Translational lung cancer research最新文献

Background: Small cell lung cancer (SCLC) is highly malignant and has a higher risk of recurrence even in patients who undergo early surgery. However, a subgroup of patients survived for many years. So far, the factors that determine the long-term survivorship remain largely unknown. To determine the genetic characteristics of long-term survival (LTS) after surgery in SCLC, we performed comprehensive comparative genomic profiling and tumor mutation burden (TMB) analysis of resected tumor tissues from patients with LTS and short-term survival (STS) after surgery.

Methods: The present study screened 11 patients from 52 patients with SCLC who underwent surgery at Zhejiang Cancer Hospital from April 2008 to December 2017. A total of six LTS patients (≥4 years) with stage IIB or IIIA SCLC and five STS patients (<2 years) with stage IA or IB SCLC were included in the study. The STS patients were used as a control. All the patients underwent resection without neoadjuvant therapy. We assessed the genomic profiles of the resected tumor tissues and calculated the TMB using next-generation sequencing. We then analyzed and compared the molecular characteristics between the LTS and STS groups.

Results: Our data indicated that tumor tissues from patients with LTS harbor a high TMB. The median TMB for LTS patients was high (approximately 16.4 mutations/Mb), while that for STS patients was low (approximately 8.5 mutations/Mb). The median TMB of patients with LTS and STS showed a trend of significant difference (P=0.08). Gene alterations characterized the survival differences between the two groups. The FAT3 mutation was only found in the LTS group, and the P value determined by Fisher's exact test was 0.06.

Conclusions: A high non-synonymous TMB and the FAT3 mutation could potentially influence LTS after SCLC resection. This study provides valuable information about the molecular differences between LTS and STS patients. Studies with larger sample sizes need to be conducted to confirm our findings in the future.

Background: Lung cancer is the malignant tumor with high incidence and mortality in China, and more than 30% of non-small cell lung cancer (NSCLC) patients are in the locally advanced stage at the first-time diagnosis. Currently, neoadjuvant epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) combined with radical surgery is effective in the treatment of unresectable stage III EGFR-mutated NSCLC (NSCLCm), and related studies are gradually increasing. But the feasibility of neoadjuvant EGFR-TKI combined with radical surgery for unresectable stage III EGFR-mutant lung squamous cell carcinoma (LUSQm) remains controversial.

Case description: This report presented a successful case of neoadjuvant target-therapy with aumolertinib, the third-generation EGFR-TKI, combined with radical surgery for a stage IIIA LUSQm female patient. After four cycles (28 days/cycle) of neoadjuvant target-therapy, the tumor had a partial response on imaging evaluation and pathological evaluation after surgery showed complete tumor response. The neoadjuvant target-therapy was well tolerated. All adverse events (AEs) that occurred during the treatment were grade I, including decreased platelets, impaired liver function, and diarrhea. The patient was instructed to continue taking Aumolertinib for 3 years after surgery. At the cut-off date of April 1, 2024, the patient had no recurrence after 20 months of treatment.

Conclusions: The result of patient treatment demonstrated the potential feasibility of neoadjuvant Aumolertinib monotherapy for locally advanced LUSQm. The report provides some support for neoadjuvant target-therapy for LUSQm.

Background: Driver genes are essential predictors of targeted therapeutic efficacy. Detecting driver gene mutations in lung adenocarcinoma (LUAD) patients can help to screen for targeted drugs and improve patient survival benefits. This study aims to investigate the mutation characterization of driver genes and their correlation with clinicopathological features in LUAD.

Methods: A total of 440 LUAD patients were selected from Sir Run Run Shaw Hospital between July 2019 and September 2022. Postoperative tissue specimens were analyzed for gene mutations using next-generation sequencing technology, focusing, including epidermal growth factor receptor EGFR, ALK, ROS1, RET, KRAS, MET, BRAF, HER2, PIK3CA and NRAS. At the same time, clinicopathological data were collected and organized for multidimensional correlation analysis.

Results: Of 440 LUAD patients, driver gene mutations were not detected in 48 patients. The proportion of patients with driver gene mutations was as high as 89.09%. The top three driver genetic mutations were EGFR, KRAS, and MET. Sixty-nine types of EGFR mutations were detected and distributed in the protein tyrosine kinase catalytic domain (56, 81.16%), Furin-like cysteine-rich region (9, 13.04%), receptor binding domain (3, 4.35%), and EGFR transmembrane domain (1, 1.45%). Single gene locus mutation occurred in 343 LUAD patients, but the mutation gene types covered all tested genes. Our findings showed that EGFR mutations were more commonly observed in non-smoking and female patients (P<0.01), KRAS mutations were more prevalent in male patients and smokers (P<0.01), ROS1 mutations had larger tumor diameters (P<0.01) and RET mutations were more prevalent in smokers (P<0.05).

Conclusions: LUAD patients exhibit diverse genetic mutations, which may co-occur simultaneously. Integrated analysis of multiple mutations is essential for accurate diagnosis and effective treatment of the disease. The use of NGS can significantly expand our understanding of gene mutations and facilitate integrated analysis of multiple gene mutations, providing critical evidence for targeted treatment methods.

