Hsa_circ_0096157 silencing suppresses autophagy and reduces cisplatin resistance in non-small cell lung cancer by weakening the Nrf2/ARE signaling pathway.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the leading cause of cancer morbidity and mortality worldwide, and new diagnostic markers are urgently needed. We aimed to investigate the mechanism by which hsa_circ_0096157 regulates autophagy and cisplatin (DDP) resistance in NSCLC. METHODS: A549 cells were treated with DDP (0 µg/mL or 3 µg/mL). Then, the autophagy activator rapamycin (200 nm) was applied to the A549/DDP cells. Moreover, hsa_circ_0096157 and Nrf2 were knocked down, and Nrf2 was overexpressed in A549/DDP cells. The expression of Hsa_circ_0096157, the Nrf2/ARE pathway-related factors Nrf2, HO-1, and NQO1, and the autophagy-related factors LC3, Beclin-1, and p62 was evaluated by qRT‒PCR or western blotting. Autophagosomes were detected through TEM. An MTS assay was utilized to measure cell proliferation. The associated miRNA levels were also tested by qRT‒PCR. RESULTS: DDP (3 µg/mL) promoted hsa_circ_0096157, LC3 II/I, and Beclin-1 expression and decreased p62 expression. Knocking down hsa_circ_0096157 resulted in the downregulation of LC3 II/I and Beclin-1 expression, upregulation of p62 expression, and decreased proliferation. Rapamycin reversed the effect of interfering with hsa_circ_0096157. Keap1 expression was lower, and Nrf2, HO-1, and NQO1 expression was greater in the A549/DDP group than in the A549 group. HO-1 expression was repressed after Nrf2 interference. In addition, activation of the Nrf2/ARE pathway promoted autophagy in A549/DDP cells. Moreover, hsa_circ_0096157 activated the Nrf2/ARE pathway. The silencing of hsa_circ_0096157 reduced Nrf2 expression by releasing miR-142-5p or miR-548n. Finally, we found that hsa_circ_0096157 promoted A549/DDP cell autophagy by activating the Nrf2/ARE pathway. CONCLUSION: Knockdown of hsa_circ_0096157 inhibits autophagy and DDP resistance in NSCLC cells by downregulating the Nrf2/ARE signaling pathway.

Time-dependent efficacy analysis of first-line immunotherapies for advanced non-small cell lung cancer.

BACKGROUND: Many randomized controlled trials (RCTs) and network meta-analyses have demonstrated that the progression-free survival (PFS) and overall survival (OS) of advanced non-small cell lung cancer (NSCLC) patients can be improved through combination immunotherapy or monotherapies. However, time-dependent analysis of the treatment effect is currently lacking. Thus, we aimed to evaluate the efficacy of first-line immunotherapy, and establish a hazard ratio function to reflect the time-varying progression or mortality risk of patients with NSCLC. METHODS: Seventeen clinical trials were selected based on search strategy. Baseline characteristics, including the age, sex, smoking status, geographical region, and Eastern Cooperative Oncology Group (ECOG) performance status of patients, were balanced, resulting in ten immunotherapies from nine appropriate clinical trials to conduct treatment effect comparison. RESULTS: We found that nivolumab plus ipilimumab (nivo + ipi) improved the PFS and OS over time. The hazard ratio of nivo + ipi, relative to that of pembrolizumab, decreased from 1.11 to 0.36 for PFS, and from 0.93 to 0.49 for OS over a 10-year period. In terms of the response to immunotherapy in patients with different PD-L1 expression levels, patients with PD-L1 > = 50% experienced lower rates of progression and a reduced mortality risk over time. The hazard ratio of patients with PD-L1 > = 50% relative to all of the patients decreased from 0.73 to 0.69 for PFS, and from 0.78 to 0.67 for OS. CONCLUSIONS: Based on the fact that time-dependent progression and mortality risk existed during the treatment duration, physicians should select a suitable treatment regimen for patients based on the hazard ratio.

Heterogeneity in PD-L1 expression between primary and metastatic lymph nodes: a predictor of EGFR-TKI therapy response in non-small cell lung cancer.

