Lung cancer presenting as subsolid lesions has been described as less aggressive than solid lung cancers. Thus, lobectomy for subsolid lesions may be an overly extensive resection compared with sublobar techniques. The objective of the current study was to compare oncological differences between patients receiving lobectomy and sublobar resection for lung cancers presenting as subsolid lesions less than 3 cm. A retrospective review of prospectively maintained databases from the International Early Lung Cancer Action Program, Initiative for Early Lung Cancer Research on Treatment, and Weill Cornell Medicine was conducted to identify lung cancers presenting as subsolid lesions treated with surgical resection. Solid lung cancers and nodules greater than 3 cm were excluded. Computed tomography imaging was used to determine the size of nodule and percent solid component. The primary outcome of interest was lung cancer-specific survival. The secondary outcomes of interest included disease-free survival and overall survival. Median duration from surgery to outcome or last follow-up was 57.7 months (interquartile range, 30.1-111.5 months). A total of 624 patients were identified and divided into 2 groups based on extent of resection: Group A underwent lobectomy (320 patients), and group B underwent sublobar resection (304 patients). Of patients undergoing sublobar resection, 61% (185) underwent wedge resection and 39% (119) underwent segmentectomy. Nodules were further stratified by percent solid component (nonsolid, <25% solid, 25%-49% solid, >50% solid). Sixteen patients (2.56%) of the entire study population developed recurrence, and 2 patients (0.3%) had died of lung cancer. At the end of follow-up, lung cancer-specific survival was 100% in group A and 98.2% in group B (95.2-100.0) (log-rank, P = .0709). Disease-free survival in group A was 67.4% (95% CI, 57.8-77.0) and 71.1% in group B (95% CI, 59.9-82.2) (log-rank, P = .8497). Overall survival was 68.2% in group A (95% CI, 58.5-77.9) and 72.3% in group B (95% CI, 60.9-83.8) (log-rank, P = .9124). Lung cancer-specific survival and disease-free survival were not significantly different when comparing lobectomy directly with wedge resection and segmentectomy, respectively, for the entire cohort. Patients with tumors greater than 2 cm treated with sublobar resection had worse disease-free survival compared with those treated with lobectomy. Percent solid component did not significantly impact lung cancer-specific survival or disease-free survival. In this large cohort of patients with lung cancers presenting as subsolid nodules less than 3 cm, lung cancer-specific survival was excellent and similar between lobectomy and sublobar resection. Disease-free survival was worse for patients with tumors greater than 2 cm treated with sublobar resection.
To investigate whether preoperative circulating tumor (ct)DNA detection is associated with pathologic upstaging, including occult lymph node (LN) metastases, in clinical stage I non-small cell lung cancer (NSCLC). We hypothesized that preoperative ctDNA detection may identify patients at increased risk of higher-stage disease, including occult nodal involvement, who may benefit from more comprehensive staging. CtDNA Lung DETECT (NCT05254782) is a multicenter prospective cohort study in patients with clinical stage I NSCLC and preoperative ctDNA detection, using a tumor-informed ctDNA assay collected preoperatively. All patients underwent guideline-concordant staging with positron emission tomography/computed tomography (CT), CT-guided biopsy, and/or endobronchial ultrasound (EBUS). Between July 2021 and September 2024, 14 of 153 patients with preoperative clinical stage I NSCLC had occult LN metastases discovered. Of these 14 LN-positive patients, 7 had prior EBUS with LN sampling, all with negative cytologic results. The other 7 were diagnosed via CT-guided biopsy alone according to standard guidelines. Preoperative ctDNA in plasma was detected in 8 of the 14 LN-positive patients. In the larger cohort, 34 of 153 patients had ctDNA detected preoperatively, 24% of whom had occult LN metastases at time of resection. In contrast, only 5% of patients without detectable ctDNA prior to surgery had occult nodal involvement (P = .003). Preoperative ctDNA detection was associated with a higher likelihood of pathologic upstaging, including occult LN metastasis in patients with clinical stage I NSCLC. These findings support further evaluation of ctDNA as a complementary tool to refine risk stratification and guide decisions regarding invasive mediastinal staging or perioperative treatment in clinical stage 1 NSCLC.
