001, P < 0.0001, P < 0.0001 and P = 0.036, respectively). Using a multivariate Cox regression model, PREX2 (P < 0.001), ARID1A (P < 0.001) and PIK3CG (P = 0.04) were independent prognostic factors in NSCLC. In the patients received chemotherapy, squamous patients had a significantly longer median OS than adenocarcinoma patients (P = 0.011). In the patients received targeted therapy, adenocarcinoma patients had a significantly longer survival period than squamous patients (P = 0.01).

CONCLUSIONS

Our study provided comprehensive genomic alterations in a cohort of Chinese NSCLC. We also identified new prognostic biomarkers, which could provide potential clues for targeted therapies.

EML4-ALK biology and drug resistance in non-small cell lung cancer: a new phase of discoveries

Anaplastic lymphoma kinase (ALK) can be driven to oncogenic activity by different types of mutational events such as point-mutations, for example F1174L in neuroblastoma, and gene fusions, for example with echinoderm microtubule-associated protein-like 4 (EML4) in non-small cell lung cancer (NSCLC). EML4-ALK variants result from different breakpoints, generating fusions of different sizes and properties. The most common variants (Variant 1 and Variant 3) form cellular compartments with distinct physical properties. The presence of a partial, probably misfolded beta-propeller domain in variant 1 confers solid-like properties to the compartments it forms, greater dependence on Hsp90 for protein stability and higher cell sensitivity to ALK tyrosine kinase inhibitors (TKIs). These differences translate to the clinic because variant 3, on average, worsens patient prognosis and increases metastatic risk. Latest generation ALK-TKIs are beneficial for most patients with EML4-ALK fusions. However, resistance to ALK inhibitors can occur via point-mutations within the kinase domain of the EML4-ALK fusion, for example G1202R, reducing inhibitor effectiveness. Here, we discuss the biology of EML4-ALK variants, their impact on treatment response, ALK-TKI drug resistance mechanisms and potential combination therapies.

Improving the process of ordering outside genomic testing for lung cancer FNA and small biopsy specimens - A multidisciplinary quality improvement project

Objectives

Lung cancer is an important cause of mortality in the United States. Targeted mutation analysis has the potential to alter mortality in those with non-small-cell lung cancer. As such, the importance of timely tissue turnaround time (TAT) is substantial. We evaluated TAT at Mayo Clinic Arizona and found it to be delayed relative to national standards.

Material and Methods

We conducted a series of plan, do, study, and act (PDSA) cycles at a single institution to identify areas for improvement with our lung cancer genomic testing. We assembled a multidisciplinary team and held serial meetings to discuss data from each PDSA cycle.

Results

Using PDSA cycles and multidisciplinary discussions, we were able to identify a number of process limitations slowing TAT. We were then able to generate enhanced and timely communication between providers and pathology, educate and enforce the order/requisition workflow, and establish pathology accessioning with lung cancer specimens top priority.

Conclusion

We were able to generate and implement a standard operating procedure for genomic testing of lung cancer specimens at our institution, thereby reducing tissue TAT.

Pretreatment levels of serum alkaline phosphatase are associated with the prognosis of patients with non‑small cell lung cancer receiving immune checkpoint inhibitors

Immune checkpoint inhibitors (ICIs) have been an encouraging treatment method in non-small cell lung cancer (NSCLC). However, bone and liver metastases are considered to restrain immunotherapy efficacy. Since serum alkaline phosphatase (ALP) is associated with bone and liver metastases, it was investigated whether serum ALP could be a novel biomarker to predict the efficacy of ICIs treatment. In the present study, 143 patients with NSCLC receiving ICIs treatment were retrospectively analyzed. The objective response rate (ORR) was compared between the ALP high and low groups, bone metastasis and non-bone metastasis groups, and liver metastasis or non-liver metastasis groups. The associations between clinical characteristics, including ALP level, bone or liver metastasis and median progression-free survival (mPFS) time were analyzed by univariate and multivariate Cox regression analysis. It was found that bone metastasis was associated with a lower ORR (24 vs. 43%; P<0.05) and shorter mPFS (10.2 vs. 17.3 months; P=0.010) in patients with NSCLC receiving ICIs. Liver metastasis was associated with lower ORR (22 vs. 38%; P<0.05), but not with mPFS (P=0.119). The ALP level was higher in patients with bone or liver metastasis than in those without (119.6 or 103.6 vs. 83.3 U/l, respectively; P<0.05). Higher ALP levels were also associated with bone or liver metastasis, lower ORR (20 vs. 39%; P<0.05) and shorter mPFS (8.5 vs. 15.4 months; P=0.009). Cox regression analysis demonstrated that ALP was an independent prognostic indicator of mPFS (hazard ratio, 1.856; 95% confidence interval, 1.030-3.343; P=0.040). In conclusion, pretreatment levels of serum ALP might be a predictive indicator of clinical outcome in patients with NSCLC after ICIs treatment.

