The Role of TP53 Mutations in EGFR-Mutated Non-Small-Cell Lung Cancer: Clinical Significance and Implications for Therapy

IQGAP3 promotes the progression of glioma as an immune and prognostic marker

Background: IQGAP3 plays a crucial role in regulating cell proliferation, division, and cytoskeletal organization. Abnormal expression of IQGAP3 has been linked to various tumors, but its function in glioma is not well understood. Methods: Various methods, including genetic differential analysis, single-cell analysis, ROC curve analysis, Cox regression, Kaplan-Meier analysis, and enrichment analysis, were employed to analyze the expression patterns, diagnostic potential, prognostic implications, and biological processes involving IQGAP3 in normal and tumor tissues. The impact of IQGAP3 on immune infiltration and the immune microenvironment in gliomas was evaluated using immunofluorescence. Additionally, the cBioPortal database was used to analyze copy number variations and mutation sites of IQGAP3. Experimental validation was also performed to assess the effects of IQGAP3 on glioma cells and explore underlying mechanisms. Results: High IQGAP3 expression in gliomas is associated with an unfavorable prognosis, particularly in wild-type IDH and 1p/19q non-codeleted gliomas. Enrichment analysis revealed that IQGAP3 is involved in regulating the cell cycle, PI3K/AKT signaling, p53 signaling, and PLK1-related pathways. Furthermore, IQGAP3 expression may be closely related to the immunosuppressive microenvironment of glioblastoma. BRD-K88742110 and LY-303511 are potential drugs for targeting IQGAP3 in anti-glioma therapy. In vitro experiments showed that downregulation of IQGAP3 inhibits the proliferation and migration of glioma cells, with the PLK1/PI3K/AKT pathway potentially playing a crucial role in IQGAP3-mediated glioma progression. Conclusion: IQGAP3 shows promise as a valuable biomarker for diagnosis, prognosis, and immunotherapeutic strategies in gliomas.

Unveiling the potential effects of resveratrol in lung cancer treatment: Mechanisms and nanoparticle-based drug delivery strategies

Lung cancer ranks among the most prevalent forms of cancer and remains a significant factor in cancer-related mortality across the world. It poses significant challenges to healthcare systems and society as a whole due to its high incidence, mortality rates, and late-stage diagnosis. Resveratrol (RV), a natural compound found in various plants, has shown potential as a nanomedicine for lung cancer treatment. RV has varied effects on cancer cells, including promoting apoptosis by increasing pro-apoptotic proteins (Bax and Bak) and decreasing anti-apoptotic proteins (Bcl-2). It also hinders cell proliferation by influencing important signaling pathways (MAPK, mTOR, PI3K/Akt, and Wnt/β-catenin) that govern cancer progression. In addition, RV acts as a potent antioxidant, diminishing oxidative stress and safeguarding cells against DNA damage. However, using RV alone in cancer treatment has drawbacks, such as low bioavailability, lack of targeting ability, and susceptibility to degradation. In contrast, nanoparticle-based delivery systems address these limitations and hold promise for improving treatment outcomes in lung cancer; nanoparticle formulations of RV offer advantages such as improved drug delivery, increased stability, controlled release, and targeted delivery to lung cancer cells. This article will provide an overview of lung cancer, explore the potential of RV as a therapeutic agent, discuss the benefits and challenges of nanoparticle-based drug delivery, and highlight the promise of RV nanoparticles for cancer treatment, including lung cancer. By optimizing these systems for clinical application, future studies aim to enhance overall treatment outcomes and improve the prognosis for lung cancer patients.

Co-Occurring Alterations in Multiple Tumor Suppressor Genes Are Associated With Worse Outcomes in Patients With EGFR-Mutant Lung Cancer

INTRODUCTION

Patients with metastatic EGFR-mutant NSCLC inevitably have disease progression while on tyrosine kinase inhibitor (TKI) therapy. Co-occurring tumor suppressor gene (TSG) alterations have been associated with poor outcomes, however, detailed analyses of their impact on patient outcomes are limited.

METHODS

Patients with EGFR-mutant NSCLC treated with EGFR TKIs who had tumor genomic profiling were included. Alterations in TP53 and five additional TSGs (RB1, NF1, ARID1A, BRCA1, and PTEN) were used to stratify the cohort into the following three subgroups: patients with tumors harboring a TP53 mutation plus a mutation in at least one additional TSG (TP53mut/TSGmut), those having a TP53 mutation without additional TSG mutations (TP53mut/TSGwt), and those with TP53wt. Patient characteristics and clinical outcomes were assessed in two independent cohorts.