BACKGROUND: There is inconclusive evidence to suggest that the expression of programmed cell death ligand 1 (PD-L1) is a putative predictor of response to EGFR-TKI therapy in advanced EGFR-mutant non-small cell lung cancer (NSCLC). We evaluated the heterogeneity in PD-L1 expression in the primary lung site and metastatic lymph nodes to analyze the association between PD-L1 expression and response for patients treated with EGFR-TKI. METHODS: This study reviewed 184 advanced NSCLC patients with EGFR mutations who received first-generation EGFR-TKI as first-line treatment from 2020 to 2021 at Shanghai Chest Hospital. The patients were divided into the primary lung site group (n = 100) and the metastatic lymph nodes group (n = 84) according to the biopsy site. The patients in each group were divided into TPS < 1%, TPS 1-49%, and TPS ≥ 50% groups according to PD-L1 expression. RESULTS: The median PFS was 7 (95% CI: 5.7-8.3) months, and the median OS was 26 (95% CI: 23.5-28.5) months for all patients. No correlation existed between PFS or OS and PD-L1 expression. The median PFS in the primary lung site group was 11 months (95% CI: 9.6-12.4) in the TPS < 1% group, 8 months (95% CI: 6.6-9.4) in TPS 1-49% group, and 4 months (95% CI: 3.2-4.8) in TPS ≥ 50% group, with statistically significant differences (p = 0.000). The median OS of the TPS < 1% group and TPS ≥ 50% group showed a statistically significant difference (p = 0.008) in the primary lung site group. In contrast, PD-L1 expression in the lymph nodes of EGFR-mutant patients was unrelated to PFS or OS after EGFR-TKI therapy. CONCLUSION: PD-L1 expression from the primary lung site might predict clinical benefit from EGFR-TKI, whereas PD-L1 from metastatic lymph nodes did not. TRIAL REGISTRATION: This retrospective study was approved by the Ethics Committee of Shanghai Chest Hospital (ID: IS23060) and performed following the Helsinki Declaration of 1964 (revised 2008).

LINC01133 contributes to the malignant phenotypes of non-small cell lung cancer by targeting miR-30b-5p/FOXA1 pathway.

This study aimed to explore the mechanism of action of LINC01133 in non-small cell lung cancer. LINC01133 expression in NSCLC patient tissues and cells was detected by qRT-PCR. After transfecting siRNA-LINC01133 in NSCLC cells, the proliferation and invasive migration ability of the cells were assessed via CCK-8 and Transwell assay, respectively. The sublocalization of LINC01133 in NSCLC cells was analyzed by bioinformatics prediction and nucleoplasm separation assay and RNA-FISH assay. Analysis of the binding relationship between LINC01133, FOXA1 and miR-30b-5p was all through bioinformatics website analysis, dual-luciferase reporter and RNA Pulldown assay. Functional rescue experiments confirmed the character of miR-30b-5p and FOXA1 in LINC01133 regulating the NSCLC cells biological behavior. LINC01133 high expressions were found in NSCLC tissues and cells. siRNA-LINC01133 treatment inhibited NSCLC cells malignant behavior. Mechanistically: LINC01133 promoted FOXA1 expression through adsorption binding of miR-30b-5p. Knocking down miR-30b-5p expression or up-regulating FOXA1 expression was able to reverse siRNA-LINC01133 inhibitory effect of tumor cell malignant behavior. LINC01133 promoted FOX1 expression by competitively binding miR-30b-5p, which attenuated the targeting inhibitory effect of miR-30b-5p on FOXA1 and ultimately promoted proliferation and invasive migration of NSCLC cells.

LINC00472 suppresses non-small cell lung cancer progression via regulating miR-23a-3p/CCL22 axis.

Long non-coding RNA (lncRNA) LINC00472 has a close connection with the development of tumors. The aim was to explore the role of LINC00472 on NSCLC cell biological function in vivo and its potential mechanisms. The mRNA levels of LncRNA 00472 and microRNA-23a-3p, were determined by RT-qPCR. Cell Counting Kit-8, cell scratches and western blot assays were used to analyze the proliferation, migration and level of apoptosis-associated proteins. Luciferase reporter assay validates the binding between LINC00472/CCL22 and miR-23a-3p. LINC00472 and CCL22 were lowly expressed in NSCLC tissues and cells, while miR-23a-3p expression was upregulated. LINC00472 overexpression significantly depressed NSCLC cell cellular behavior, whereas promoting cell death. MiR-23a-3p could reverse these above-mentioned biological behavior changes caused by LINC00472 overexpression. Additionally, LINC00472 increased CCL22 expression through sponging miR-23a-3p. Knocking down CCL22 antagonized the inhibitory effect of LINC00472 on NSCLC cell survival. LINC00472 may reduce the cellular growth, and accelerate death of NSCLC through increasing CCL22 expression by targeting miR-23a-3p.

Significance of metastatic lymph nodes ratio in overall survival for patients with resected nonsmall cell lung cancer: a retrospective cohort study.