Deep learning for predicting epidermal growth factor receptor mutations of non-small cell lung cancer on PET/CT images

Background

Predicting the mutation status of the epidermal growth factor receptor (EGFR) gene based on an integrated positron emission tomography/computed tomography (PET/CT) image of non-small cell lung cancer (NSCLC) is a noninvasive, low-cost method which is valuable for targeted therapy. Although deep learning has been very successful in robotic vision, it is still challenging to predict gene mutations in PET/CT-derived studies because of the small amount of medical data and the different parameters of PET/CT devices.

Methods

We used the advanced EfficientNet-V2 model to predict the EGFR mutation based on fused PET/CT images. First, we extracted 3-dimensional (3D) pulmonary nodules from PET and CT as regions of interest (ROIs). We then fused each single PET and CT image. The network model was used to predict the mutation status of lung nodules by the new data after fusion, and the model was weighted adaptively. The EfficientNet-V2 model used multiple channels to represent nodules comprehensively.

Results

We trained the EfficientNet-V2 model through our PET/CT fusion algorithm using a dataset of 150 patients. The prediction accuracy of EGFR and non-EGFR mutations was 86.25% in the training dataset, and the accuracy rate was 81.92% in the validation set.

Conclusions

Combined with experiments, the demonstrated PET/CT fusion algorithm outperformed radiomics methods in predicting EGFR and non-EGFR mutations in NSCLC.

The prognostic value of histopathology in invasive lung adenocarcinoma: a comparative review of the main proposed grading systems

INTRODUCTION

An accurate histological evaluation of invasive lung adenocarcinoma is essential for a correct clinical and pathological definition of the tumour. Different grading systems have been proposed to predict the prognosis of invasive lung adenocarcinoma.

AREAS COVERED

Invasive non mucinous lung adenocarcinoma is often morphologically heterogeneous, consisting of complex combinations of architectural patterns with different proportions. Several grading systems for non-mucinous lung adenocarcinoma have been proposed, being the main based on architectural differentiation and the predominant growth pattern. Herein we perform a thorough review of the literature using PubMed, Scopus and Web of Science and we highlight the peculiarities and the differences between the main grading systems and compare the data about their prognostic value. In addition, we carried out an evaluation of the proposed grading systems for less common histological variants of lung adenocarcinoma, such as fetal adenocarcinoma and invasive mucinous adenocarcinoma.

EXPERT OPINION

The current IASLC grading system, based on the combined score of predominant growth pattern plus high-grade histological pattern, shows the stronger prognostic significance than the previous grading systems in invasive non mucinous lung adenocarcinoma.

Emerging precision neoadjuvant systemic therapy for patients with resectable non-small cell lung cancer: current status and perspectives

