DNA polymerase delta 2 (POLD2) plays a crucial role in DNA repair and replication. POLD2 is upregulated and related to poor prognosis in several types of cancer. However, the biological and clinical importance of POLD2 in lung adenocarcinoma remains unclear.

We investigated the relationship between POLD2 expression and tumor malignancy in lung adenocarcinoma cell lines. Immunohistochemistry (IHC) was performed on 373 patients with completely resected lung adenocarcinoma, and the association between POLD2 expression, clinicopathological features, and prognosis was examined.

POLD2 knockdown decreases cell proliferation and migration, resulting in apoptosis and G1 arrest in the cell cycle in lung adenocarcinoma cells. Additionally, POLD2 knockdown attenuates MYC expression, which may decrease the expression of cyclin-dependent kinases 4 and 6, pRb, Rb, and E2F1. Furthermore, among 373 patients with completely resected lung adenocarcinoma, smoking history, advanced pathological stage, and vascular invasion were significantly more prevalent in patients with high POLD2 expression (n = 146, 39.3%) than in those with low POLD2 expression (n = 227, 60.7%). Patients with high POLD2 expression also had a significantly worse recurrence-free survival (RFS) and overall survival. In the multivariable analysis, high POLD2 expression was an independent poor prognostic factor of RFS.

We provide the possibility of POLD2 as a potential new therapeutic target because high POLD2 expression is associated with high malignancy and poor prognosis in specimens from patients with lung adenocarcinoma and POLD2 depletion triggers the suppression of cell migration, cell cycle progression, and cell proliferation.

The E3 ubiquitin ligase RING finger protein 6 (RNF6) has been widely recognized for its role in promoting tumorigenesis in multiple cancers. However, we found that it is downregulated in lung adenocarcinoma (LUAD), and the molecular rationale for this discrepancy remains unclear. In the present study, we find that RNF6, but not its ΔRING inactive form, inhibits LUAD cell proliferation and migration and sensitizes LUAD to chemotherapy. To understand the molecular mechanism, we utilize affinity purification/tandem mass spectrometry (MS-MS) to analyze RNF6-interacting proteins and find that cyclin D2 (CCND2), a key regulator of the G1-S transition in the cell cycle. RNF6 physically binds to CCND2 and mediates its K48-linked polyubiquitination and subsequent degradation. However, ΔRING RNF6 fails to mediate CCND2 for ubiquitination and degradation. Moreover, Thr280 is critically important for CCND2 stability. When Thr280 is mutated, CCND2 becomes more stable and less ubiquitinated by RNF6. Furthermore, RNF6 arrests LUAD cell cycle at the G1 phase by inhibiting the CCND2/phospho-Rb signaling pathway, which is consistent with decreased cell proliferation. Lastly, RNF6 curtails the growth of LUAD xenografts in vivo, associated with decreased CCND2 expression. Therefore, RNF6 is a novel E3 ligase of CCND2 and suppresses LUAD cell proliferation. Implications: This study reveals a novel regulation on cell-cycle transition in LUAD and suggests the RNF6/CCND2 axis may represent an alternative therapeutic target for the treatment of LUAD.

BackgroundSince the publication of the original work in 2014, significant progress has been made in the characterization of genomic alterations that drive oncogenic addiction of nonsmall cell lung cancer (NSCLC) and how the immune system can leverage non-oncogenic pathways to modulate therapeutic outcomes. This update evaluates and validates the recent and emerging data for prognostic and predictive biomarkers with therapeutic targets in NSCLC.Data sourcesWe performed a literature search from January 2015 to October 2023 using the keywords non-small cell lung cancer, clinical practice guidelines, gene mutations, genomic assay, immune cancer therapy, circulating tumor DNA, predictive and prognostic biomarkers, and targeted therapies.Study selection and data extractionWe identified, reviewed, and evaluated relevant clinical trials, meta-analyses, seminal articles, and published clinical practice guidelines in the English language.Data synthesisRegulatory-approved targeted therapies include those somatic gene alterations of EGFR ("classic" mutations, exon 20 insertion, and rare EGFR mutations), ALK, ROS1, BRAF V600, RET, MET, NTRK, HER2, and KRAS G12C. Data for immunotherapy and circulating tumor DNA in next-generation sequencing are considered emerging, whereas the predictive role for PIK3CA gene mutation is insufficient.ConclusionsAdvances in sequencing and other genomic technologies have led to identifying novel oncogenic drivers, novel resistance mechanisms, and co-occurring mutations that characterize NSCLC, creating further therapeutic opportunities. The benefits associated with immunotherapy in the perioperative setting hold initial promise, with their long-term results awaiting.