Phallusia arabica (P. arabica) aqueous extract-mediated precipitation method was adopted in the synthesis of copper oxide nanoparticles (CuO NPs) referred to as tenorite. This green route for CuO synthesis enabled the use of P. arabica aqueous extract as a capping agent, affording biocompatibility with tunable properties. A wide peak in the ultraviolet (UV) region (288 nm) denoted the facile production of CuO NPs. CuO NPs unveiled fluorescence with peaks in both UV and visible regions, such as 388 nm and 657 nm, respectively. Fourier transform infrared spectroscopic analysis corroborated broad coverage of varied biomolecules present in the P. arabica aqueous extract, aiding the synthetic process. The crystallite size and hydrodynamic size of CuO NPs were calculated to be 29.89 nm and 133.4 nm from the x-ray diffractometer and dynamic light scattering techniques, respectively. The thermal studies confirmed the high stability of CuO NPs heated up to 800℃. The electron microscopic analysis confirmed spherical-shaped particles of size 35.5 nm with even distribution. The antimicrobial activity of P. arabica mediated CuO NPs exhibited moderate activity against the strains of Staphylococcus aureus and Candida glabrata. Further, the IC50 value was found to be 49.70 ± 1.10 µg/mL against A549 human lung cancer cells. These results suggested multiple incorporations in the biomedical field, with CuO NPs offering versatile properties that could be tailored for wider applications.
Lung cancer (LC) is the leading cause of cancer-related mortality worldwide, primarily due to diagnosis at advanced stages. Although low-dose computed tomography (LDCT) screening reduces lung cancer mortality in high-risk populations, current screening programmes are largely restricted to individuals defined by age and smoking history. This approach excludes never-smokers and individuals with non-smoking-related risk factors, limiting the equity, efficiency and scalability of lung cancer screening. The LUng Cancer risk factors and their Impact Assessment (LUCIA) project aims to overcome these limitations by developing personalised lung cancer risk prediction models and evaluating novel non-invasive technologies for early detection within a risk-adapted screening strategy. LUCIA is a multicentre, observational, longitudinal cohort study that will recruit approximately 4000 participants across four European regions: Andalusia and the Basque Country (Spain), Liège (Belgium) and Riga (Latvia). The study population includes smokers, never-smokers and reduced smokers with low-to-moderate lung cancer risk. All participants will initially enter phase 1 (wide population screening) and may transition to phase 2 (precision screening) or phase 3 (diagnosis) based on LDCT findings, results from non-invasive screening devices and artificial intelligence-based risk prediction models. Participants will be followed up for 24 months, with assessments at baseline and at 6, 12 and 24 months. Data collection includes sociodemographic characteristics, medical history, environmental and occupational exposures, lifestyle factors, spirometry, multi-omics profiles and outputs from novel non-invasive devices, including a breath analyser, spectrometry-on-card and a skin-applied volatile organic compound sensing patch. The study will develop and validate integrated lung cancer risk prediction models and evaluate the diagnostic performance of these technologies to support population stratification and personalised screening. The study will be conducted in accordance with the Declaration of Helsinki, Good Clinical Practice guidelines and applicable national and European regulations. Ethical approval has been obtained from the relevant ethics committees in all participating countries. Written informed consent will be obtained from all participants. Study findings will be disseminated through peer-reviewed open-access publications, scientific conferences and communication with public health stakeholders. ClinicalTrials.gov, NCT06473870.