RESULTS

A total of 101 patients from the Yale Cancer Center and 182 patients from the American Association for Cancer Research Project GENIE database were included. In the Yale cohort, TP53 mutations were identified in 65 cases (64%), of which 23 were TP53mut/TSGmut and 42 were TP53mut/TSGwt. Although the presence of a TP53 mutation was associated with worse outcomes, the additional TSG alteration in TP53mut tumors identified a subset of patients associated with particularly aggressive disease and inferior clinical outcome in both the Yale and the GENIE cohorts. Specifically, in the Yale cohort for patients receiving first-line TKIs, those with TP53mut/TSGmut tumors had shorter progression-free survival (PFS) and overall survival (OS) than TP53mut/TSGwt (PFS: hazard ratio [HR] = 2.03, confidence interval [CI]: 1.12-3.69, p < 0.01, OS: HR = 1.58, CI: 0.82-3.04, p = 0.12) or TP53wt cases (PFS: HR 2.4, CI: 1.28-4.47, p < 0.001, OS: HR = 2.54, CI: 1.21-5.34, p < 0.005). Inferior outcomes in patients with TP53mut/TSGmut tumors were also found in those receiving osimertinib as second-line therapy. Similar findings were seen in patients in the GENIE cohort.

CONCLUSIONS

Patients with TP53mut/TSGmut tumors represent a patient subgroup characterized by an aggressive disease phenotype and inferior outcomes on EGFR TKIs. This information is important for understanding the biological underpinnings of differential outcomes with TKI treatment and has implications for identifying patients who may benefit from additional therapeutic interventions beyond osimertinib monotherapy.

Effectiveness and safety of amivantamab in EGFR exon 20 insertion (E20I) mutations in non-small cell lung cancer (NSCLC)

Background

In non-small cell lung cancer (NSCLC), the epidermal growth factor receptor (EGFR) mutation is a representative oncogenic driver mutation. Only about 12% of EGFR mutation patients have the exon 20 insertion mutation, which is the third most frequent mutation among EGFR mutation NSCLC. Amivantamab, an EGFR and MET proto-oncogene, receptor tyrosine kinase (MET) bispecific antibody, was approved for NSCLC patients with the EGFR exon 20 insertion (E20I) mutation. In this study, we described the real-world, single-center efficacy and safety data of amivantamab in E20I mutation patients.

Methods

This study included metastatic NSCLC patients with EGFR E20I mutations. From January 2018 to June 2022, patients with EGFR E20I mutations who were treated with amivantamab were analyzed at Samsung Medical Center as part of the clinical trial or the early access program (EAP). We collected the patients' characteristics [age, sex, smoking history, location of mutation, sites of metastasis, programmed death-ligand 1 (PD-L1) expression status, etc.] and analyzed progression-free survival (PFS) and overall survival (OS) stratified by PD-L1 expression status, co-mutation such as tumor protein p53 (TP53), and metastasis sites.

Results

A total of 42 patients were analyzed, of which 16 patients were enrolled in the phase 1 study, and 26 patients received amivantamab through EAP. There were 14 (33%) patients with partial remission, 18 (43%) patients with stable disease, and 10 (24%) patients with disease progression. The objective response rate (ORR) was 33%, and the disease control rate (DCR) was 76%. PFS was analyzed by dividing the near and far loop for 31 patients whose mutation location was known. The two groups had no statistically significant difference in PFS [median (range): 11.8 (2.3-21.3) vs. 11.3 (3.4-19.2) months, P=0.69]. For 29 patients with TP53 mutation data, there was no significant difference in PFS between the two groups [median (range): 5.9 (0-18.0) vs. 12.6 (6.9-18.3) months, P=0.11]. When analyzing PFS in 37 patients with PD-L1 expression data, PD-L1 (+) patients showed a poor prognosis [median (range): 11.3 (5.0-17.6) vs. 19.5 (5.3-33.7) months, P=0.04; hazard ratio (HR), 0.44; 95% confidence interval (CI): 0.20-0.98].

Conclusions

The efficacy of amivantamab was confirmed for the real-world population for EGFR E20I-mutated NSCLC. PD-L1 status could be a poor predictive factor, which should be further validated.