A subset of ALK+ non-small cell lung cancer (NSCLC) patients relapse on ALK inhibitor (ALKi) treatment due to on-target resistance mutations affecting the tyrosine kinase domain.

In this study, we investigated the presence of minor resistant clones in pre-treatment tissue samples and assessed their predictive value for subsequent resistance mechanisms.

Using the highly sensitive digital droplet (dd)PCR technique, we analyzed 40 tissue samples obtained from 17 patients who had developed on-target resistance mutations after receiving ALKi between 2013 and 2022. We focused on 10 on-target ALKi resistant mutations identified in our patient cohort.

Fifteen ALKi resistance mutations were detected in 13 samples from 11/17 patients. Among these, four mutations were observed as resistance mutations in follow-up biopsies taken after first or subsequent lines of ALKi. Comparison of the test results from two subsequent biopsies, before and directly after therapy, revealed presence of the resistance mutation identified upon relapse in the pre-treatment sample of three cases that were all taken from the same tumor location. In six cases taken from different tumor locations, the resistant mutations were not found in the pre-treatment sample.

By using the highly sensitive ddPCR approach, we detected minor clones with on-target resistant mutations in both treatment-naive and relapse biopsies from ALK-positive NSCLC patients. The predictive value of these mutations as the potential resistance-causing mechanism was limited to relapses occurring at the same tumor location as the pre-treatment sample.

Mutations in the kinase and juxtamembrane domains of the MET Receptor Tyrosine Kinase are responsible for oncogenesis in various cancers and can drive resistance to MET-directed treatments. Determining the most effective inhibitor for each mutational profile is a major challenge for MET-driven cancer treatment in precision medicine. Here, we used a deep mutational scan (DMS) of ~5764 MET kinase domain variants to profile the growth of each mutation against a panel of 11 inhibitors that are reported to target the MET kinase domain. We validate previously identified resistance mutations, pinpoint common resistance sites across type I, type II, and type I ½ inhibitors, unveil unique resistance and sensitizing mutations for each inhibitor, and verify non-cross-resistant sensitivities for type I and type II inhibitor pairs. We augment a protein language model with biophysical and chemical features to improve the predictive performance for inhibitor-treated datasets. Together, our study demonstrates a pooled experimental pipeline for identifying resistance mutations, provides a reference dictionary for mutations that are sensitized to specific therapies, and offers insights for future drug development.

Precision cancer medicine is widely established, and numerous molecularly targeted drugs for various tumor entities are approved or are in development. Personalized pharmacotherapy in oncology has so far been based primarily on tumor characteristics, for example, somatic mutations. However, the response to drug treatment also depends on pharmacological processes summarized under the term ADME (absorption, distribution, metabolism, and excretion). Variations in ADME genes have been the subject of intensive research for >5 decades, considering individual patients' genetic makeup, referred to as pharmacogenomics (PGx). The combined impact of a patient's tumor and germline genome is only partially understood and often not adequately considered in cancer therapy. This may be attributed, in part, to the lack of methods for combined analysis of both data layers. Optimized personalized cancer therapies should, therefore, aim to integrate molecular information, which derives from both the tumor and the germline genome, and taking into account existing PGx guidelines for drug therapy. Moreover, such strategies should provide the opportunity to consider genetic variants of previously unknown functional significance. Bioinformatic analysis methods and corresponding algorithms for data interpretation need to be developed to integrate PGx data in cancer therapy with a special meaning for interdisciplinary molecular tumor boards, in which cancer patients are discussed to provide evidence-based recommendations for clinical management based on individual tumor profiles. SIGNIFICANCE STATEMENT: The era of personalized oncology has seen the emergence of drugs tailored to genetic variants associated with cancer biology. However, the full potential of targeted therapy remains untapped owing to the predominant focus on acquired tumor-specific alterations. Optimized cancer care must integrate tumor and patient genomes, guided by pharmacogenomic principles. An essential prerequisite for realizing truly personalized drug treatment of cancer patients is the development of bioinformatic tools for comprehensive analysis of all data layers generated in modern precision oncology programs.