Relapsed small cell lung cancer (SCLC) is widely considered as a difficult-to-treat disease with an adverse prognosis and scarce therapeutic options, especially in the case of platinum-resistance. Tarlatamab (IMDELLTRA™), a first-in-class, Delta-like ligand-3 (DLL3)-targeted bispecific T-cell engager (BiTE), works by creating a molecular bridge between DLL3 on tumor cells and CD3 on T-cells, leading to T-cell activation and Τ-cell-mediated tumor cell lysis. Tarlatamab demonstrated promising efficacy in early-phase trials at the cost of immune-mediated toxicities like cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). CRS and ICANS emerge primarily during the first two cycles of treatment, have low to moderate severity and are generally manageable with general supportive measures and specialized immunosuppressive treatment including corticosteroids and monoclonal antibodies like tocilizumab. Tarlatamab appears to be a promising choice for relapsed SCLC, based on the results of the Phase III DeLLphi-304 trial, which demonstrated a clinically and statistically meaningful improvement in overall survival (OS) with its use compared to approved second-line chemotherapy (ChT) options. Having been recently granted FDA approval for use in patients with SCLC who progressed on or after platinum-based ChT, tarlatamab is currently being evaluated in multiple settings of SCLC, including first-line and maintenance treatment. Small cell lung cancer is a very aggressive type of lung cancer. The management of patients whose cancer comes back after the initial treatment is considered as a difficult-to-solve riddle with no significant breakthrough for many years and a few therapeutic options based on chemotherapy. Tarlatamab (IMDELLTRA™) is a new, targeted drug that establishes a connection between the cancer cells and a subgroup of the patient’s immune cells, enabling the latter to localize and destroy the tumor. This drug has been shown to be more effective than standard chemotherapy for patients whose cancer has come back after platinum-based treatment. Specifically, a major study (DeLLphi-304) found that tarlatamab helped patients live longer and kept the disease under control for a longer period compared to chemotherapy. While tarlatamab can cause side effects related to the immune system or to the nervous system due to its mechanism of action, these are usually mild and happen early in the treatment. Based on this study, tarlatamab has recently been approved by the FDA for the treatment of relapsed small cell lung cancer and is under ongoing assessment for other indications like newly diagnosed small cell lung cancer.
Non-small cell lung cancer (NSCLC) is increasingly diagnosed at early stages, yet intraoperative localization of small and subsolid lesions remains challenging. Intraoperative molecular imaging (IMI) using tumor-targeted tracers is effective in many cancers; however, no available optical agents are specific for precursor or early-stage NSCLC. Sodium-glucose cotransporter 2 (SGLT2) is upregulated in in situ and minimally invasive lung cancers. This study aimed to develop and validate GlucoGlo, a novel SGLT2-targeted near-infrared (NIR) contrast agent, for IMI in early-stage NSCLC. GlucoGlo, an SGLT2-targeted fluorescent tracer, was developed and assessed for specificity and efficacy in targeting and detecting NSCLC. Its SGLT2-specific binding was assessed by fluorescence imaging in in vitro and in vivo murine NSCLC models. Mice pretreated with an SGLT2 inhibitor were used to confirm on target binding. GlucoGlo's performance in detecting residual tumor after resection was compared to conventional visualization and palpation. GlucoGlo selectively bound SGLT2-expressing NSCLC cell lines in vitro with minimal fluorescent signal seen in negative controls. In vivo, it accumulated in flank xenografts at clinically relevant doses (peak signal to background ratio (SBR) of 6.85 at 48 h) without toxicity. Fluorescent signal was eliminated with pretreatment with a non-fluorescent SGLT2 inhibitor, confirming target specificity. Histopathologic analysis further confirmed the selective tumor accumulation. In a murine partial-resection model, GlucoGlo exhibited significantly greater sensitivity for detecting residual tumor compared to conventional visualization and palpation in resection models (100% vs. 62.5%; p < 0.01). In ex-vivo human lung tissue, GlucoGlo accurately identified pulmonary malignancy and had significantly greater mean fluorescence in tumor areas compared to normal lung (25,218 vs. 3,371 a.u., respectively, SBR: 7.57; p = 0.009). GlucoGlo demonstrated high sensitivity and specificity for SGLT2 in preclinical models of NSCLC, supporting its potential for clinical translation in intraoperative detection of ground glass opacities and early-stage lung cancer.