OBJECTIVE: The tumor, node and metastasis stage is widely applied to classify lung cancer and is the foundation of clinical decisions. However, increasing studies have pointed out that this staging system is not precise enough for the N status. In this study, we aim to build a convenient survival prediction model that incorporates the current items of lymph node status. METHODS: We performed a retrospective cohort study and collected the data from resectable nonsmall cell lung cancer (NSCLC) (IA-IIIB) patients from the Surveillance, Epidemiology, and End Results database (2006-2015). The x-tile program was applied to calculate the optimal threshold of metastatic lymph node ratio (MLNR). Then, independent prognostic factors were determined by multivariable Cox regression analysis and enrolled to build a nomogram model. The calibration curve as well as the Concordance Index (C-index) were selected to evaluate the nomogram. Finally, patients were grouped based on their specified risk points and divided into three risk levels. The prognostic value of MLNR and examined lymph node numbers (ELNs) were presented in subgroups. RESULTS TOTALLY,: 40853 NSCLC patients after surgery were finally enrolled and analyzed. Age, metastatic lymph node ratio, histology type, adjuvant treatment and American Joint Committee on Cancer 8th T stage were deemed as independent prognostic parameters after multivariable Cox regression analysis. A nomogram was built using those variables, and its efficiency in predicting patients' survival was better than the conventional American Joint Committee on Cancer stage system after evaluation. Our new model has a significantly higher concordance Index (C-index) (training set, 0.683 v 0.641, respectively; P < 0.01; testing set, 0.676 v 0.638, respectively; P < 0.05). Similarly, the calibration curve shows the nomogram was in better accordance with the actual observations in both cohorts. Then, after risk stratification, we found that MLNR is more reliable than ELNs in predicting overall survival. CONCLUSION: We developed a nomogram model for NSCLC patients after surgery. This novel and useful tool outperforms the widely used tumor, node and metastasis staging system and could benefit clinicians in treatment options and cancer control.

Integrin αVß1-activated PYK2 promotes the progression of non-small-cell lung cancer via the STAT3-VGF axis.

BACKGROUND: Non-small-cell lung cancer (NSCLC) accounts for 80-85% of all lung cancer and is the leading cause of cancer-related deaths globally. Although various treatment strategies have been introduced, the 5-year survival rate of patients with NSCLC is only 20-30%. Thus, it remains necessary to study the pathogenesis of NSCLC and develop new therapeutic drugs. Notably, PYK2 has been implicated in the progression of many tumors, including NSCLC, but its detailed mechanism remains unclear. In this study, we aimed to elucidate the mechanisms through which PYK2 promotes NSCLC progression. METHODS: The mRNA and protein levels of various molecules were measured using qRT-PCR, western blot (WB), and immunohistochemistry (IHC), respectively. We established stable PYK2 knockdown and overexpression cell lines, and CCK-8, EdU, and clonogenic assays; wound healing, transwell migration, and Matrigel invasion assays; and flow cytometry were employed to assess the phenotypes of tumor cells. Protein interactions were evaluated with co-immunoprecipitation (co-IP), immunofluorescence (IF)-based colocalization, and nucleocytoplasmic separation assays. RNA sequencing was performed to explore the transcriptional regulation mediated by PYK2. Secreted VGF levels were examined using ELISA. Dual-luciferase reporter system was used to detect transcriptional regulation site. PF4618433 (PYK2 inhibitor) and Stattic (STAT3 inhibitor) were used for rescue experiments. A public database was mined to analyze the effect of these molecules on NSCLC prognosis. To investigate the role of PYK2 in vivo, mouse xenograft models of lung carcinoma were established and examined. RESULTS: The protein level of PYK2 was higher in human NSCLC tumors than in the adjacent normal tissue, and higher PYK2 expression was associated with poorer prognosis. PYK2 knockdown inhibited the proliferation and motility of tumor cells and caused G1-S arrest and cyclinD1 downregulation in A549 and H460 cells. Meanwhile, PYK2 overexpression had the opposite effect in H1299 cells. The siRNA-induced inhibition of integrins alpha V and beta 1 led to the downregulation of p-PYK2(Tyr402). Activated PYK2 could bind to STAT3 and enhance its phosphorylation at Tyr705, regulating the nuclear accumulation of p-STAT3(Tyr705). This further promoted the expression of VGF, as confirmed by RNA sequencing in a PYK2-overexpressing H1299 cell line and validated by rescue experiments. Two sites in promoter region of VGF gene were confirmed as binding sites of STAT3 by Dual-luciferase assay. Data from the TGCA database showed that VGF was related to the poor prognosis of NSCLC. IHC revealed higher p-PYK2(Tyr402) and VGF expression in lung tumors than in adjacent normal tissues. Moreover, both proteins showed higher levels in advanced TNM stages than earlier ones. A positive linear correlation existed between the IHC score of p-PYK2(Tyr402) and VGF. Knockdown of VGF inhibited tumor progression and reversed the tumor promoting effect of PYK2 overexpression in NSCLC cells. Finally, the mouse model exhibited enhanced tumor growth when PYK2 was overexpressed, while the inhibitors PF4618433 and Stattic could attenuate this effect. CONCLUSIONS: The Integrin αVß1-PYK2-STAT3-VGF axis promotes NSCLC development, and the PYK2 inhibitor PF4618433 and STAT3 inhibitor Stattic can reverse the pro-tumorigenic effect of high PYK2 expression in mouse models. Our findings provide insights into NSCLC progression and could guide potential therapeutic strategies against NSCLC with high PYK2 expression levels.