Clinicopathological Features of Non-Small Cell Lung Carcinoma with BRAF Mutation

(1) Background: BRAF mutations affect 4-5% of lung adenocarcinomas. This study aimed to analyze the clinicopathological features of lung carcinomas with BRAF mutations, focusing on V600E vs. non-V600E and the presence of co-mutations. (2) Methods: All BRAF-mutated lung carcinomas were retrieved from a molecular diagnostic unit (the reference unit for four different hospitals). The samples were analyzed using next-generation sequencing. Statistical analyses included log-rank tests for overall survival (OS) and progression-free survival (PFS). (3) Results: In total, 60 BRAF-mutated lung carcinomas were retrieved: 24 (40.0%) with V600E and 36 (60.0%) with non-V600E mutations, and 21 (35.0%) with other co-mutations and 39 (65.0%) with only BRAF mutations. Survival data were available for 54/60 (90.0%) cases. Targeted therapy was documented in 11 cases. Patients with V600E mutations exhibited a better prognosis than patients with non-V600E mutations (p = 0.008 for OS, p = 0.018 for PFS); this was confirmed in PFS (p = 0.036) when considering only patients who received no targeted therapy. Patients with co-mutations displayed no prognostic difference compared to patients carrying only BRAF mutations (p = 0.590 for OS, p = 0.938 for PFS). (4) Conclusions: BRAF-mutated lung carcinomas with V600E (40.0%) had a better prognosis than those without V600E. Concomitant co-mutations (35.0%) did not affect the prognosis.

Clinical and Genomic Landscape of FGFR3-Altered Urothelial Carcinoma and Treatment Outcomes with Erdafitinib: A Real-World Experience

PURPOSE

Erdafitinib is the only FDA-approved targeted therapy for FGFR2/3-altered metastatic urothelial cancer. We characterized the genetic landscape of FGFR-altered urothelial carcinoma and real-world clinical outcomes with erdafitinib, including on-treatment genomic evolution.

EXPERIMENTAL DESIGN

Prospectively collected clinical data were integrated with institutional genomic data to define the landscape of FGFR2/3-altered urothelial carcinoma. To identify mechanisms of erdafitinib resistance, a subset of patients underwent prospective cell-free (cf) DNA assessment.

RESULTS

FGFR3 alterations predictive of erdafitinib sensitivity were identified in 39% (199/504) of patients with non-muscle invasive, 14% (75/526) with muscle-invasive, 43% (81/187) with localized upper tract, and 26% (59/228) with metastatic specimens. One patient had a potentially sensitizing FGFR2 fusion. Among 27 FGFR3-altered cases with a primary tumor and metachronous metastasis, 7 paired specimens (26%) displayed discordant FGFR3 status. Erdafitinib achieved a response rate of 40% but median progression-free and overall survival of only 2.8 and 6.6 months, respectively (n = 32). Dose reductions (38%, 12/32) and interruptions (50%, 16/32) were common. Putative resistance mutations detected in cfDNA involved TP53 (n = 5), AKT1 (n = 1), and second-site FGFR3 mutations (n = 2).

CONCLUSIONS

FGFR3 mutations are common in urothelial carcinoma, whereas FGFR2 alterations are rare. Discordance of FGFR3 mutational status between primary and metastatic tumors occurs frequently and raises concern over sequencing archival primary tumors to guide patient selection for erdafitinib therapy. Erdafitinib responses were typically brief and dosing was limited by toxicity. FGFR3, AKT1, and TP53 mutations detected in cfDNA represent putative mechanisms of acquired erdafitinib resistance.

Comparative bioinformatic analysis of KRAS, STK11 and KEAP1 (co-)mutations in non-small cell lung cancer with a special focus on KRAS G12C

OBJECTIVES

Mutations in STK11 (STK11MUT) and KEAP1 (KEAP1MUT) occur frequently in non-small cell lung cancer (NSCLC) and are often co-mutated with KRAS. Several studies linked the co-occurrence of KRASMUT + STK11MUT, as well as KRASMUT + KEAP1MUT to reduced response to immune checkpoint inhibitors (ICI) and even a negative impact on survival. Data focusing STK11 + KEAP1 co-mutations or the triple mutation (KRAS + STK11 + KEAP1) are scarce. The recent availability of KRAS-G12C inhibitors increases the clinical relevance of those co-mutations in KRAS-mutated NSCLC.

MATERIALS AND METHODS

We present a comprehensive bioinformatic analysis encompassing six datasets retrieved from cBioPortal.