Mutations in the kinase and juxtamembrane domains of the MET Receptor Tyrosine Kinase are responsible for oncogenesis in various cancers and can drive resistance to MET-directed treatments. Determining the most effective inhibitor for each mutational profile is a major challenge for MET-driven cancer treatment in precision medicine. Here, we used a deep mutational scan (DMS) of ~5,764 MET kinase domain variants to profile the growth of each mutation against a panel of 11 inhibitors that are reported to target the MET kinase domain. We validate previously identified resistance mutations, pinpoint common resistance sites across type I, type II, and type I ½ inhibitors, unveil unique resistance and sensitizing mutations for each inhibitor, and verify non-cross-resistant sensitivities for type I and type II inhibitor pairs. We augment a protein language model with biophysical and chemical features to improve the predictive performance for inhibitor-treated datasets. Together, our study demonstrates a pooled experimental pipeline for identifying resistance mutations, provides a reference dictionary for mutations that are sensitized to specific therapies, and offers insights for future drug development.

Despite the outstanding results achieved by osimertinib for the treatment of advanced EGFR-mutated NSCLC, the development of resistance is almost inevitable. While molecular mechanism responsible for osimertinib resistance are being mostly revealed, the definition of predictive biomarkers is crucial in order to identify patients at higher risk of progression and optimize treatment strategy.

This is a prospective single-center study aimed to assess the potential role of liquid biopsy and 18F-FDG PET/CT derived metabolic parameters as noninvasive predictive biomarkers of osimertinib outcomes in advanced EGFR-mutated NSCLC patients. Patients underwent blood samples for ctDNA analysis at baseline, after 15 days and 1 month (t1) of osimertinib. 18F-FDG PET/CT was performed at baseline and after 1 month of osimertinib.

Seventy-two advanced EGFR-mutated NSCLC patients treated with osimertinib in first (n = 63) and in second-line (n = 9) were prospectively enrolled. Baseline positive shedding status was significantly associated with a shorter progression-free survival (PFS) (9.5 vs. 29.2 months, P = .031). Early metabolic response (MR) led to improved PFS (16.8 vs. 5.5 months, P = .038) and OS (35.2 vs. 15.3 months, P = .047). Early MR was significantly correlated with subsequent radiologic response (P = .010). All 18F-FDG PET/CT baseline parameters were significantly related to baseline EGFR activating mutation allele frequency. Both clearance and no detection of EGFR at t1 were significantly associated with MR (P = .001 and P = .004, respectively).

Molecular and 18F-FDG PET/CT derived metabolic parameters might represent a useful tool to predict osimertinib outcome in advanced EGFR-mutated NSCLC patients.

Radiolabeled tyrosine kinase inhibitors (TKIs) offer a promising approach for molecular imaging of EGFR-positive cancers. Despite the development of various EGFR small-molecule probes, none of the 68Ga-labeled small-molecule probes based on the chelator DOTA have shown tumor-specific uptake. To address this challenge, we selected Olmutinib, a third-generation EGFR covalent inhibitor, as a PET imaging tracer for EGFR-positive tumors. We synthesized the precursor DOTA-Olmutinib through a five-step process and subsequently radiolabeled it with 68Ga to prepare 68Ga-DOTA-Olmutinib. 68Ga-DOTA-Olmutinib displayed moderate lipophilicity (log P = 0.85) and exhibited high stability in vitro and in vivo. Western blot analysis was used to detect the level of EGFR in multiple tumor cells. In cell uptake experiments, 68Ga-DOTA-Olmutinib exhibited enhanced uptake specifically in tumor cells with a higher level of EGFR supporting it as an EGFR-specific tracer. Additionally, PET/CT imaging with 68Ga-DOTA-Olmutinib showed significant tumor uptake at 60 min with 4 % ID/g post-injection, marking a breakthrough, though the uptake is not yet ideal. Overall, our results suggest that 68Ga-labeled Olmutinib holds promise as a potential PET tracer for detecting EGFR-positive cancers.