Over the past decade, targeted therapy for oncogene-driven NSCLC and immune checkpoint inhibitors for non-oncogene-driven NSCLC, respectively, have greatly improved the survival and quality of life for patients with unresectable NSCLC. Increasingly, these biomarker-guided systemic therapies given before or after surgery have been used in patients with early-stage NSCLC. In March 2022, the US FDA granted the approval of neoadjuvant nivolumab and chemotherapy for patients with stage IB-IIIA NSCLC. Several phase II/III trials are evaluating the clinical efficacy of various neoadjuvant immune checkpoint inhibitor combinations for non-oncogene-driven NSCLC and neoadjuvant molecular targeted therapies for oncogene-driven NSCLC, respectively. However, clinical application of precision neoadjuvant treatment requires a paradigm shift in the biomarker testing and multidisciplinary collaboration at the diagnosis of early-stage NSCLC. In this comprehensive review, we summarize the current diagnosis and treatment landscape, recent advances, new challenges in biomarker testing and endpoint selections, practical considerations for a timely multidisciplinary collaboration at diagnosis, and perspectives in emerging neoadjuvant precision systemic therapy for patients with resectable, early-stage NSCLC. These biomarker-guided neoadjuvant therapies hold the promise to improve surgical and pathological outcomes, reduce systemic recurrences, guide postoperative therapy, and improve cure rates in patients with resectable NSCLC.

Postoperative survival of pulmonary invasive mucinous adenocarcinoma versus non-mucinous invasive adenocarcinoma

PURPOSE

In 2015, the World Health Organization renamed mucinous bronchioloalveolar adenocarcinoma as pulmonary invasive mucinous adenocarcinoma (IMA). Due to its low incidence and unclear prognosis with surgical treatment, previous studies have presented opposing survival outcomes. We aimed to investigate the differences in surgical prognosis and prognosis-related risk factors by comparing IMA with non-mucinous invasive adenocarcinoma (NMA).

METHODS

A total of 20,914 patients diagnosed with IMA or NMA from 2000 to 2014 were screened from the Surveillance, Epidemiology, and End Results database. The screened patients were subjected to propensity score matching (PSM) in a 1:4 ratio to explore the survival differences between patients with IMA and NMA and the factors influencing prognosis.

RESULTS

For all patients, IMA was prevalent in the lower lobes of the lungs (p < 0.0001), well-differentiated histologically (p < 0.0001), less likely to have lymph node metastases (94.4% vs. 72.0%, p < 0.0001) and at an earlier pathological stage (p = 0.0001). After PSM, the IMA cohort consisted of 303 patients, and the NMA cohort consisted of 1212 patients. Kaplan‒Meier survival analysis showed no difference in overall survival (OS) between patients in the IMA cohort and those in the NMA cohort (p = 0.7). Cox proportional hazards analysis showed that differences in tumor pathological type did not influence OS between the two cohorts (p = 0.65). Age (HR: 1.98, 95% CI 1.7-2.31, p < 0.0001), gender (HR: 0.64, 95% CI 0.55-0.75, p < 0.0001), and radiation treatment (HR: 2.49, 95% CI 1.84-3.37, p < 0.0001) were independent predictors of patient OS.

CONCLUSION

There was no significant difference in OS between patients with IMA and those with NMA after surgical treatment. Age, sex, and radiation treatment can independently predict OS.

Drug Repurposing in Non-Small Cell Lung Carcinoma: Old Solutions for New Problems

Lung cancer is the second most common cancer and the leading cause of cancer-related deaths in 2022. The majority (80%) of lung cancer cases belong to the non-small cell lung carcinoma (NSCLC) subtype. Despite the increased screening efforts, the median five-year survival of metastatic NSCLC remains low at approximately 3%. Common treatment approaches for NSCLC include surgery, multimodal chemotherapy, and concurrent radio and chemotherapy. NSCLC exhibits high rates of resistance to treatment, driven by its heterogeneity and the plasticity of cancer stem cells (CSCs). Drug repurposing offers a faster and cheaper way to develop new antineoplastic purposes for existing drugs, to help overcome therapy resistance. The decrease in time and funds needed stems from the availability of the pharmacokinetic and pharmacodynamic profiles of the Food and Drug Administration (FDA)-approved drugs to be repurposed. This review provides a synopsis of the drug-repurposing approaches and mechanisms of action of potential candidate drugs used in treating NSCLC, including but not limited to antihypertensives, anti-hyperlipidemics, anti-inflammatory drugs, anti-diabetics, and anti-microbials.