Clinicopathological and prognostic implications of EGFR mutations subtypes in Moroccan non-small cell lung cancer patients: A first report.

BACKGROUND: Non-small cell lung cancer (NSCLC) remains a significant global health concern, with EGFR mutations playing a pivotal role in guiding treatment decisions. This prospective study investigated the prevalence and clinical implications of EGFR mutations in Moroccan NSCLC patients. METHODS: A cohort of 302 NSCLC patients was analyzed for EGFR mutations using multiple techniques. Demographic, clinical, and pathological characteristics were assessed, and overall survival (OS) outcomes were compared among different EGFR mutation subtypes. RESULTS: EGFR mutations were present in 23.5% of patients, with common mutations (81.69%) dominating. Common mutations showed strong associations with female gender and non-smoking status, while rare mutations were associated with a positive smoking history. Patients with EGFR mutations receiving tyrosine kinase inhibitors (TKIs) had significantly improved OS compared to wild-type EGFR patients. Notably, patients with common EGFR mutations had the highest OS, while those with rare mutations had a shorter survival period, albeit not statistically significant. CONCLUSION: This study highlights the relevance of EGFR mutation status in NSCLC patients, particularly in therapeutic decision-making. The association between smoking history and rare mutations suggests the need for tailored approaches. The survival advantage for patients with common EGFR mutations underscores the significance of personalized treatment strategies.

Predicting treatment response in multicenter non-small cell lung cancer patients based on federated learning.

BACKGROUND: Multicenter non-small cell lung cancer (NSCLC) patient data is information-rich. However, its direct integration becomes exceptionally challenging due to constraints involving different healthcare organizations and regulations. Traditional centralized machine learning methods require centralizing these sensitive medical data for training, posing risks of patient privacy leakage and data security issues. In this context, federated learning (FL) has attracted much attention as a distributed machine learning framework. It effectively addresses this contradiction by preserving data locally, conducting local model training, and aggregating model parameters. This approach enables the utilization of multicenter data with maximum benefit while ensuring privacy safeguards. Based on pre-radiotherapy planning target volume images of NSCLC patients, a multicenter treatment response prediction model is designed by FL for predicting the probability of remission of NSCLC patients. This approach ensures medical data privacy, high prediction accuracy and computing efficiency, offering valuable insights for clinical decision-making. METHODS: We retrospectively collected CT images from 245 NSCLC patients undergoing chemotherapy and radiotherapy (CRT) in four Chinese hospitals. In a simulation environment, we compared the performance of the centralized deep learning (DL) model with that of the FL model using data from two sites. Additionally, due to the unavailability of data from one hospital, we established a real-world FL model using data from three sites. Assessments were conducted using measures such as accuracy, receiver operating characteristic curve, and confusion matrices. RESULTS: The model's prediction performance obtained using FL methods outperforms that of traditional centralized learning methods. In the comparative experiment, the DL model achieves an AUC of 0.718/0.695, while the FL model demonstrates an AUC of 0.725/0.689, with real-world FL model achieving an AUC of 0.698/0.672. CONCLUSIONS: We demonstrate that the performance of a FL predictive model, developed by combining convolutional neural networks (CNNs) with data from multiple medical centers, is comparable to that of a traditional DL model obtained through centralized training. It can efficiently predict CRT treatment response in NSCLC patients while preserving privacy.

Molecular analysis of genetic mutations in non-small cell lung cancer in Morocco.

Non-small cell lung cancer (NSCLC) is a significant global health issue with diverse molecular profiles affecting treatment responses. Yet, NSCLC's molecular epidemiology in Morocco is largely unexplored. This study focuses on NSCLC genetic mutations, specifically in adenocarcinoma, among Moroccan patients to contribute to understanding NSCLC in this population. Ninety-four patients diagnosed with lung adenocarcinoma were analyzed. Formalin-fixed paraffin-embedded tissue samples were processed, and deoxyribonucleic acid (DNA)/ribonucleic acid (RNA) was extracted using standardized protocols. Mutations were detected using the AmoyDx Pan Lung Cancer Polymerase Chain Reaction (PCR) Panel kit, and their frequencies were assessed through statistical analysis. Epidermal Growth Factor Receptor (EGFR) mutations were detected in 22.34% of patients, predominantly exon 19 deletions (66.66%) and exon 21 L858R mutations (23.80%). Anaplastic lymphoma kinase (ALK) gene fusion was observed in 3.19% of patients, and KRAS mutations in 1.06%. No mutations were found in other tested genes. A slightly higher mutation rate was noted in females (54.16%) compared to males (45.84%). The study reveals a distinct mutation profile in Moroccan NSCLC patients, with a notable prevalence of EGFR mutations, albeit lower than in some Asian populations. The significance of EGFR mutations in treatment response aligns with global findings, highlighting the importance of understanding regional molecular variations for personalized therapy. Despite limitations in sample size and clinical data, this study sheds light on the genetic landscape of NSCLC in Morocco. The observed mutation rates, particularly in EGFR, underscore the potential for targeted therapies in Moroccan NSCLC patients, emphasizing the need for further research to refine treatment strategies tailored to this population.