Breast cancer is one of the most common malignancies affecting women worldwide, with a significant need for novel therapeutic agents to target specific molecular pathways involved in tumor progression. In this study, a series of rhodanine-piperazine hybrids were designed, synthesized, and evaluated for their anticancer activity, targeting key tyrosine kinases such as VEGFR, EGFR, and HER2. Biological screening against breast cancer cell lines (MCF-7, MDA-MB-231, T47D, and MDA-MB-468) revealed 3 of the 13 tested compounds as the most potent, with 5-({4-[bis(4-fluorophenyl)methyl]piperazin-1-yl}methylidene)-2-thioxo-1,3-thiazolidin-4-one (12) showing the strongest activity, particularly against the MCF-7 and MDA-MB-468 cell lines. Molecular docking studies indicated favorable binding interactions of compound 12 and its 3-phenyl-2-thioxo-1,3-thiazolidin-4-one analogue (15) with HER2, VEGFR, and EGFR, and molecular dynamics simulations further confirmed their stable binding to HER2. These findings highlight the potential of rhodanine-piperazine hybrids as promising leads for developing new anticancer agents targeting breast cancer, particularly HER2-positive subtypes. Further structural optimization could enhance their efficacy and therapeutic profile.

Oncogenes and tumor suppressors are well-known to orchestrate several signaling cascades, regulate extracellular and intracellular stimuli, and ultimately control the fate of cancer cells. Accumulating evidence has recently revealed that perturbation of these key modulators by mutations or abnormal protein expressions are closely associated with drug resistance in cancer therapy; however, the inherent drug resistance or compensatory mechanism remains to be clarified for targeted drug discovery. Thus, dual-target drug development has been widely reported to be a promising therapeutic strategy for improving drug efficiency or overcoming resistance mechanisms. In this review, we provide an overview of the therapeutic strategies of dual-target drugs, especially focusing on pharmacological small-molecule compounds in cancer, including small molecules targeting mutation resistance, compensatory mechanisms, synthetic lethality, synergistic effects, and other new emerging strategies. Together, these therapeutic strategies of dual-target drugs would shed light on discovering more novel candidate small-molecule drugs for the future cancer treatment.

Non-small cell lung cancer (NSCLC) accounts for 85 % of all lung cancers. In NSCLC, 10-20 % of Caucasian patients and 30-50 % of Asian patients have tumors with activating mutations in the Epidermal Growth Factor Receptor (EGFR). A high percentage of these patients exhibit favorable responses to treatment with tyrosine kinase inhibitors (TKI). Unfortunately, a majority of these patients develop therapeutic resistance with progression free survival lasting 9-18 months. The mechanisms that underlie the tumorigenic effects of EGFR and the ability of NSCLC to develop resistance to TKI therapies, however, are poorly understood. Here we demonstrate that CHI3L1 is produced by EGFR activation of normal epithelial cells, transformed epithelial cells with wild type EGFR and cells with cancer-associated, activating EGFR mutations. We also demonstrate that CHI3L1 auto-induces itself and feeds back to stimulate EGFR and its ligands via a STAT3-dependent mechanism(s). Highly specific antibodies against CHI3L1 (anti-CHI3L1/FRG) and TKI, individually and in combination, abrogated the effects of EGFR activation on CHI3L1 and the ability of CHI3L1 to stimulate the EGFR axis. Anti-CHI3L1 also interacted with osimertinib to reverse TKI therapeutic resistance and induce tumor cell death and inhibit pulmonary metastasis while stimulating tumor suppressor genes including KEAP1. CHI3L1 is a downstream target of EGFR that feeds back to stimulate and activate the EGFR axis. Anti-CHI3L1 is an exciting potential therapeutic for EGFR mutant NSCLC, alone and in combination with osimertinib or other TKIs.