Deep targeted sequencing of cytological tumor cells using whole genome amplification

BACKGROUND

Genomic profiling in lung cancer is essential for precision medicine. Cytological specimens provide an alternative to formalin-fixed paraffin-embedded (FFPE) samples for comprehensive genomic analysis. However, this approach remains challenging when a limited number of tumor cells are available. We applied whole genome amplification (WGA) to cytology specimens to overcome this limitation.

METHODS

Using a lung cancer panel targeting 58 genes, we performed next-generation sequencing of whole genome-amplified DNA extracted from cytological specimens containing 10-20 tumor cells (cyto-WGA) and DNA from corresponding FFPE tumor tissue. We compared sequencing data from cyto-WGA and FFPE samples to examine the detection accuracy of copy number variations and oncogenic and drug-matched variants.

RESULTS

The DNA quality and quantity from cyto-WGA were higher than those from FFPE samples (p < .0005 and p < .05, respectively). Sequencing metrics of cyto-WGA and FFPE tissues showed no difference in the number of mapped reads and mean coverage depth, but there were significant differences in the on-target rate (p < .05) and uniformity (p < .0005). Copy number variations in cyto-WGA samples (n = 211) were higher than in FFPE samples (n = 9) (p < .0001). Fourty nine oncogenic variants were detected in cyto-WGA and 39 in FFPE. Of these variants, 34 (63%) were present in both samples. In addition, all 16 drug-matched variants were detected in FFPE and cyto-WGA samples with 100% concordance.

CONCLUSION

Cyto-WGA can be a feasible and alternative method to detect oncogenic and drug-matched variants.

MBL2 polymorphism may be a protective factor of autoimmune thyroid disease susceptibility

Genetic susceptibility is an essential pathogenetic mechanism in autoimmune thyroid disease (AITD). MBL2 gene polymorphisms have been shown to play a vital role in the pathogenesis of multiple autoimmune disorders, but its contribution to AITD is unclear. The aim of this study was to assess the linkage between MBL2 gene polymorphisms and AITD susceptibility in a Chinese Han population. One thousand seven hundred sixty seven subjects consisting of 965 AITD patients and 802 controls from a Chinese Han population were enrolled in the case-control study. Four common single-nucleotide polymorphisms (SNPs) in the MBL2 gene were tested using high-throughput sequencing technology for sequence-based SNP genotyping. The allele and genotype distribution results showed that the minor alleles of rs198266, rs10824793, and rs4935046 were significantly lower in Hashimoto's thyroiditis (HT) patients than in healthy controls. In further genetic model analysis, the dominant models of rs1982266, rs10824793, and rs4935046 for MBL2 in the AITD group exhibited a lower risk of morbidity. Finally, we discovered that haplotype AAGC was associated with Graves' disease (GD), while AGC was associated with HT. Our study provides strong evidence for a genetic correlation between MBL2 and AITD, and the polymorphism of the MBL2 gene may be a protective factor for AITD, especially for HT. These findings can advance our understanding of the etiology of AITD, as well as provide guidance for prevention and intervention toward AITD.

The impact of population-based EGFR testing in non-squamous metastatic non-small cell lung cancer in Alberta, Canada

OBJECTIVES

While Epidermal Growth Factor Receptor (EGFR) Tyrosine Kinase Inhibitors have been shown to be effective in phase III randomized trials, the value of targeted therapies has been challenging to evaluate at the population-level. We examined the impact of population-level EGFR testing and treatment on survival outcomes among non-squamous metastatic Non-Small Cell Lung Cancer (NSCLC) patients.

MATERIALS AND METHODS

Real-world, population-level data were collected from all de novo non-squamous metastatic NSCLC patients in Alberta, Canada from 2004 to 2020. EGFR testing data were collected through Alberta Precision Laboratories. Differences in survival rates and overall survival (OS) pre (2004-2012) and post initiation (post) (2013-2019) testing periods were evaluated using interrupted time series analyses. The impact of testing and subsequent treatment was evaluated using multivariable Cox Proportional Hazards models.