Remodelin delays non-small cell lung cancer progression by inhibiting NAT10 via the EMT pathway.

BACKGROUND: Lung cancer remains the foremost reason of cancer-related mortality, with invasion and metastasis profoundly influencing patient prognosis. N-acetyltransferase 10 (NAT10) catalyzes the exclusive N (4)-acetylcytidine (ac4C) modification in eukaryotic RNA. NAT10 dysregulation is linked to various diseases, yet its role in non-small cell lung cancer (NSCLC) invasion and metastasis remains unclear. Our study delves into the clinical significance and functional aspects of NAT10 in NSCLC. METHODS: We investigated NAT10's clinical relevance using The Cancer Genome Atlas (TCGA) and a group of 98 NSCLC patients. Employing WB, qRT-PCR, and IHC analyses, we assessed NAT10 expression in NSCLC tissues, bronchial epithelial cells (BECs), NSCLC cell lines, and mouse xenografts. Further, knockdown and overexpression techniques (siRNA, shRNA, and plasmid) were employed to evaluate NAT10's effects. A series of assays were carried out, including CCK-8, colony formation, wound healing, and transwell assays, to elucidate NAT10's role in proliferation, invasion, and metastasis. Additionally, we utilized lung cancer patient-derived 3D organoids, mouse xenograft models, and Remodelin (NAT10 inhibitor) to corroborate these findings. RESULTS: Our investigations revealed high NAT10 expression in NSCLC tissues, cell lines and mouse xenograft models. High NAT10 level correlated with advanced T stage, lymph node metastasis and poor overall survive. NAT10 knockdown curtailed proliferation, invasion, and migration, whereas NAT10 overexpression yielded contrary effects. Furthermore, diminished NAT10 levels correlated with increased E-cadherin level whereas decreased N-cadherin and vimentin expressions, while heightened NAT10 expression displayed contrasting results. Notably, Remodelin efficiently attenuated NSCLC proliferation, invasion, and migration by inhibiting NAT10 through the epithelial-mesenchymal transition (EMT) pathway. CONCLUSIONS: Our data underscore NAT10 as a potential therapeutic target for NSCLC, presenting avenues for targeted intervention against lung cancer through NAT10 inhibition.

PPIA dictates NRF2 stability to promote lung cancer progression.

Nuclear factor erythroid 2-related factor 2 (NRF2) hyperactivation has been established as an oncogenic driver in a variety of human cancers, including non-small cell lung cancer (NSCLC). However, despite massive efforts, no specific therapy is currently available to target NRF2 hyperactivation. Here, we identify peptidylprolyl isomerase A (PPIA) is required for NRF2 protein stability. Ablation of PPIA promotes NRF2 protein degradation and blocks NRF2-driven growth in NSCLC cells. Mechanistically, PPIA physically binds to NRF2 and blocks the access of ubiquitin/Kelch Like ECH Associated Protein 1 (KEAP1) to NRF2, thus preventing ubiquitin-mediated degradation. Our X-ray co-crystal structure reveals that PPIA directly interacts with a NRF2 interdomain linker via a trans-proline 174-harboring hydrophobic sequence. We further demonstrate that an FDA-approved drug, cyclosporin A (CsA), impairs the interaction of NRF2 with PPIA, inducing NRF2 ubiquitination and degradation. Interestingly, CsA interrupts glutamine metabolism mediated by the NRF2/KLF5/SLC1A5 pathway, consequently suppressing the growth of NRF2-hyperactivated NSCLC cells. CsA and a glutaminase inhibitor combination therapy significantly retard tumor progression in NSCLC patient-derived xenograft (PDX) models with NRF2 hyperactivation. Our study demonstrates that targeting NRF2 protein stability is an actionable therapeutic approach to treat NRF2-hyperactivated NSCLC.

[18F]FAPI adds value to [18F]FDG PET/CT for diagnosing lymph node metastases in stage I-IIIA non-small cell lung cancer: a prospective study.