Chimeric antigen receptor (CAR) T-cell treatment has developed among major substantial improvements for modern cancer treatment, providing sustained responses in patients with otherwise resistant blood cancers. This method comprises of patients reprogramming or donor's T lymphocytes to interpret tumor associated antigens self-sufficiently of major histocompatibility multifaceted presentation, thereby circumventing a key limitation of natural immune surveillance. The approval of CD19- and BCMA-targeted therapies demonstrated remarkable clinical impact and validated the approach. Over successive generations, CAR constructs have been refined with additional costimulatory elements, cytokine support, and multifunctional signaling domains, improving both their persistence and therapeutic activity. Despite such progress, important challenges remain, including risks of relapse, toxicity including neurotoxicity and cytokine release syndrome with limited efficacy in solid tumors. Current research is focused on strategies, such as armored CARs, gene editing, and combination therapies to expand clinical benefit. A comprehensive literature search was conducted using PubMed, Scopus, and Web of Science databases, covering publications from 2000 to 2026 till date. Relevant peer-reviewed articles were selected based on their relevance to CAR T-cell therapy, including preclinical and clinical studies. Detailed search strategy, inclusion criteria, and screening methods are described in the main manuscript. This review explores the evolution, applications, and future outlook of CAR T-cell rehabilitation. CAR T-cell therapy in cancer: training the body’s immune system to fight cancer more effectivelyCancer is a major cause of illness and death worldwide. Traditional treatments such as chemotherapy, radiation, and surgery can be effective, but they often have serious side effects and may not work for all patients. This has led to the development of newer treatments that help the body’s own immune system fight cancer. CAR T-cell therapy is one such advanced treatment. It works by collecting a patient’s immune cells (called T-cells) and modifying them in a laboratory so they can better recognize and attack cancer cells. These modified cells are then multiplied and returned to the patient’s body, where they seek out and destroy cancer cells. This therapy has shown very promising results, especially in certain types of blood cancers that are difficult to treat with standard therapies. Some patients have experienced long-lasting responses. However, there are still challenges. These include side effects caused by an overactive immune response, the risk of cancer returning, and limited success in treating solid tumors such as lung or breast cancer. Researchers are working to improve this therapy by making it safer, more effective, and suitable for more types of cancer. New approaches include combining CAR T-cell therapy with other treatments and using advanced technologies like gene editing. Overall, CAR T-cell therapy is a rapidly developing and promising approach that could improve outcomes for many cancer patients in the future.
Lung cancer, especially non-small cell lung cancer (NSCLC), remains a leading cause of cancer-related morbidity and mortality worldwide, largely due to challenges in early diagnosis, pronounced tumor heterogeneity, and frequent therapeutic resistance. N6-methyladenosine (m6A), the most prevalent RNA epigenetic modification, participates in tumorigenesis and progression by regulating various aspects of RNA metabolism. Circular RNAs (circRNAs), characterized by their covalently closed loop structure and high stability, have emerged as important regulators of tumor proliferation, metastasis, and drug resistance. Increasing evidence indicates that m6A modification influences circRNA biogenesis, stability, and translational potential, while circRNAs can reciprocally modulate the m6A machinery or act as molecular scaffolds within m6A regulatory networks. In this mini-review, we summarize recent advances regarding m6A-modified circRNAs in lung cancer, with particular emphasis on their roles in tumor growth and metastasis, ferroptosis, cancer stem cell maintenance, resistance to radiotherapy, chemotherapy, and targeted therapy, metabolic reprogramming, and the tumor immune microenvironment. Additionally, we discuss the diagnostic and therapeutic potential of m6A-circRNA interactions. Finally, we highlight the need for future studies to elucidate the dynamic regulation and clinical translation of the m6A-circRNA axis, aiming to provide novel strategies for precision therapy in lung cancer.
Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy but can cause serious immune-related adverse events (irAEs), with pneumonitis (ICI-P) being among the most severe. Early identification of high-risk patients before ICI initiation is critical to close monitoring, enable timely intervention, and optimize outcomes. To develop and validate a deep learning foundation model to predict ICI-P from baseline CT scans in patients with lung cancer. We designed the Checkpoint-Inhibitor Pneumonitis Hazard EstimatoR (CIPHER), a deep learning-powered foundation model combining contrastive learning with a transformer-based masked autoencoder to predict ICI-P from baseline CT scans in lung cancer patients. Using self-supervised learning, CIPHER was pre-trained on 590,284 CT slices from 2,500 non-small cell lung cancer (NSCLC) patients, to understand heterogeneous lung parenchyma. Following pre-training, the model was fine-tuned on an internal NSCLC cohort for ICI-P risk prediction, with images from 254 patients used for model development and from 93 patients for internal validation. We compared CIPHER with classical radiomic models. We also validated CIPHER on an external NSCLC cohort of 116 patients. In our internal immunotherapy cohort, CIPHER consistently distinguished patients at elevated risk of ICI-P from those without the event, with AUCs ranging from 0.77 to 0.85. In head-to-head benchmarking, CIPHER achieved an AUC of 0.83, outperforming radiomic model. In the external validation cohort, CIPHER maintained high performance (AUC=0.83; balanced accuracy=81.7%), exceeding the radiomic models (Delong p=0.0318) and demonstrating superior specificity without sacrificing sensitivity. By contrast, radiomic model, despite high sensitivity (85.0%), showed markedly lower specificity (45.8%). Confusion matrix analyses confirmed CIPHER's robust classification, correctly identifying 80 of 96 non-ICI-P cases and 16 of 20 ICI-P cases. We developed and externally validated CIPHER for predicting future risk of developing ICI-P from pre-treatment CT scans. With prospective validation, CIPHER can be incorporated into routine patient management to improve outcomes. The first chest CT AI foundation model for immune toxicity - We introduce CIPHER (Checkpoint-Inhibitor Pneumonitis Hazard EstimatoR), a transformer-based masked autoencoder trained through self-supervised contrastive learning on 590,284 CT slices from 4,242 NSCLC patients' scans. This large-scale pretraining enables CIPHER to learn intrinsic lung parenchymal representations linked to immune toxicity risk. Early risk prediction prior to therapy initiation - CIPHER predicts the likelihood of ICI-induced pneumonitis directly from baseline CT scans, offering the first non-invasive foundation model for early risk assessment before ICI. Robust validation and benchmarking - We fine-tuned and evaluated CIPHER across independent internal and external NSCLC immunotherapy cohorts, achieving AUCs of 0.77- 0.85 internal cross validation and 0.83 external testing, surpassing conventional radiomic models in both performance and generalizability. Interpretability and clinical readiness - We demonstrate how model-derived attention maps align with clinically relevant pulmonary patterns, enhancing interpretability and enabling seamless integration into radiology workflows. Translational potential - CIPHER's performance and scalability underscore its potential as decision-support tool to guide treatment planning, pre-emptive monitoring, and toxicity mitigation in immunotherapy practice.
Patients with active lung or lower head and neck cancer (HNC) are at increased risk of infection, particularly hospital-acquired pneumonia (HAP), ventilated HAP (vHAP) and ventilator-associated pneumonia (VAP), due to immunosuppression and treatment-related side effects. These infections are associated with increased mortality, prolonged hospital stays and interruptions in cancer therapy. Despite their clinical relevance, data on epidemiology, risk factors, treatment, and outcomes in this population remain limited. We conducted a retrospective, observational, multicentre matched cohort study at eight tertiary care centres in Germany and Spain. Patients with lung or lower HNC who received anti-cancer treatment between January 2018 and May 2022 and were hospitalised for at least 48 h were included. Patients with HAP/vHAP/VAP (case group) were matched 1:1 to those without pneumonia (control group) and followed for 90 days. A total of 256 patients were included, with median ages of 65 (cases) and 64 years (controls). Most patients had lung cancer (94%, n = 240), predominantly in stages III-IV (81%, n = 207). In the case group, patients had mostly HAP (88%, n = 113), diagnosed in median 7 days after hospital admission. Common antibiotics given included penicillin derivatives with β-lactamase inhibitors, cephalosporins and carbapenems. Patients with HAP/vHAP/VAP had significantly higher mortality and longer hospital stays (p < 0.001). Cox regression identified HAP/vHAP/VAP and dysphagia as independent predictors of mortality. HAP/vHAP/VAP imposes a significant clinical burden in patients with lung or lower HNC. Early prevention, timely diagnosis, and close monitoring of high-risk patients are essential to improve outcomes.
This narrative review summarizes the current concept, CT imaging features, pathologic basis, and the correlation between imaging and pathology in lung cancer associated with cystic airspaces (LCCAs). Lung cancer associated with cystic airspaces is a distinct subtype of lung cancer with unique imaging and pathological features. Lung cancer screening can identify patients with cystic lesions on imaging, but distinguishing benign from malignant lesions remains challenging. The pathologic types of LCCAs vary, and early diagnosis and accurate identification are of great clinical value for patient management and improved prognosis. Clinicians should pay more attention to LCCAs to promote early diagnosis, improve the timing of interventions, and achieve better survival benefits for patients.