The safety and efficacy of combination of gefitinib with chemotherapy and bevacizumab in treatment patients with epidermal growth factor receptor (EGFR) mutations are currently unknown. This study was designed to evaluate the safety and preliminary efficacy of a combination therapy consisting of gefitinib, bevacizumab, pemetrexed, and carboplatin in patients with advanced non-squamous non-small cell lung cancer (NSCLC) harboring EGFR mutations.

Eligible patients with EGFR-mutated advanced non-squamous NSCLC were recruited and received gefitinib combination with bevacizumab plus pemetrexed and carboplatin treatment. The primary endpoints were safety and progression-free survival (PFS). Secondary endpoints included objective response rate (ORR), disease control rate (DCR), duration of response (DOR), and overall survival (OS).

From June 2019 to June 2021, 20 patients were enrolled in this study. The median follow-up was 33.8 months (95% CI, 31.0-36.6). Grade ≥ 3 adverse events was 65%, including neutropenia (30%), thrombocytopenia (20%), nausea (20%), skin rash (20%), bleeding (10%), and increased ALT (10%). There was no death related to toxicity occurred. The median PFS was 28 months (95% CI, 20.4-35.6). the ORR was 95% (95% CI, 75.1-99.9%), the DCR was 100% (95% CI, 83.2-100%), and the median DOR was 26.4 months (95% CI, 18.9-33.9). The median OS has not been reached.

The results of this study demonstrate that the four-drug combination regimen, led by gefitinib, is manageable and tolerated and effective for patients with EGFR-mutated advanced non-squamous NSCLC.

Lazertinib, a novel third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), demonstrates marked efficacy in EGFR-mutant lung cancer. However, resistance commonly develops, prompting consideration of therapeutic strategies to overcome initial drug resistance mechanisms. This study aimed to elucidate the adaptive resistance to lazertinib and advocate novel combination treatments that demonstrate efficacy in preventing resistance as a first-line treatment for EGFR mutation-positive NSCLC. We found that AXL knockdown significantly inhibited lung cancer cell viability in the presence of lazertinib, indicating that AXL activation contributes to lazertinib resistance. However, long-term culture with a combination of lazertinib and AXL inhibitors led to residual cell proliferation and increased the MCL-1 expression level, which was mediated by the nuclear translocation of the transcription factor YAP. Triple therapy with an MCL-1 or YAP inhibitor in combination with lazertinib and an AXL inhibitor significantly reduced cell viability and increased the apoptosis rate. These results demonstrate that AXL and YAP/MCL-1 signals contribute to adaptive lazertinib resistance in EGFR-mutant lung cancer cells, suggesting that the initial dual inhibition of AXL and YAP/MCL-1 might be a highly effective strategy in eliminating lazertinib-resistant cells.

Tyrosine kinase inhibitor (TKI)-targeted therapy has revolutionized cancer treatment by selectively blocking specific signaling pathways crucial for tumor growth, offering improved outcomes with fewer side effects compared with conventional chemotherapy. However, despite their initial effectiveness, resistance to TKIs remains a significant challenge in clinical practice. Understanding the mechanisms underlying TKI resistance is paramount for improving patient outcomes and developing more effective treatment strategies. In this review, we explored various mechanisms contributing to TKI resistance, including on-target mechanisms and off-target mechanisms, as well as changes in the tumor histology and tumor microenvironment (intrinsic mechanisms). Additionally, we summarized current therapeutic approaches aiming at circumventing TKI resistance, including the development of next-generation TKIs and combination therapies. We also discussed emerging strategies such as the use of dual-targeted antibodies and PROteolysis Targeting Chimeras. Furthermore, we explored future directions in TKI-targeted therapy, including the methods for detecting and monitoring drug resistance during treatment, identification of novel targets, exploration of dual-acting kinase inhibitors, application of nanotechnologies in targeted therapy, and so on. Overall, this review provides a comprehensive overview of the challenges and opportunities in TKI-targeted therapy, aiming to advance our understanding of resistance mechanisms and guide the development of more effective therapeutic approaches in cancer treatment.