RESULTS

Independent of the treatment, triple mutations and STK11MUT + KEAP1MUT were significantly associated with a reduced overall survival (OS). Across treatments, OS of patients with a KRAS G12C triple mutation was significantly reduced compared to patients with KRAS G12C-only. Under ICI-therapy, there was no significant difference in OS between patients harboring the KRAS G12C-only and patients with the KRAS G12C triple mutation, but a significant difference between patients harboring KRAS non-G12C and KRAS non-G12C triple mutations. Triple mutated primary tumors showed a significantly increased frequency of distant metastases to bone and adrenal glands compared to KRAS-only mutated tumors. Additionally, our drug response analysis in cancer cell lines harboring the triple mutations revealed the WNT pathway inhibitor XAV-939 as a potential future drug candidate for this mutational situation.

CONCLUSION

The triple mutation status may serve as a negative prognostic and predictive factor across treatments compared to KRASMUT-only. KRAS G12C generally seems to be a negative predictive marker for ICI-therapy.

Genomic profiling and sites of metastasis in non-small cell lung cancer

Background

We investigated the biological predisposition to site of metastasis in patients with NSCLC based on their molecular profiling and program death ligand PD-L1 status. We sought to identify any association between metastatic site and molecular profile in NSCLC patients.

Methods

This was a retrospective analysis of patients with stage IV NSCLC who were newly diagnosed from January 2014 to June 2022. Clinical characteristics, pathology, molecular reports, and imaging were retrieved and analyzed.

Results

A total of 143 patients were included in the study. Median age was 65 years, with an equal number of men (n=71) and women (n=72). The most common histology was adenocarcinoma (81.8%). At least one genetic mutation was discovered in 100 patients. Mutations with a targetable drug were found in 86 patients. The most common mutations were TP53 (25.2%), EGFR (24.5%), KRAS/NRAS (20.3%), and CDKN2A/2B (7.7%). Patients with any mutation were significantly more likely to have metastatic disease to the brain (57% vs. 37%, p=0.03), but there was no difference in metastatic disease to bone (34% vs. 26%, p=0.32). Patients without a discoverable mutation were significantly more likely to have metastatic disease to other sites (e.g., adrenal gland 91% vs. liver 66%, p=0.002). There was no difference in progression-free survival (PFS) or overall survival (OS) between those with versus without mutations. Median PFS and OS were significantly longer in patients with an EGFR mutation than those with KRAS/NRAS or TP53 mutations. Patients with PD-L1 >1% or TP53 were significantly more likely to have metastatic disease to organs other than bone or brain (p=0.047 and p=0.023, respectively). We identified four prognostic groups in metastatic NSCLC. Patients with PD-L1 <1% and no actionable mutations have the poorest prognosis, with median survival of around 20 months.

Conclusion

Patients with mutations discoverable on NGS are more likely to have metastatic disease to the brain. KRAS/NRAS in particular has a predilection to metastasize to the brain and bone. PD-L1 expression and a TP53 mutation, on the other hand, tend to lead to metastasis of NSCLC to organs other than brain or bone. These results need to be corroborated in larger prospective studies.

New insights into the biology and development of lung cancer in never smokers-implications for early detection and treatment

Lung cancer is the leading cause of cancer deaths worldwide. Despite never smokers comprising between 10 and 25% of all cases, lung cancer in never smokers (LCNS) is relatively under characterized from an etiological and biological perspective. The application of multi-omics techniques on large patient cohorts has significantly advanced the current understanding of LCNS tumor biology. By synthesizing the findings of multi-omics studies on LCNS from a clinical perspective, we can directly translate knowledge regarding tumor biology into implications for patient care. Primarily focused on never smokers with lung adenocarcinoma, this review details the predominance of driver mutations, particularly in East Asian patients, as well as the frequency and importance of germline variants in LCNS. The mutational patterns present in LCNS tumors are thoroughly explored, highlighting the high abundance of the APOBEC signature. Moreover, this review recognizes the spectrum of immune profiles present in LCNS tumors and posits how it can be translated to treatment selection. The recurring and novel insights from multi-omics studies on LCNS tumor biology have a wide range of clinical implications. Risk factors such as exposure to outdoor air pollution, second hand smoke, and potentially diet have a genomic imprint in LCNS at varying degrees, and although they do not encompass all LCNS cases, they can be leveraged to stratify risk. Germline variants similarly contribute to a notable proportion of LCNS, which warrants detailed documentation of family history of lung cancer among never smokers and demonstrates value in developing testing for pathogenic variants in never smokers for early detection in the future. Molecular driver subtypes and specific co-mutations and mutational signatures have prognostic value in LCNS and can guide treatment selection. LCNS tumors with no known driver alterations tend to be stem-like and genes contributing to this state may serve as potential therapeutic targets. Overall, the comprehensive findings of multi-omics studies exert a wide influence on clinical management and future research directions in the realm of LCNS.