The cross-sectional area (CSA) of the iliopsoas muscle on computed tomography is associated with sarcopenia, but its perioperative changes and prognostic significance in lung cancer remain unclear. This study aimed to clarify postoperative changes in the iliopsoas CSA and their prognostic correlation in the perioperative period of lung cancer. We analyzed 270 patients with lung cancer age ≥70 years who underwent lobectomy between January 2016 and December 2020. Iliopsoas CSA at the L3 vertebral level was measured preoperatively and at 6 and 12 months postoperatively and analyzed with ImageJ software. Patients were grouped based on whether their CSA decreased or increased between 6 months and 12 months postoperatively. Recurrence-free survival (RFS) and overall survival (OS) were compared between groups. Compared with preoperatively, the iliopsoas CSA was decreased significantly at 6 months (23.2 mm2; P < .01) and 12 months (15.5 mm2; P = .03). Patients in the decreasing CSA were older (P = .02), more often male (P = .02), and had poorer lung function (P = .04). Decreased CSA was linked to poorer 5-year RFS (P = .07) and significantly worse OS (P = .04). The multivariate analysis revealed that a decrease in iliopsoas muscle CSA between 6 months and 12 months postoperatively was an independent poor prognostic factor for RFS (P < .01) and OS (P = .05). In elderly patients with primary lung cancer, decreased iliopsoas CSA from 6 months to 12 months postoperatively was at least an independent poor prognostic factor for OS.
Accurate mediastinal staging is critical for the effective treatment of non-small cell lung cancer because lymph node involvement significantly influences prognosis and therapeutic decisions. We sought to evaluate the diagnostic accuracy, limitations, and complementary roles of endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA), cervical mediastinoscopy, and surgical lymph node sampling in mediastinal staging of non-small cell lung cancer. A systematized literature review was performed using PubMed and national guideline repositories. Studies were included if they reported or provided sufficient data to calculate the negative predictive value (NPV) for EBUS-TBNA, mediastinoscopy, or surgical lymph node sampling. Data were synthesized qualitatively across different clinical scenarios. The pooled (unweighted) NPV of EBUS-TBNA was 93.2% (range, 84.7%-98%). Mediastinoscopy demonstrated a pooled NPV of 93.8% (range, 78.8%-97%), with most false negatives attributable to inaccessible stations. Surgical lymph node sampling yielded a pooled NPV of 92.2% (range, 83.6%-96%) for resected nodal stations, although assessment is limited by variability across studies with inconsistent surgical approaches. These data support the need for systematic intraoperative nodal evaluation to confirm pathologic stage and inform treatment selection. Although EBUS-TBNA is the preferred initial staging modality due to its minimally invasive nature, its diagnostic limitations warrant a low threshold for additional nodal evaluation. Systematic intraoperative lymph node evaluation at the time of surgical resection is indispensable for definitive staging, providing clinically actionable data that influences treatment decisions. Optimal staging of non-small cell lung cancer requires a multidisciplinary, individualized approach that combines modalities based on pretest probability, imaging findings, and patient factors.
Systemic inflammation and metabolic alterations frequently coexist in lung cancer, yet their interrelationship remains incompletely understood. Serum urea is routinely measured in clinical practice but is rarely examined in relation to immune-inflammatory indices. We conducted a retrospective cross-sectional analysis of lung cancer patients with available serum urea and complete blood count data. Associations between serum urea and inflammatory immune indices, including the neutrophil-to-lymphocyte ratio (NLR), were evaluated using non-parametric correlation analyses. Multivariable regression and exploratory mediation analyses were performed to assess the contribution of lymphocyte count to observed associations. Eighty-three patients were included in the final analysis. Serum urea was positively associated with NLR and inversely associated with absolute lymphocyte count. Serum creatinine did not demonstrate a comparable association with NLR. Exploratory mediation analysis suggested that lymphocyte count partially mediated the association between serum urea and NLR. Sensitivity analyses excluding explicitly treated patients and additional adjustment for hepatic biochemical markers did not materially alter the findings. In patients with lung cancer, higher serum urea levels are associated with systemic immune dysregulation, reflected by elevated NLR and lower lymphocyte counts. These findings suggest that serum urea may serve as an integrative marker of metabolic-immune coupling beyond its conventional interpretation as a marker of renal function. Further longitudinal studies are warranted to clarify the clinical implications of this association.