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

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

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

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

Proteolysis-targeting chimeras (PROTACs) selectively eliminate detrimental proteins by exploiting the ubiquitin-proteasome system (UPS), representing a promising therapeutic strategy against various diseases. Effective adaptations of degradation signal sequences and E3 ligases for PROTACs remain limited. Here, we employed three amino acids─Gly, Pro, and Lys─as the ligand to recruit the corresponding E3 ligases: CRL2ZYG11B/ZER1, GID4, and UBRs, to degrade EML4-ALK and mutant EGFR, two oncogenic drivers in NSCLC. We found that the extent of EML4-ALK and EGFR reduction can be easily fine-tuned by using different degradation signals. These amino acid-based PROTACs, termed AATacs, hindered proliferation and induced cell cycle arrest and apoptosis of NSCLC cells in vitro. Compared to other PROTACs, AATacs are small, interchangeable but with different degradation efficiency. Our study further expands the repertoire of E3 ligases and their ligands for PROTAC application, improving the versatility and utility of targeted protein degradation for therapeutic purposes.

Glutathione peroxidase 2 (GPX2) is an antioxidant enzyme with an important role in tumor progression in various cancers. However, the clinical significance of GPX2 in lung adenocarcinoma has not been clarified.

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to analyze GPX2 mRNA expression. Then, we conducted immunohistochemistry (IHC) to assess GPX2 expression in specimens acquired from 351 patients with lung adenocarcinoma who underwent surgery at Kyushu University from 2003 to 2012. We investigated the association between GPX2 expression and clinicopathological characteristics and further analyzed the prognostic relevance.

qRT-PCR revealed that GPX2 mRNA expression was notably higher in tumor cells than in normal tissues. IHC revealed that high GPX2 expression (n = 175, 49.9%) was significantly correlated with male sex, smoking, advanced pathological stage, and the presence of pleural, lymphatic, and vascular invasion. Patients with high GPX2 expression exhibited significantly shorter recurrence-free survival (RFS) and overall survival. Multivariate analysis identified high GPX2 expression as an independent prognostic factor of RFS.

GPX2 expression was significantly associated with pathological malignancy. It is conceivable that high GPX2 expression reflects tumor malignancy. Therefore, high GPX2 expression is a significant prognostic factor of poor prognosis for completely resected lung adenocarcinoma.

There is a paucity of comprehensive knowledge pertaining to the underlying mechanisms leading to gefitinib resistance in individuals diagnosed NSCLC harboring EGFR-sensitive mutations who inevitably develop resistance to gefitinib treatment within six months to one year. In our preceding investigations, we have noted a marked upregulation of IGFBP2 in the neoplastic tissues of NSCLC, predominantly in the periphery of the tissue, implying its plausible significance in NSCLC. Consequently, in the current research, we delved into the matter and ascertained the molecular mechanisms that underlie the participation of IGFBP2 in the emergence of gefitinib resistance in NSCLC cells. Firstly, the expression of IGFBP2 in the bronchoalveolar lavage fluid and lung cancer tissues of 20 NSCLC patients with gefitinib tolerance was found to be significantly higher than that of non-tolerant patients. Furthermore, in vitro and in vivo experiments demonstrated that IGFBP2 plays a significant role in the acquisition of gefitinib resistance. Mechanistically, IGFBP2 can activate STAT3 to enhance the transcriptional activity of CXCL1, thereby increasing the intracellular expression level of CXCL1, which contributes to the survival of lung cancer cells in the gefitinib environment. Additionally, we identified ITGA5 as a key player in IGFBP2-mediated gefitinib resistance, but it does not function as a membrane receptor in the process of linking IGFBP2 to intracellular signaling transduction. In conclusion, this study demonstrates the promoting role and mechanism of IGFBP2 in acquired gefitinib resistance caused by non-EGFR secondary mutations, suggesting the potential of IGFBP2 as a biomarker for gefitinib resistance and a potential intervention target.