RESULTS

In total, 4,578 non-squamous metastatic NSCLC patients were diagnosed pre-EGFR testing and 4,457 patients were diagnosed post-EGFR testing (2013-2019). Among patients diagnosed in the pre-EGFR testing period, the 6-month, 1-year, and 2-year survival probabilities were 0.39 (95 % CI: 0.38-0.41), 0.22 (95 % CI: 0.21-0.23), and 0.09 (95 % CI: 0.08-0.10), while the survival probabilities for patients diagnosed in the post-EGFR testing period were 0.45 (95 % CI: 0.43-0.46), 0.29 (95 % CI: 0.27-0.30), and 0.16 (95 % CI: 0.15-0.17), respectively. After adjusting for baseline patient and clinical characteristics, OS in the post-EGFR period was significantly improved compared to the pre-EGFR period (HR: 0.81; 95 % CI: 0.78-0.85). Among patients who were treated with systemic therapy, those tested for an EGFR mutation had significantly greater survival than patients who were not tested HR of 0.81 (95 % CI: 0.70-0.95).

CONCLUSION

These results show the considerable impact of population-based molecular testing and subsequent targeted therapies on survival among metastatic NSCLC patients. The estimates here can be used in future studies to evaluate the population-level cost-effectiveness of testing and treatment.

Artificial intelligence in clinical decision support systems for oncology

Artificial intelligence (AI) has been widely used in various medical fields, such as image diagnosis, pathological classification, selection of treatment schemes, and prognosis analysis. Especially in the image-aided diagnosis of tumors, the cooperation of human-computer interactions has become mature. However, the ethics of the application of AI as an emerging technology in clinical decision-making have not been fully supported, so the clinical decision support system (CDSS) based on AI technology has not fully realized human-computer interactions in clinical practice as the image-aided diagnosis system. The CDSS was currently used and promoted worldwide including Watson for Oncology, Chinese society of clinical oncology-artificial intelligence (CSCO AI) and so on. This paper summarized the applications and clarified the principle of AI in CDSS, analyzed the difficulties of AI in oncology decisions, and provided a reference scheme for the application of AI in oncology decisions in the future.

Prognostic value of Beclin 1, EGFR and ALK in non-squamous non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is one of the most malignant tumors. The study was carried out to investigate the prognostic value of Beclin 1, EGFR and ALK for this cancer. Patients diagnosed with non-squamous NSCLC and admitted to our hospital from January 2011 to September 2016 were analyzed. Expression of Beclin 1 and mutation of EGFR and ALK were assessed using polymerase chain reaction (PCR) and fluorescent in situ hybridization (FISH) and analyzed for their relationship with demographic and clinical characteristics of the patients. Multivariate Cox regression models were applied to analyze the risk factors associated with survival and receiver response curves (ROC) were plotted to determine the prognostic value of Beclin 1, EGFR and ALK for patients with non-squamous NSCLC. Compared with adjacent normal tissue, Beclin 1 expression was elevated in the cancer tissue significantly; assessments of EGFR and ALK mutations showed that out of the 480 patients, 233 (48.5%) and 75 (12.6%) patients had EGFR and ALK mutations. Univariate analysis revealed that Beclin 1 level, EGFR and ALK mutations were associated with lymph node metastasis, TNM stage, tumor differentiation and prognosis, but not with gender, age and smoking status. The Kaplan-Meier survival analysis indicated that low Beclin 1 expression and positive EGFR and ALK rearrangements were associated with higher survival rate and longer progress-free survival (PFS). Multivariate Cox regression analysis showed that Beclin 1, EGFR, ALK mutations, tumor differentiation grade, TNM stage and lymph node metastasis were independently associated with PFS. ROC analysis showed that Beclin 1, EGFR and ALK were significant predictors for PFS; the areas under curve (AUC) for Beclin 1, EGFR and ALK were 0.812 (P = 0.018, cut-off value: 1.2), 0.781 (P = 0.011, cut-off value: 15%) and 0.722 (P = 0.010, cut-off value: 11%), respectively, suggesting that they have significant prognostic value for lung cancer patients. Our data indicate that Beclin 1, EGFR and ALK genes are associated with the prognosis of patients with non-squamous NSCLC. High Beclin 1 expression and negative EGFR and ALK mutations predict a poor prognosis with PFS.