HER2-mutant lung cancer represents approximately 2-5% of all NSCLCs and is associated with poor prognosis. Two different HER2-targeted therapeutic approaches with different mechanisms of action -antibody-drug conjugates (ADCs) and HER2-selective tyrosine-kinase inhibitors (TKIs)- have shown convincing efficacy in pretreated patients. Trastuzumab deruxtecan (T-DXd) was the first targeted therapy approved for patients with HER2-mutant NSCLC, demonstrating robust and durable responses in about 50% of these patients. Toxicity, while overall manageable, includes an increased risk of interstitial lung disease (ILD), which can be problematic and requires close clinical monitoring. More novel HER2-directed ADCs have confirmed the solid efficacy in this tumor type, showing variable rates of ILD as a class effect of these agents. On the other hand, novel orally available TKIs with higher specificity and inhibitory potency against HER2 over wild type EGFR such as sevabertinib (a dual HER2/EGFR mutant-selective reversible TKI) or zongertinib (an irreversible HER2-selective TKI that spares EGFR, including mutant EGFR) have further demonstrated deep and durable responses in this disease. Toxicities with these agents are mostly related to EGFR wild type inhibition, with significantly lower rates of ILD. Consistent with its selectivity and mechanism of action, zongertinib offers a favorable tolerability profile, with mainly low-grade adverse events including those related to wild type EGFR inhibition. In this review, we first describe the molecular landscape and clinical features of HER2-mutant NSCLC. Then, we summarize the clinical and preclinical evidence of HER2-targeted therapies and provide a forward-looking perspective of the treatment landscape of HER2-mutant NSCLC.
Aberrant anabolic activity is critical to tumor biology; however, much remains to be learned about the regulators of protein anabolism in cancer and how this regulation may affect cancer pathophysiology. MicroRNA (miRNA), a family of small nucleotide regulatory molecules, may serve as a potential source of proteostatic regulation. Here, we examined the ability of two co-transcribed miRNA species, miR15a and miR16 (jointly described as miR15a/16) to regulate protein handling and pathophysiology in non-small cell lung cancer (NSCLC). We found that miR15a/16 regulates genes in numerous metabolic and pathological pathways, including those related to protein metabolism. Transfection of cellular models of NSCLC with miR15a/16 mimetics caused reductions in both cell growth and protein synthesis rates. These findings indicate that miR15a/16 acts as regulators of protein anabolism in NSCLC, serving as novel metabolic regulators and potential clinical therapeutic targets for malignant lung cancer.
Thoracic Surgery Oncology Group 103 was a prospective multi-institutional trial that aimed to (1) evaluate the role of perioperative chemotherapy for low-risk patients with metastatic colorectal cancer undergoing pulmonary metastasectomy and (2) characterize the impact of surgery on outcomes for high-risk patients with metastatic colorectal cancer receiving chemotherapy. From July 2018 to September 2023, patients with histologically confirmed primary colorectal cancer and lung metastases amenable to complete margin-negative resection from 3 institutions were enrolled and stratified by low- and high-risk clinical features and randomized accordingly within 2 treatment paradigms. A total of 22 and 26 patients were enrolled in the low- and high-risk cohorts, respectively. Randomization within the low-risk cohort resulted in 8 individuals (40.0%) receiving perioperative chemotherapy and surgery (+Chemo) and 12 patients (60.0%) undergoing surgery alone (-Chemo). Median overall survival was unable to be calculated for either group, and median recurrence-free survival was 21.8 months for +Chemo and not yet reached for -Chemo (P = .33). Among high-risk patients receiving chemotherapy, 8 (36.4%) remained on chemotherapy only (-SX) and 14 (63.6%) underwent pulmonary metastasectomy (+SX). Partial response to initial chemotherapy was achieved in 4 (50.0%) -SX patients and 6 (42.9%, P = 1.00) +SX patients. No deaths occurred in either group, and median recurrence-free survival was 33.4 months in the -SX group and 55.8 (P = .95) months in the +SX group. Patient accrual targets were not reached, leaving this study underpowered; as such, all analyses are descriptive and hypothesis generating. We were unable to determine differences in survival in the high-risk cohort; however, our findings suggest that adequately selected low-risk individuals can be treated with up-front pulmonary metastasectomy without additional lung-directed chemotherapy.