The dynamic interplay between tyrosine kinase inhibitors (TKIs) and the tumor immune microenvironment (TME) plays a crucial role in the therapeutic trajectory of non-small cell lung cancer (NSCLC). Understanding the functional dynamics and resistance mechanisms of TKIs is essential for advancing the treatment of NSCLC.

This study assessed the effects of short-term and long-term TKI treatments on the TME in NSCLC, particularly targeting epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) mutations. We analyzed changes in immune cell composition, cytokine profiles, and key proteins involved in immune evasion, such as laminin subunit γ-2 (LAMC2). We also explored the use of aspirin as an adjunct therapy to modulate the TME and counteract TKI resistance.

Short-term TKI treatment enhanced T cell-mediated tumor clearance, reduced immunosuppressive M2 macrophage infiltration, and downregulated LAMC2 expression. Conversely, long-term TKI treatment fostered an immunosuppressive TME, contributing to drug resistance and promoting immune escape. Differential responses were observed among various oncogenic mutations, with ALK-targeted therapies eliciting a stronger antitumor immune response compared with EGFR-targeted therapies. Notably, we found that aspirin has potential in overcoming TKI resistance by modulating the TME and enhancing T cell-mediated tumor clearance.

These findings offer new insights into the dynamics of TKI-induced changes in the TME, improving our understanding of NSCLC challenges. The study underscores the critical role of the TME in TKI resistance and suggests that adjunct therapies, like aspirin, may provide new strategies to enhance TKI efficacy and overcome resistance.

This study aimed to non-invasively predict epidermal growth factor receptor (EGFR) mutation status in patients with lung adenocarcinoma using multi-phase computed tomography (CT) radiomics features.

A total of 424 patients with lung adenocarcinoma were recruited from two hospitals who underwent preoperative non-enhanced CT (NE-CT) and enhanced CT (including arterial phase CT [AP-CT], and venous phase CT [VP-CT]). Patients were divided into training (n = 297) and external validation (n = 127) cohorts according to hospital. Radiomics features were extracted from the NE-CT, AP-CT, and VP-CT images, respectively. The Wilcoxon test, correlation analysis, and simulated annealing were used for feature screening. A clinical model and eight radiomics models were established. Furthermore, a clinical-radiomics model was constructed by incorporating multi-phase CT features and clinical risk factors. Receiver operating characteristic curves were used to evaluate the predictive performance of the models.

The predictive performance of multi-phase CT radiomics model (AUC of 0.925 [95% CI, 0.879-0.971] in the validation cohort) was higher than that of NE-CT, AP-CT, VP-CT, and clinical models (AUCs of 0.860 [95% CI,0.794-0.927], 0.792 [95% CI, 0.713-0.871], 0.753 [95% CI, 0.669-0.838], and 0.706 [95% CI, 0.620-0.791] in the validation cohort, respectively) (all P < 0.05). The predictive performance of the clinical-radiomics model (AUC of 0.927 [95% CI, 0.882-0.971] in the validation cohort) was comparable to that of multi-phase CT radiomics model (P > 0.05).

Our multi-phase CT radiomics model showed good performance in identifying the EGFR mutation status in patients with lung adenocarcinoma, which may assist personalized treatment decisions.

Circular RNAs (circRNAs) play an important role in the development of acquired resistance to many anticancer drugs. We developed the Non-Small-Cell Lung Cancer (NSCLC) cell lines with acquired resistance to osimertinib, a third-generation of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs), and evaluated the different expression profiles of circRNAs in osimertinib-sensitive and -resistant NSCLC cell lines using RNA sequencing (RNA-Seq). The expression of selected differentially expressed circRNAs was verified using quantitative real-time PCR (qRT-PCR) in paired osimertinib-sensitive and -resistant NSCLC cell lines, and in plasma samples of osimertinib-sensitive and -resistant NSCLC patients. We found that circMYBL1(has_circ_0136924) was downregulated after acquired resistance to osimertinib, inhibiting circMYBL1 expression facilitated the proliferation, migration, and invasion in osimertinib-sensitive NSCLC cells. CircMYBL1 may be a novel molecular biomarker and therapeutic target for osimertinib-resistant NSCLC.