Advances in Genomic Data and Biomarkers: Revolutionizing NSCLC Diagnosis and Treatment

Non-small cell lung cancer (NSCLC) is a significant public health concern with high mortality rates. Recent advancements in genomic data, bioinformatics tools, and the utilization of biomarkers have improved the possibilities for early diagnosis, effective treatment, and follow-up in NSCLC. Biomarkers play a crucial role in precision medicine by providing measurable indicators of disease characteristics, enabling tailored treatment strategies. The integration of big data and artificial intelligence (AI) further enhances the potential for personalized medicine through advanced biomarker analysis. However, challenges remain in the impact of new biomarkers on mortality and treatment efficacy due to limited evidence. Data analysis, interpretation, and the adoption of precision medicine approaches in clinical practice pose additional challenges and emphasize the integration of biomarkers with advanced technologies such as genomic data analysis and artificial intelligence (AI), which enhance the potential of precision medicine in NSCLC. Despite these obstacles, the integration of biomarkers into precision medicine has shown promising results in NSCLC, improving patient outcomes and enabling targeted therapies. Continued research and advancements in biomarker discovery, utilization, and evidence generation are necessary to overcome these challenges and further enhance the efficacy of precision medicine. Addressing these obstacles will contribute to the continued improvement of patient outcomes in non-small cell lung cancer.

The role of oncogenes and tumor suppressor genes in determining survival rates of lung cancer patients in the population of North Sumatra, Indonesia

Background: Gaining a better understanding of molecular alterations in the pathogenesis of lung cancer reveals a significant change in approach to the management and prognosis of lung cancer. Several oncogenes and tumor suppressor genes have been identified and have different roles related to survival rates in lung cancer patients. This study aims to determine the role of KRAS, EGFR, and TP53 mutations in the survival rate of lung cancer patients in the population of North Sumatra. Methods: This is a retrospective cohort study involving 108 subjects diagnosed with lung cancer from histopathology specimens. DNA extractions were performed using FFPE followed by PCR examinations for assessing the expressions of EGFR, RAS, and TP53 protein. Sequencing analysis was carried out to determine the mutations of EGFR exon 19 and 21, RAS protein exon 2, and TP53 exon 5-6 and 8-9. Data input and analysis were conducted using statistical analysis software for Windows. The survival rate analysis was presented with Kaplan Meier. Results: 52 subjects completed all procedures in this study. Most of the subjects are male (75%), above 60 years old (53.8%), heavy smokers (75%), and suffer from adenocarcinoma type of lung cancer (69.2%). No subjects showed KRAS exon 2 mutations. Overall survival rates increased in patients with EGFR mutations (15 months compared to 8 months; p=0.001) and decreased in patients with TP53 mutations (7 months compared to 9 months; p=0.148). Also, there was increasing Progression-Free Survival in patients with EGFR mutations (6 months compared to 3 months) ( p=0.19) and decreasing PFS in patients with TP53 mutations (3 months compared to 6 months) ( p=0.07). Conclusions: There were no KRAS mutations in this study. EGFR mutations showed a higher survival rate, while TP53 mutations showed a lower survival rate in overall survival and progression-free survival.

Tp53 haploinsufficiency is involved in hotspot mutations and cytoskeletal remodeling in gefitinib-induced drug-resistant EGFRL858R-lung cancer mice