The recent approval of KRAS inhibitors supports the therapeutic value of targeting mutant KRAS cancers. However, clinical efficacy is hindered by both primary and treatment-associated acquired resistance. We applied a CRISPR-Cas9 loss-of-function screen and identified loss of KEAP1 as a resistance mechanism to the KRAS G12D -selective inhibitor MRTX1133 and the RAS(ON) multi-selective inhibitor RMC-7977 in pancreatic cancer models. RNA-sequencing analyses revealed a KEAP1 KO transcriptome that is distinct from the ERK-, MYC-, and YAP/TAZ-TEAD-dependent transcriptional programs that drive KRAS inhibitor resistance, demonstrating a distinct mechanism of resistance. We then established a PDAC KEAP1-deficient (PKD) gene signature that was enriched in patients and preclinical models insensitive to KRAS inhibitor treatment. Finally, we observed that KEAP1-deficient cells exhibited elevated glutamine metabolism, and combination treatment with the glutamine antagonist DRP-104 (sirpiglenastat) enhanced KRAS inhibitor suppression of pancreatic and lung tumors. KEAP1 loss is associated with reduced response to KRAS inhibitor therapy. We demonstrate that KEAP1 loss-associated resistance can be overcome by pharmacologic inhibition of the KEAP1 loss-induced glutamine dependency, establishing a combination to enhance RAS inhibitor clinical efficacy.
To investigate the prognosis of peripheral early-stage lung adenocarcinoma patterns treated by lobectomy or segmentectomy. Retrospective multicentric cohort of patients with cT1a-bN0M0 lung adenocarcinoma who underwent lobectomy or segmentectomy with systematic lymph node dissection in 10 European centers (one per country) from 2015 to 2021. Overall survival (OS), disease-free survival (DFS), and lung cancer-specific death (LCSD) between both groups were assessed in entire dataset and in dataset of histologic aggressive patterns, before and after propensity score-matching (PSM). Prognostic risk factors were analyzed using parsimonious model Cox regression. Recurrences were assessed by linearized risks. Lobectomy and segmentectomy were performed in 1029 (73.1%) and 377 (26.8%) patients, respectively. In total, 427 (30.3%) patients had at least 1 histologic aggressive (micropapillary or solid) pattern, and 88 patients (20.7%) underwent segmentectomy. OS, DFS, and LCSD rates were similar between patients who underwent lobectomy or segmentectomy, in both datasets, before and after PSM. In aggressive dataset, PSM, 5-year OS rates were lobectomy 88.0% (95% CI, 80.9-95.7%), segmentectomy 89.1% (95% CI, 82.2-96.6%), P = .8; 5-year DFS rates were lobectomy 79.8% (95% CI, 70.8-89.8%), segmentectomy 80.6% (95% CI, 71.6-90.6%), P = .6; and 5-year LCSD rates were lobectomy 6.0%, segmentectomy 7.8%, P = .8. Locoregional recurrence was not superior in patients who underwent segmentectomy in entire dataset (linearized risks: lobectomy 0.078, segmentectomy 0.073) and in aggressive dataset (linearized risks: lobectomy 0.036, segmentectomy 0.011) only in the unmatched cohorts. Aggressive histologic patterns impacted on only LCSD, and only when they were dominant. Segmentectomy seems comparable to lobectomy for patients with peripheral cT1a-bN0M0 lung adenocarcinoma even in case of histologic aggressive patterns.
Background Early cancer diagnosis improves survival and quality of life, yet disparities in stage at diagnosis persist. This study evaluates demographic, clinical, insurance, and neighborhood-level socioeconomic factors associated with late-stage cancer diagnosis within an academic health system. Methods We conducted a retrospective cohort study of 27,064 adults diagnosed with breast, colorectal, or lung and bronchus cancer between 2015 and 2025 in the University of California Health System. Late-stage disease was defined as AJCC stage III/IV. Multivariable logistic regression examined associations between late-stage diagnosis and patient characteristics, insurance status, comorbidity burden, and neighborhood socioeconomic measures, including the Area Deprivation Index (ADI), Social Vulnerability Index (SVI), and Healthy Places Index (HPI). Results 17.6% of patients were diagnosed at a late stage. Cancer type was the strongest predictor, with lung (aOR ≈ 13-14) and colorectal cancer (aOR ≈ 8) associated with higher odds of late-stage diagnosis compared with breast cancer. Residence in medium and high ADI tertiles and Medicaid insurance (OR = 1.16; 95% CI: 1.06-1.28) were associated with higher odds of late-stage diagnosis, while Veterans Affairs coverage was associated with lower odds (OR = 0.76; 95% CI: 0.58-1.01). SVI was not associated with stage at diagnosis, whereas higher HPI scores were modestly protective. Conclusion Late-stage cancer diagnosis is driven primarily by cancer type and insurance status, with additional contributions from neighborhood disadvantage.