Background: Pulmonary sarcomatoid carcinoma (PSC) is a rare, highly malignant type of non-small cell lung cancer (NSCLC) with a poor prognosis. Targeted drugs for MET exon 14 (METex14) skipping mutation can have considerable clinical benefits. This study aimed to predict METex14 skipping mutation in PSC patients by whole-tumour texture analysis combined with clinical and conventional contrast-enhanced computed tomography (CECT) features.

Methods: This retrospective study included 56 patients with PSC diagnosed by pathology. All patients underwent CECT before surgery or other treatment, and both targeted DNA- and RNA-based next-generation sequencing (NGS) were used to detect METex14 skipping mutation status. The patients were divided into two groups: METex14 skipping mutation and nonmutation groups. Overall, 1,316 texture features of the whole tumour were extracted. We also collected 12 clinical and 20 conventional CECT features. After dimensionality reduction and selection, predictive models were established by multivariate logistic regression analysis. Models were evaluated using the area under the curve (AUC), and the clinical utility of the model was assessed by decision curve analysis.

Results: METex14 skipping mutation was detected in 17.9% of PSCs. Mutations were found more frequently in those (I) who had smaller long- or short-axis diameters (P=0.02, P=0.01); (II) who had lower T stages (I, II) (P=0.02); and (III) with pseudocapsular or annular enhancement (P=0.03). The combined model based on the conventional and texture models yielded the best performance in predicting METex14 skipping mutation with the highest AUC (0.89). The conventional and texture models also had good performance (AUC =0.83 conventional; =0.88 texture).

Conclusions: Whole-tumour texture analysis combined with clinical and conventional CECT features may serve as a noninvasive tool to predict the METex14 skipping mutation status in PSC.

Background: No robust predictive biomarkers exist to identify non-small cell lung cancer (NSCLC) patients likely to benefit from immune checkpoint inhibitor (ICI) therapies. The aim of this study was to explore the role of delta-radiomics features in predicting the clinical outcomes of patients with advanced NSCLC who received ICI therapy.

Methods: Data of 179 patients with advanced NSCLC (stages IIIB-IV) from two institutions (Database 1 =133; Database 2 =46) were retrospectively analyzed. Patients in the Database 1 were randomly assigned into training and validation dataset, with a ratio of 8:2. Patients in Database 2 were allocated into testing dataset. Features were selected from computed tomography (CT) images before and 6-8 weeks after ICI therapy. For each lesion, a total of 1,037 radiomic features were extracted. Lowly reliable [intraclass correlation coefficient (ICC) <0.8] and redundant (r>0.8) features were excluded. The delta-radiomics features were defined as the relative net change of radiomics features between two time points. Prognostic models for progression-free survival (PFS) and overall survival (OS) were established using the multivariate Cox regression based on selected delta-radiomics features. A clinical model and a pre-treatment radiomics model were established as well.

Results: The median PFS (after therapy) was 7.0 [interquartile range (IQR): 3.4, 9.1] (range, 1.4-13.2) months. To predict PFS, the model established based on the five most contributing delta-radiomics features yielded Harrell's concordance index (C-index) values of 0.708, 0.688, and 0.603 in the training, validation, and testing databases, respectively. The median survival time was 12 (IQR: 8.7, 15.8) (range, 2.9-23.3) months. To predict OS, a promising prognostic performance was confirmed with the corresponding C-index values of 0.810, 0.762, and 0.697 in the three datasets based on the seven most contributing delta-radiomics features, respectively. Furthermore, compared with clinical and pre-treatment radiomics models, the delta-radiomics model had the highest area under the curve (AUC) value and the best patients' stratification ability.

Conclusions: The delta-radiomics model showed a good performance in predicting therapeutic outcomes in advanced NSCLC patients undergoing ICI therapy. It provides a higher predictive value than clinical and the pre-treatment radiomics models.

Background: Lung adenocarcinoma (LUAD) is among the most prevalent malignancies worldwide, with unfavorable treatment outcomes. Peptidyl-prolyl isomerase F (PPIF) is known to influence the malignancy traits of tumor progression by modulating the bioenergetics and mitochondrial permeability in cancer cells; however, its role in LUAD remains unclear. Our study seeks to investigate the clinical significance, tumor proliferation, and immune regulatory functions of PPIF in LUAD.

Methods: The expression of PPIF in LUAD tissues and cells was assessed using bioinformatics analysis, immunohistochemistry (IHC), and Western blotting. Survival curve analysis was conducted to examine the prognostic association between PPIF expression and LUAD. The immunomodulatory role of PPIF in LUAD was assessed through the analysis of PPIF expression and immune cell infiltration. A series of gain- and loss-of-function experiments were conducted on PPIF to investigate its biological functions in LUAD both in vitro and in vivo. The mechanisms underlying PPIF's effects on LUAD were delineated through functional enrichment analysis and Western blotting assays.