Tumor heterogeneity is the major factor for inducing drug resistance. p53 is the major defender to maintain genomic stability, which is a high proportion mutated in most of the cancer types. In this study, we established in vivo animal models of gefitinib-induced drug-resistant lung cancer containing EGFR^L858R and EGFR^L858R*Tp53^+/- mice to explore the molecular mechanisms of drug resistance by studying the genomic integrity and global gene expression. The cellular morphology of the lung tumors between gefitinib-induced drug-resistant mice and drug-sensitive mice were very different. In addition, in drug-resistant mice, the expression of many cytoskeleton-related genes were changed, accompanied by decreased amounts of actin filaments and increased amounts of microtubule, indicating that significant cytoskeletal remodeling is induced in gefitinib-induced drug-resistant EGFR^L858R and EGFR^L858R*Tp53^+/- lung cancer mice. The gene expression profiles and involved pathways were different in gefitinib-sensitive, gefitinib-resistant and Tp53^+/--mice. Increases in drug resistance and nuclear size (N/C ratio) were found in EGFR^L858R*Tp53^+/- drug-resistant mice. Mutational hotspot regions for drug resistance via Tp53^+/+- and Tp53^+/--mediated pathways are located on chromosome 1 and chromosome 11, respectively, and are related to prognosis of lung cancer cohorts. This study not only builds up a gefitinib-induced drug-resistant EGFR^L858R lung cancer animal model, but also provides a novel mutation profile in a Tp53^+/+- or Tp53^+/--mediated manner and induced cytoskeleton remodeling during drug resistance, which could contribute to the prevention of drug resistance during cancer therapy.

UNcommon EGFR Mutations: International Case Series on Efficacy of Osimertinib in Real-Life Practice in First-LiNe Setting (UNICORN)

INTRODUCTION

Approximately 10% of EGFR mutations (EGFRmuts) are uncommon (ucEGFRmuts). We aimed to collect real-world data about osimertinib for patients with ucEGFRmuts.

METHODS

This is a multicenter, retrospective study of ucEGFRmut (exon 20 insertions excluded) metastatic NSCLC treated with osimertinib as first EGFR inhibitor. The Response Evaluation Criteria in Solid Tumors and response assessment in neuro-oncology brain metastases brain objective response rate (ORR) were evaluated by the investigators. Median progression-free survival (mPFS), median overall survival, and median duration of response (mDOR) were calculated from osimertinib initiation. Mutations found at resistance were collected.

RESULTS

A total of 60 patients were included (22 centers, nine countries), with median age of 64 years, 75% females, and 83% Caucasian. The largest subgroups were G719X (30%), L861Q (20%), and de novo Thr790Met (T790M) (15%). The ORR was 61%, mPFS 9.5 months, mDOR 17.4 months, and median overall survival 24.5 months. Regarding patients with no concurrent common mutations or T790M (group A, n = 44), ORR was 60%, mPFS 8.6 months, and mDOR 11 months. For G719X, ORR was 47%, mPFS 8.8 months, and mDOR 9.1 months. For L861Q, ORR was 80%, mPFS 16 months, and mDOR 16 months. For de novo T790M, ORR was 44%, mPFS 12.7 months, and mDOR 46.2 months. Compound EGFRmut including common mutations had better outcome compared with only ucEGFRmut. For 13 patients with a response assessment in neuro-oncology brain metastases-evaluable brain metastases, brain ORR was 46%. For 14 patients, rebiopsy results were analyzed: four patients with additional EGFR mutation (C797S, D585Y, E709K), three with new TP53 mutation, one with c-Met amplification, one with PIK3CA mutation, and one with neuroendocrine transformation.

CONCLUSIONS

Osimertinib was found to have an activity in ucEGFRmut with a high rate of disease control systemically and intracranially. Several resistance mechanisms were identified. This report comprises, to the best of our knowledge, the largest data set of its kind.

Mutational Profiling of Lung Cancer Using Next Generation Sequencing: A Malaysian Real-World Clinical Diagnostic Experience

Lung cancer is one of the most common cancers and a leading cause of cancer-related mortality in Malaysia. This analysis aimed to evaluate the prevalence of actionable and common mutations, as well as co-mutations frequently occurring with EGFR variants in lung cancer. Mutational profiling of lung tumour samples was performed using next generation sequencing (NGS) panels at the Subang Jaya Medical Centre laboratory. A total of 469 lung tumour samples referred from several medical facilities in Malaysia were analysed and 84% were of the adenocarcinoma subtype. The three most frequent mutations found were EGFR (46.5%), TP53 (37.5%) and KRAS (14.3%). Actionable mutations with approved drug targets for lung cancer were detected in 63.5% of patient samples. Among patients with EGFR mutations, deletions in exon 19 were detected in 44.5% and p.L858R in 38.5% of samples. The most common co-mutations for samples with EGFR mutations were found in the TP53 gene (38.1%). A median turnaround time (TAT) of 3 working days was achievable with an automated NGS platform. NGS testing can provide valuable information on the mutational landscape and the prevalence of common or actionable mutations present in lung cancer patients. This real-world experience demonstrates the high percentage of actionable mutations detected and highlights the value of NGS testing in a clinical diagnostic setting.