BACKGROUND: This study investigates the value of fluorine 18 ([18F])-labeled fibroblast activation protein inhibitor (FAPI) for lymph node (LN) metastases in patients with stage I-IIIA non-small cell lung cancer (NSCLC). METHODS: From November 2021 to October 2022, 53 patients with stage I-IIIA NSCLC who underwent radical resection were prospectively included. [18F]-fluorodeoxyglucose (FDG) and [18F]FAPI examinations were performed within one week. LN staging was validated using surgical and pathological findings. [18F]FDG and [18F]FAPI uptake was compared using the Wilcoxon signed-ranks test. Furthermore, the diagnostic value of nodal groups was investigated. RESULTS: In 53 patients (median age, 64 years, range: 31-76 years), the specificity of [18F]FAPI for detecting LN metastasis was significantly higher than that of [18F]FDG (P < 0.001). High LN risk category, greater LN short-axis dimension(≥ 1.0 cm), absence of LN calcification or high-attenuation, and higher LN FDG SUVmax (≥ 10.1) were risk factors for LN metastasis(P < 0.05). The concurrence of these four risk factors accurately predicted LN metastases (Positive Predictive Value [PPV] 100%), whereas the presence of one to three risk factors was unable to accurately discriminate the nature of LNs (PPV 21.7%). Adding [18F]FAPI in this circumstance improved the diagnostic value. LNs with an [18F]FAPI SUVmax<6.2 were diagnosed as benign (Negative Predictive Value 93.8%), and LNs with an [18F]FAPI SUVmax≥6.2 without calcification or high-attenuation were diagnosed as LN metastasis (PPV 87.5%). Ultimately, the integration of [18F]FDG and [18F]FAPI PET/CT resulted in the highest accuracy for N stage (83.0%) and clinical decision revisions for 29 patients. CONCLUSION: In patients with stage I-IIIA NSCLC, [18F]FAPI contributed additional valuable information to reduce LN diagnostic uncertainties after [18F]FDG PET/CT. Integrating [18F]FDG and [18F]FAPI PET/CT resulted in more precise clinical decisions. TRIAL REGISTRATION: The Chinese Clinical Trial Registry: ChiCTR2100044944 (Registered: 1 April 2021, https://www.chictr.org.cn/showprojEN.html?proj=123995 ).

Does clinical T1N0 GGN really require checking for distant metastasis during initial staging for lung cancer?

BACKGROUND: Accurate clinical staging is crucial for selection of optimal oncological treatment strategies in non-small cell lung cancer (NSCLC). Although brain MRI, bone scintigraphy and whole-body PET/CT play important roles in detecting distant metastases, there is a lack of evidence regarding the indication for metastatic staging in early NSCLCs, especially ground-grass nodules (GGNs). Our aim was to determine whether checking for distant metastasis is required in cases of clinical T1N0 GGN. METHODS: This was a retrospective study of initial staging using imaging tests in patients who had undergone complete surgical R0 resection for clinical T1N0 Stage IA NSCLC. RESULTS: A total of 273 patients with cT1N0 GGNs (n = 183) or cT1N0 solid tumors (STs, n = 90) were deemed eligible. No cases of distant metastasis were detected on initial routine imaging evaluations. Among all cT1N0M0 cases, there were 191 incidental findings on various modalities (128 in the GGN). Most frequently detected on brain MRI was cerebral leukoaraiosis, which was found in 98/273 (35.9%) patients, while cerebral infarction was detected in 12/273 (4.4%) patients. Treatable neoplasms, including brain meningioma and thyroid, gastric, renal and colon cancers were also detected on PET/CT (and/or MRI). Among those, 19 patients were diagnosed with a treatable disease, including other-site cancers curable with surgery. CONCLUSIONS: Extensive staging (MRI, scintigraphy, PET/CT etc.) for distant metastasis is not required for patients diagnosed with clinical T1N0 GGNs, though various imaging modalities revealed the presence of adventitious diseases with the potential to increase surgical risks, lead to separate management, and worsen patient outcomes, especially in elderly patients. If clinically feasible, it could be considered to complement staging with whole-body procedures including PET/CT.

Oligo-residual disease in PD-1/PD-L1 inhibitor-treated metastatic non-small cell lung cancer: incidence, pattern of failure, and clinical value of local consolidative therapy.

OBJECTIVES: To investigate the feasibility and potential clinical value of local consolidative therapy (LCT) in PD-1/PD-L1 inhibitor-treated metastatic non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: PD-1/PD-L1 inhibitor-treated metastatic NSCLC patients with measurable disease in three academic centers were screened and those with adequate follow-up were included. Oligo-residual disease (ORD) was defined as residual tumors limited to three organs and five lesions evaluated at the best response among patients with partial response or stable disease after PD-1/PD-L1 inhibitors. Oligometastatic and multiple-metastatic disease (OMD/MMD) were similarly classified at baseline. Locoregional interventions, administered after effective treatment of PD-1/PD-L1 inhibitors and before initial disease progression, were defined as LCT. Patterns of initial progressive disease (PD) were classified as involving only residual sites (RP), only new sites (NP), or a combination of both (BP). RESULTS: Among the 698 patients included, ORD was documented in 73 (47.1%) of 155 patients with baseline OMD and 60 (11.0%) of 543 patients with baseline MMD. With a median follow-up of 31.0 (range, 6.0-53.0) months, 108 patients with ORD developed initial PD, with RP, NP, and BP occurring in 51 (47%), 23 (21.3%), and 34 (31.5%), respectively. Among the 133 patients with ORD, those receiving LCT (n = 43) had longer progression-free survival (HR = 0.58, 95% CI 0.40-0.85, p = 0.01) and overall survival (HR = 0.49, 95% CI 0.30-0.79, p < 0.0001). CONCLUSION: ORD occurs with a clinically relevant frequency among PD-1/PD-L1 inhibitor-treated metastatic NSCLC patients and LCT may provide extra survival benefits in those with ORD.