Results: PPIF exhibited overexpression in LUAD tissues compared to normal controls. Survival curve analysis revealed that patients with LUAD exhibiting higher PPIF expression demonstrated decreased overall survival and a shorter progression-free interval. PPIF was implicated in modulating immune cell infiltration, particularly in regulating the T helper 1-T helper 2 cell balance. Functionally, PPIF was discovered to promote tumor cell proliferation and advance cell-cycle progression. Furthermore, PPIF could impede mitophagy by targeting the FOXO3a/PINK1-Parkin signaling pathway.

Conclusions: The findings of this study indicate that the prognosis-related gene PPIF may have a significant role in the regulation of LUAD cell proliferation, tumor-associated immune cell infiltration, and mitophagy, and thus PPIF may be a promising therapeutic target of LUAD.

Background: Immune therapy has become first-line treatment option for patients with lung cancer, but some patients respond poorly to immune therapy, especially among patients with lung adenocarcinoma (LUAD). Novel tools are needed to screen potential responders to immune therapy in LUAD patients, to better predict the prognosis and guide clinical decision-making. Although many efforts have been made to predict the responsiveness of LUAD patients, the results were limited. During the era of immunotherapy, this study attempts to construct a novel prognostic model for LUAD by utilizing differentially expressed genes (DEGs) among patients with differential immune therapy responses.

Methods: Transcriptome data of 598 patients with LUAD were downloaded from The Cancer Genome Atlas (TCGA) database, which included 539 tumor samples and 59 normal control samples, with a mean follow-up time of 29.69 months (63.1% of patients remained alive by the end of follow-up). Other data sources including three datasets from the Gene Expression Omnibus (GEO) database were analyzed, and the DEGs between immunotherapy responders and nonresponders were identified and screened. Univariate Cox regression analysis was applied with the TCGA cohort as the training set and GSE72094 cohort as the validation set, and least absolute shrinkage and selection operator (LASSO) Cox regression were applied in the prognostic-related genes which fulfilled the filter criteria to establish a prognostic formula, which was then tested with time-dependent receiver operating characteristic (ROC) analysis. Enriched pathways of the prognostic-related genes were analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and tumor immune microenvironment (TIME), tumor mutational burden, and drug sensitivity tests were completed with appropriate packages in R (The R Foundation of Statistical Computing). Finally, a nomogram incorporating the prognostic formula was established.

Results: A total of 1,636 DEGs were identified, 1,163 prognostic-related DEGs were extracted, and 34 DEGs were selected and incorporated into the immunotherapy responsiveness-related risk score (IRRS) formula. The IRRS formula had good performance in predicting the overall prognoses in patients with LUAD and had excellent performance in prognosis prediction in all LUAD subgroups. Moreover, the IRRS formula could predict anticancer drug sensitivity and immunotherapy responsiveness in patients with LUAD. Mechanistically, immune microenvironments varied profoundly between the two IRRS groups; the most significantly varied pathway between the high-IRRS and low-IRRS groups was ribonucleoprotein complex biogenesis, which correlated closely with the TP53 and TTN mutation burdens. In addition, we established a nomogram incorporating the IRRS, age, sex, clinical stage, T-stage, N-stage, and M-stage as predictors

Background: With the advent of targeted therapies, the survival rates of patients with locally advanced lung cancer have significantly improved. However, there is limited research on the efficacy of neoadjuvant targeted therapy in resectable advanced non-small cell lung cancer (NSCLC) patients with positive driver genes. This article reports a case of stage IIIA NSCLC with an epidermal growth factor receptor (EGFR) 19del mutation that successfully underwent radical lung cancer surgery following neoadjuvant targeted therapy. By observing the perioperative treatment outcomes and side effects in this patient, we aimed to provide insights and summarize experiences for treating similar cases in the future.

Case description: We report a case of a 54-year-old female diagnosed preoperatively with stage IIIA adenocarcinoma of the left upper lung (cT1cN2M0). The patient's course was complicated by acute sick sinus syndrome and was cured by implanting a permanent pacemaker. After multidisciplinary discussion, it was decided to administer neoadjuvant targeted therapy with osimertinib. Following 6 weeks of treatment, the tumor assessment showed partial response (PR), making the patient eligible for surgery. The patient underwent single-port thoracoscopic left upper lobectomy + mediastinal lymphadenectomy. Intraoperatively, the left hilar lymph nodes were found to be tightly adherent to the apical-anterior branch of the left upper pulmonary artery. The main trunk of the left pulmonary artery was temporarily occluded with a vascular clamp to safely dissect the left upper pulmonary artery. The procedure was completed without conversion to open thoracotomy, achieving an R0 resection. Postoperative pathology confirmed stage IIIA (ypT1bN2M0), and the patient continued adjuvant therapy with osimertinib.

Conclusions: Neoadjuvant targeted therapy with osimertinib is expected to become one of the options for neoadjuvant therapy in locally advanced NSCLC with sensitizing EGFR mutations. And for those with advanced lung cancer involving tumors close to the hilum or mediastinal lymph node metastasis, preblocking of the left upper pulmonary artery can help improve surgical safety and better ensure R0 resection.