Prognostic value of genes related to cancer-associated fibroblasts in lung adenocarcinoma

BACKGROUND

Although it has been established that cancer-associated fibroblasts (CAFs) facilitate tumor development, the relationship between CAFs and the prognosis of patients with lung adenocarcinoma (LUAD) has not been extensively explored.

OBJECTIVE

This study was formulated to investigate the prognostic value of CAF-related genes in LUAD.

METHODS

Differential analysis was carried out with TCGA-LUAD dataset as the training set. By overlapping differentially expressed genes (DEGs) with genes associated with CAF, CAF-related DEGs specific to LUAD were obtained. A prognostic risk model was constructed by Lasso and Cox regression analysis, and samples were grouped according to median risk score. The efficacy of the model was accessed through survival curve and receiver operating characteristic curve (ROC) analyses, with the validation set for verification. Risk score combined with clinical factors was utilized for Cox analysis to verify the independence of the model, and a nomogram was drawn. GSEA was performed on different risk groups. Immunologic infiltration and tumor mutational burden were assessed in different risk groups.

RESULTS

Eleven feature genes including DLGAP5, KCNE2, UPK2, NPAS2, ARHGAP11A, ANGPTL4, ANLN, DKK1, SMUG1, C16orf74, and ACAD8 were identified, based on which a prognostic model was constructed. Risk score could predict the prognosis of LUAD patients and could be an independent prognostic factor for LUAD patients. GSEA outcomes displayed significant enrichment of genes in the high-risk group in the P53 SIGNALING PATHWAY. In comparison to the low-risk group, the high-risk group exhibited a decreased degree of immune infiltration and an elevated level of tumor mutational burden.

CONCLUSION

An 11-gene model was constructed based on CAF-related genes to predict LUAD prognosis. This model represented an independent prognostic factor for LUAD.

Short-term dynamics of circulating tumor DNA predicting efficacy of sintilimab plus docetaxel in second-line treatment of advanced NSCLC: biomarker analysis from a single-arm, phase 2 trial

OBJECTIVE

Robust biomarker predicting efficacy of immunotherapy is limited. Circulating tumor DNA (ctDNA) sought to effectively monitor therapeutic response as well as disease progression. This study aims to investigate predictive role of ctDNA short-term dynamic change (6 weeks postimmunotherapy) in a single-arm, phase 2 trial of sintilimab plus docetaxel for previously treated advanced non-small cell lung cancer (NSCLC) patients.

METHODS

A total of 33 patients with advanced NSCLC with disease progression during or after any first-line treatment were prospectively enrolled between 2019 and 2020. Patients received sintilimab (200 mg, day 1, every 3 weeks) plus docetaxel (75 mg/m², day 3, every 3 weeks) for 4-6 cycles, followed by maintenance therapy with sintilimab (200 mg, day 1, every 3 weeks) until disease progression or unacceptable toxic effects. Blood samples were prospectively collected at baseline, and after 2 cycles of treatment (6 weeks post-treatment). All samples were subjected to targeted next-generation sequencing with a panel of 448 cancer-related genes. The landscape of high-frequency genomic profile of baseline and 6th week was described. Major molecular characteristics in preselected genes of interest associated with response to second-line chemoimmunotherapy were analyzed. The curative effects and prognosis of patients were evaluated.

RESULTS

Patients with ctDNA clearance at 6th week had decreased tumor volume, while most patients with positive ctDNA at 6th-week experienced an increase in tumor volume. Positive 6th-week ctDNA was associated with significantly shorter progression-free survival (PFS) (91 vs NR days; p<0.0001) and overall survival (47 vs 467 days; p =0.0039). Clearance of clonal mutations and none new clonal formation at 6th week were associated with longer PFS (mPFS 89 vs 266 days, p =0.003). ctDNA clearance at 6th week was an independent risk factor for progression or death (HR=100 (95% CI 4.10 to 2503.00), p=0.005).

CONCLUSION

ctDNA status and ctDNA mutation clearance putatively serve as predictive biomarkers for sintilimab combined with docetaxel chemotherapy in pretreated advanced NSCLC patients.