Two nomograms constructed for predicting the efficacy and prognosis of advanced non­small cell lung cancer patients treated with anti­PD­1 inhibitors based on the absolute counts of lymphocyte subsets.

BACKGROUND: Patients treated with immune checkpoint inhibitors (ICIs) are at risk of considerable adverse events, and the ongoing struggle is to accurately identify the subset of patients who will benefit. Lymphocyte subsets play a pivotal role in the antitumor response, this study attempted to combine the absolute counts of lymphocyte subsets (ACLS) with the clinicopathological parameters to construct nomograms to accurately predict the prognosis of advanced non-small cell lung cancer (aNSCLC) patients treated with anti-PD-1 inhibitors. METHODS: This retrospective study included a training cohort (n = 200) and validation cohort (n = 100) with aNSCLC patients treated with anti-PD-1 inhibitors. Logistic and Cox regression were conducted to identify factors associated with efficacy and progression-free survival (PFS) respectively. Nomograms were built based on independent influencing factors, and assessed by the concordance index (C-index), calibration curve and receiver operating characteristic (ROC) curve. RESULT: In training cohort, lower baseline absolute counts of CD3+ (P < 0.001) and CD4+ (P < 0.001) were associated with for poorer efficacy. Hepatic metastases (P = 0.019) and lower baseline absolute counts of CD3+ (P < 0.001), CD4+ (P < 0.001), CD8+ (P < 0.001), and B cells (P = 0.042) were associated with shorter PFS. Two nomograms to predict efficacy at 6-week after treatment and PFS at 4-, 8- and 12-months were constructed, and validated in validation cohort. The area under the ROC curve (AUC-ROC) of nomogram to predict response was 0.908 in training cohort and 0.984 in validation cohort. The C-index of nomogram to predict PFS was 0.825 in training cohort and 0.832 in validation cohort. AUC-ROC illustrated the nomograms had excellent discriminative ability. Calibration curves showed a superior consistence between the nomogram predicted probability and actual observation. CONCLUSION: We constructed two nomogram based on ACLS to help clinicians screen of patients with possible benefit and make individualized treatment decisions by accurately predicting efficacy and PFS for advanced NSCLC patient treated with anti-PD-1 inhibitors.

SIRPG expression positively associates with an inflamed tumor microenvironment and response to PD-1 blockade.

BACKGROUND: This study aimed to investigate the relationship between signal regulatory protein gamma (SIRPG) and tumor immune microenvironment phenotypes or T cell mediated-adaptive antitumor immunity, and its predictive value for response to PD-1 blockade in cancers. METHODS: Pan-cancer analysis of SIRPG expression and immune deconvolution was performed using transcriptomic data across 33 tumor types. Transcriptomic and clinical data from 157 patients with non-small-cell lung cancer (NSCLC) and melanoma received PD-1 blockade were analyzed. Expression characteristics of SIRPG were investigated using single-cell RNA sequencing (scRNA-seq) data of 103,599 cells. The effect of SIRPG expression was evaluated via SIRPG knockdown or overexpression in Jurkat T cells. RESULTS: The results showed that most cancers with high SIRPG expression had significantly higher abundance of T cells, B cells, NK cells, M1 macrophages and cytotoxic lymphocytes and increased expression level of immunomodulatory factors regulating immune cell recruitment, antigen presentation, T cell activation and cytotoxicity, but markedly lower abundance of neutrophils, M2 macrophages, and myeloid-derived suppressor cells. High SIRPG expression was associated with favorable response to PD-1 blockade in both NSCLC and melanoma. scRNA-seq data suggested SIRPG was mainly expressed in CD8+ exhausted T and CD4+ regulatory T cells, and positively associated with immune checkpoint expression including PDCD1 and CTLA4. In vitro test showed SIRPG expression in T cells could facilitate expression of PDCD1 and CTLA4. CONCLUSION: High SIRPG expression is associated with an inflamed immune phenotype in cancers and favorable response to PD-1 blockade, suggesting it would be a promising predictive biomarker for PD-1 blockade and novel immunotherapeutic target.

Integration of deep learning and habitat radiomics for predicting the response to immunotherapy in NSCLC patients.