Long non-coding RNA DLGAP1-AS1 modulates the development of non-small-cell lung cancer via the microRNA-193a-5p/DTL axis

Non-small cell lung cancer (NSCLC) is one of the most malignant cancers worldwide. A growing number of studies have suggested that long noncoding RNAs (lncRNAs) play a key role in the progression of non-small cell lung cancer (NSCLC). Here, we report a novel lncRNA DLGAP1 antisense RNA 1 (DLGAP1-AS1) that exhibits oncogenic properties in NSCLC. The lncRNA DLGAP1-AS1 and denticleless protein homolog (DTL) presented upregulated expression, but microRNA-193a-5p (miR-193a-5p) showed downregulated expression in cancerous tissues of human lung samples from 48 patients with NSCLC. Partial loss of lncRNA DLGAP1-AS1 reduced malignant cell viability, migration, and invasion but induced apoptosis. Dual-luciferase reporter gene, RNA pull-down and RNA binding protein immunoprecipitation assays demonstrated enrichment of lncRNA DLGAP1-AS1 in miR-193a-5p and Argonaute 2, suggesting that lncRNA DLGAP1-AS1 modulated DTL, a putative target of miR-193a-5p. We also found that restoration of miR-193a-5p rescued NSCLC cell biological functions affected by overexpression of lncRNA DLGAP1-AS1. Silencing lncRNA DLGAP1-AS1 was found to reduce the tumorigenesis of NSCLC cells xenografted into nude mice, which was rescued by DTL overexpression. In conclusion, our study highlights a novel regulatory network of the lncRNA DLGAP1-AS1/miR-193a-5p/DTL axis in NSCLC, providing a potential therapeutic strategy for NSCLC.

Biomarker-Targeted Therapies in Non-Small Cell Lung Cancer: Current Status and Perspectives

Non-small-cell lung cancer (NSCLC) is one of the most common malignancies and the leading causes of cancer-related death worldwide. Despite many therapeutic advances in the past decade, NSCLC remains an incurable disease for the majority of patients. Molecular targeted therapies and immunotherapies have significantly improved the prognosis of NSCLC. However, the vast majority of advanced NSCLC develop resistance to current therapies and eventually progress. In this review, we discuss current and potential therapies for NSCLC, focusing on targeted therapies and immunotherapies. We highlight the future role of metabolic therapies and combination therapies in NSCLC.

Personalized Targeted Therapeutic Strategies against Oral Squamous Cell Carcinoma. An Evidence-Based Review of Literature

Oral squamous cell carcinoma (OSCC) is the most common type of malignant tumor in the head and neck, with a poor prognosis mainly due to recurrence and metastasis. Classical treatment modalities for OSCC like surgery and radiotherapy have difficulties in dealing with metastatic tumors, and together with chemotherapy, they have major problems related to non-specific cell death. Molecular targeted therapies offer solutions to these problems through not only potentially maximizing the anticancer efficacy but also minimizing the treatment-related toxicity. Among them, the receptor-mediated targeted delivery of anticancer therapeutics remains the most promising one. As OSCC exhibits a heterogeneous nature, selecting the appropriate receptors for targeting is the prerequisite. Hence, we reviewed the OSCC-associated receptors previously used in targeted therapy, focused on their biochemical characteristics and expression patterns, and discussed the application potential in personalized targeted therapy of OSCC. We hope that a better comprehension of this subject will help to provide the fundamental information for OSCC personalized therapeutic planning.

Liquid Biopsy Analysis as a Tool for TKI-Based Treatment in Non-Small Cell Lung Cancer

The treatment of non-small cell lung cancer (NSCLC) has recently evolved with the introduction of targeted therapy based on the use of tyrosine kinase inhibitors (TKIs) in patients with certain gene alterations, including EGFR, ALK, ROS1, BRAF, and MET genes. Molecular targeted therapy based on TKIs has improved clinical outcomes in a large number of NSCLC patients with advanced disease, enabling significantly longer progression-free survival (PFS). Liquid biopsy is an increasingly popular diagnostic tool for treating TKI-based NSCLC. The studies presented in this article show that detection and analysis based on liquid biopsy elements such as circulating tumor cells (CTCs), cell-free DNA (cfDNA), exosomes, and/or tumor-educated platelets (TEPs) can contribute to the appropriate selection and monitoring of targeted therapy in NSCLC patients as complementary to invasive tissue biopsy. The detection of these elements, combined with their molecular analysis (using, e.g., digital PCR (dPCR), next generation sequencing (NGS), shallow whole genome sequencing (sWGS)), enables the detection of mutations, which are required for the TKI treatment. Despite such promising results obtained by many research teams, it is still necessary to carry out prospective studies on a larger group of patients in order to validate these methods before their application in clinical practice.