DRPreter: Interpretable Anticancer Drug Response Prediction Using Knowledge-Guided Graph Neural Networks and Transformer

Some of the recent studies on drug sensitivity prediction have applied graph neural networks to leverage prior knowledge on the drug structure or gene network, and other studies have focused on the interpretability of the model to delineate the mechanism governing the drug response. However, it is crucial to make a prediction model that is both knowledge-guided and interpretable, so that the prediction accuracy is improved and practical use of the model can be enhanced. We propose an interpretable model called DRPreter (drug response predictor and interpreter) that predicts the anticancer drug response. DRPreter learns cell line and drug information with graph neural networks; the cell-line graph is further divided into multiple subgraphs with domain knowledge on biological pathways. A type-aware transformer in DRPreter helps detect relationships between pathways and a drug, highlighting important pathways that are involved in the drug response. Extensive experiments on the GDSC (Genomics of Drug Sensitivity and Cancer) dataset demonstrate that the proposed method outperforms state-of-the-art graph-based models for drug response prediction. In addition, DRPreter detected putative key genes and pathways for specific drug-cell-line pairs with supporting evidence in the literature, implying that our model can help interpret the mechanism of action of the drug.

Radiogenomic System for Non-Invasive Identification of Multiple Actionable Mutations and PD-L1 Expression in Non-Small Cell Lung Cancer Based on CT Images

PURPOSE

Personalized treatments such as targeted therapy and immunotherapy have revolutionized the predominantly therapeutic paradigm for non-small cell lung cancer (NSCLC). However, these treatment decisions require the determination of targetable genomic and molecular alterations through invasive genetic or immunohistochemistry (IHC) tests. Numerous previous studies have demonstrated that artificial intelligence can accurately predict the single-gene status of tumors based on radiologic imaging, but few studies have achieved the simultaneous evaluation of multiple genes to reflect more realistic clinical scenarios.

METHODS

We proposed a multi-label multi-task deep learning (MMDL) system for non-invasively predicting actionable NSCLC mutations and PD-L1 expression utilizing routinely acquired computed tomography (CT) images. This radiogenomic system integrated transformer-based deep learning features and radiomic features of CT volumes from 1096 NSCLC patients based on next-generation sequencing (NGS) and IHC tests.

RESULTS

For each task cohort, we randomly split the corresponding dataset into training (80%), validation (10%), and testing (10%) subsets. The area under the receiver operating characteristic curves (AUCs) of the MMDL system achieved 0.862 (95% confidence interval (CI), 0.758-0.969) for discrimination of a panel of 8 mutated genes, including EGFR, ALK, ERBB2, BRAF, MET, ROS1, RET and KRAS, 0.856 (95% CI, 0.663-0.948) for identification of a 10-molecular status panel (previous 8 genes plus TP53 and PD-L1); and 0.868 (95% CI, 0.641-0.972) for classifying EGFR / PD-L1 subtype, respectively.

CONCLUSIONS

To the best of our knowledge, this study is the first deep learning system to simultaneously analyze 10 molecular expressions, which might be utilized as an assistive tool in conjunction with or in lieu of ancillary testing to support precision treatment options.

Serum Metabolomics Profiling Reveals Metabolic Alterations Prior to a Diagnosis with Non-Small Cell Lung Cancer among Chinese Community Residents: A Prospective Nested Case-Control Study

The present high mortality of lung cancer in China stems mainly from the lack of feasible, non-invasive and early disease detection biomarkers. Serum metabolomics profiling to reveal metabolic alterations could expedite the disease detection process and suggest those patients who are harboring disease. Using a nested case-control design, we applied ultra-high-performance liquid chromatography/mass spectrometry (LC-MS)-based serum metabolomics to reveal the metabolomic alterations and to indicate the presence of non-small cell lung cancer (NSCLC) using serum samples collected prior to disease diagnoses. The studied serum samples were collected from 41 patients before a NSCLC diagnosis (within 3.0 y) and 38 matched the cancer-free controls from the prospective Shanghai Suburban Adult Cohort. The NSCLC patients markedly presented cellular metabolism alterations in serum samples collected prior to their disease diagnoses compared with the cancer-free controls. In total, we identified 18 significantly expressed metabolites whose relative abundance showed either an upward or a downward trend, with most of them being lipid and lipid-like molecules, organic acids, and nitrogen compounds. Choline metabolism in cancer, sphingolipid, and glycerophospholipid metabolism emerged as the significant metabolic disturbance of NSCLC. The metabolites involved in these biological processes may be the distinctive features associated with NSCLC prior to a diagnosis.