BACKGROUND: The non-invasive biomarkers for predicting immunotherapy response are urgently needed to prevent both premature cessation of treatment and ineffective extension. This study aimed to construct a non-invasive model for predicting immunotherapy response, based on the integration of deep learning and habitat radiomics in patients with advanced non-small cell lung cancer (NSCLC). METHODS: Independent patient cohorts from three medical centers were enrolled for training (n = 164) and test (n = 82). Habitat imaging radiomics features were derived from sub-regions clustered from individual's tumor by K-means method. The deep learning features were extracted based on 3D ResNet algorithm. Pearson correlation coefficient, T test and least absolute shrinkage and selection operator regression were used to select features. Support vector machine was applied to implement deep learning and habitat radiomics, respectively. Then, a combination model was developed integrating both sources of data. RESULTS: The combination model obtained a strong well-performance, achieving area under receiver operating characteristics curve of 0.865 (95% CI 0.772-0.931). The model significantly discerned high and low-risk patients, and exhibited a significant benefit in the clinical use. CONCLUSION: The integration of deep-leaning and habitat radiomics contributed to predicting response to immunotherapy in patients with NSCLC. The developed integration model may be used as potential tool for individual immunotherapy management.

Insights into the heterogeneity of the tumor microenvironment in lung adenocarcinoma and squamous carcinoma through single-cell transcriptomic analysis: Implications for distinct immunotherapy outcomes.

BACKGROUND: Immune checkpoint blockade has emerged as a key strategy to the therapy landscape of non-small cell lung cancer (NSCLC). However, notable differences in immunotherapeutic outcomes exist between the two primary NSCLC subtypes: lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). This disparity may stem from the tumor immune microenvironment's heterogeneity at the transcriptome level. METHODS: By integrative analysis of transcriptomic characterization of 38 NSCLC patients by single-cell RNA sequencing, the present study revealed a distinct tumor microenvironment (TME) between LUAD and LUSC, with relevant results further confirmed in bulk transcriptomic and multiplex immunofluorescence (mIF) validation cohort of neoadjuvant immunotherapy patients. RESULTS: LUAD exhibited a more active immune microenvironment compared to LUSC. This included highly expression of HLA I/II in cancer cells, reinforced antigen presentation potential of dendritic cells and enhanced cytotoxic activity observed in T/NK cells. In LUSC, cancer cells highly expressed genes belonging to the aldo-keto reductases, glutathione S-transferases and aldehyde dehydrogenase family, negatively correlating with immunotherapy outcomes in the validation cohort of our center. Further analysis revealed elevated infiltrated cancer-associated fibroblasts (CAFs) in LUSC, which was corroborated in The Cancer Genome Atlas cohort. Corresponding increased infiltration of ADH1B+ CAFs in major pathologic response (MPR) patients and the higher presence of FAP+ CAFs in non-MPR patients were demonstrated by multiplex mIF. Moreover, upregulating immunosuppressive extracellular matrix remodeling was identified in LUSC. CONCLUSIONS: These comprehensive analyses advance the understanding of the differences in TME between LUAD and LUSC, offering insights for patient selection and developing subtype-specific treatment strategies.

Diagnostic leukapheresis reveals distinct phenotypes of NSCLC circulating tumor cells.

BACKGROUND: Circulating tumor cells (CTCs) hold immense promise for unraveling tumor heterogeneity and understanding treatment resistance. However, conventional methods, especially in cancers like non-small cell lung cancer (NSCLC), often yield low CTC numbers, hindering comprehensive analyses. This study addresses this limitation by employing diagnostic leukapheresis (DLA) to cancer patients, enabling the screening of larger blood volumes. To leverage DLA's full potential, this study introduces a novel approach for CTC enrichment from DLAs. METHODS: DLA was applied to six advanced stage NSCLC patients. For an unbiased CTC enrichment, a two-step approach based on negative depletion of hematopoietic cells was used. Single-cell (sc) whole-transcriptome sequencing was performed, and CTCs were identified based on gene signatures and inferred copy number variations. RESULTS: Remarkably, this innovative approach led to the identification of unprecedented 3,363 CTC transcriptomes. The extensive heterogeneity among CTCs was unveiled, highlighting distinct phenotypes related to the epithelial-mesenchymal transition (EMT) axis, stemness, immune responsiveness, and metabolism. Comparison with sc transcriptomes from primary NSCLC cells revealed that CTCs encapsulate the heterogeneity of their primary counterparts while maintaining unique CTC-specific phenotypes. CONCLUSIONS: In conclusion, this study pioneers a transformative method for enriching CTCs from DLA, resulting in a substantial increase in CTC numbers. This allowed the creation of the first-ever single-cell whole transcriptome in-depth characterization of the heterogeneity of over 3,300 NSCLC-CTCs. The findings not only confirm the diagnostic value of CTCs in monitoring tumor heterogeneity but also propose a CTC-specific signature that can be exploited for targeted CTC-directed therapies in the future. This comprehensive approach signifies a major leap forward, positioning CTCs as a key player in advancing our understanding of cancer dynamics and paving the way for tailored therapeutic interventions.