Deep learning analysis to predict EGFR mutation status in lung adenocarcinoma manifesting as pure ground-glass opacity nodules on CT

Background

Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) showed potency as a non-invasive therapeutic approach in pure ground-glass opacity nodule (pGGN) lung adenocarcinoma. However, optimal methods of extracting information about EGFR mutation from pGGN lung adenocarcinoma images remain uncertain. We aimed to develop, validate, and evaluate the clinical utility of a deep learning model for predicting EGFR mutation status in lung adenocarcinoma manifesting as pGGN on computed tomography (CT).

Methods

We included 185 resected pGGN lung adenocarcinomas in the primary cohort. The patients were divided into training (n = 125), validation (n = 23), and test sets (n = 37). A preoperative CT-based deep learning model with clinical factors as well as clinical and radiomics models was constructed and applied to the test set. We evaluated the clinical utility of the deep learning model by applying it to 83 GGNs that received EGFR-TKI from an independent cohort (clinical validation set), and treatment response was regarded as the reference standard.

Results

The prediction efficiencies of each model were compared in terms of area under the curve (AUC). Among the 185 pGGN lung adenocarcinomas, 122 (65.9%) were EGFR-mutant and 63 (34.1%) were EGFR-wild type. The AUC of the clinical, radiomics, and deep learning with clinical models to predict EGFR mutations were 0.50, 0.64, and 0.85, respectively, for the test set. The AUC of deep learning with the clinical model in the validation set was 0.72.

Conclusions

Deep learning approach of CT images combined with clinical factors can predict EGFR mutations in patients with lung adenocarcinomas manifesting as pGGN, and its clinical utility was demonstrated in a real-world sample.

Computed tomography-based radiomics quantification predicts epidermal growth factor receptor mutation status and efficacy of first-line targeted therapy in lung adenocarcinoma

Background

Biomarkers that predict the efficacy of first-line tyrosine kinase inhibitors (TKIs) are pivotal in epidermal growth factor receptor (EGFR) mutant advanced lung adenocarcinoma. Imaging-based biomarkers have attracted much attention in anticancer therapy. This study aims to use the machine learning method to distinguish EGFR mutation status and further explores the predictive role of EGFR mutation-related radiomics features in response to first-line TKIs.

Methods

We retrospectively analyzed pretreatment CT images and clinical information from a cohort of lung adenocarcinomas. We entered the top-ranked features into a support vector machine (SVM) classifier to establish a radiomics signature that predicted EGFR mutation status. Furthermore, we identified the best response-related features based on EGFR mutant-related features in first-line TKI therapy patients. Then we test and validate the predictive effect of the best response-related features for progression-free survival (PFS).

Results

Six hundred ninety-two patients were enrolled in building radiomics signatures. The 13 top-ranked features were input into an SVM classifier to establish the radiomics signature of the training cohort (n = 514), and the predictive score of the radiomics signature was assessed on an independent validation group with 178 patients and obtained an area under the curve (AUC) of 74.13%, an F1 score of 68.29%, a specificity of 79.55%, an accuracy of 70.79%, and a sensitivity of 62.22%. More importantly, the skewness-Low (≤0.882) or 10th percentile-Low group (≤21.132) had a superior partial response (PR) rate than the skewness-High or 10th percentile-High group (p < 0.01). Higher skewness (hazard ratio (HR) = 1.722, p = 0.001) was also found to be significantly associated with worse PFS.

Conclusions

The radiomics signature can be used to predict EGFR mutation status. Skewness may contribute to the stratification of disease progression in lung cancer patients treated with first-line TKIs.