We aimed to develop and validate a deep learning-based system using pre-therapy computed tomography (CT) images to detect epidermal growth factor receptor (EGFR)-mutant status in patients with non-small cell lung cancer (NSCLC) and predict the prognosis of advanced-stage patients with EGFR mutations treated with EGFR tyrosine kinase inhibitors (TKI). This retrospective, multicenter study included 485 patients with NSCLC from four hospitals. Of them, 339 patients from three centers were included in the training dataset to develop an EfficientNetV2-L-based model (EME) for predicting EGFR-mutant status, and the remaining patients were assigned to an independent test dataset. EME semantic features were extracted to construct an EME-prognostic model to stratify the prognosis of EGFR-mutant NSCLC patients receiving EGFR-TKI. A comparison of EME and radiomics was conducted. Additionally, we included patients from The Cancer Genome Atlas lung adenocarcinoma dataset with both CT images and RNA sequencing data to explore the biological associations between EME score and EGFR-related biological processes. EME obtained an area under the curve (AUC) of 0.907 (95% CI 0.840-0.926) on the test dataset, superior to the radiomics model (P = 0.007). The EME and radiomics fusion model showed better (AUC, 0.941) but not significantly increased performance (P = 0.895) compared with EME. In prognostic stratification, the EME-prognostic model achieved the best performance (C-index, 0.711). Moreover, the EME-prognostic score showed strong associations with biological pathways related to EGFR expression and EGFR-TKI efficacy. EME demonstrated a non-invasive and biologically interpretable approach to predict EGFR status, stratify survival prognosis, and correlate biological pathways in patients with NSCLC.

With the global incidence of non-small cell lung cancer (NSCLC) on the rise, the development of innovative treatment strategies is increasingly vital. This review underscores the pivotal role of precision medicine in transforming NSCLC management, particularly through the integration of genomic and epigenomic insights to enhance treatment outcomes for patients. We focus on the identification of key gene mutations and examine the evolution and impact of targeted therapies. These therapies have shown encouraging results in improving survival rates and quality of life. Despite numerous gene mutations being identified in association with NSCLC, targeted treatments are available for only a select few. This paper offers an exhaustive analysis of the pathogenesis of NSCLC and reviews the latest advancements in targeted therapeutic approaches. It emphasizes the ongoing necessity for research and development in this domain. In addition, we discuss the current challenges faced in the clinical application of these therapies and the potential directions for future research, including the identification of novel targets and the development of new treatment modalities.

Metabolic reprogramming is a hallmark of cancer, driving the development of therapies targeting cancer metabolism. Stable isotope tracing has emerged as a widely adopted tool for monitoring cancer metabolism both in vitro and in vivo. Advances in instrumentation and the development of new tracers, metabolite databases, and data analysis tools have expanded the scope of cancer metabolism studies across these scales. In this review, we explore the latest advancements in metabolic analysis, spanning from experimental design in stable isotope-labeling metabolomics to sophisticated data analysis techniques. We highlight successful applications in cancer research, particularly focusing on ongoing clinical trials utilizing stable isotope tracing to characterize disease progression, treatment responses, and potential mechanisms of resistance to anticancer therapies. Furthermore, we outline key challenges and discuss potential strategies to address them, aiming to enhance our understanding of the biochemical basis of cancer metabolism.

Recently, the development of targeted therapy approaches such as those based on tyrosine kinase inhibitor (TKI) greatly improved the clinical outcomes of patients affected by oncogene addicted advanced non-small cell lung cancer (NSCLC). Similarly, the improvement of radiation therapy techniques has permitted to deliver high radiation doses to a limited number of metastatic target lesions (oligopersistent or oligoprogressive), with limited high-dose normal tissue exposure that leads to low severe toxicity rates. The aim of this narrative review was to provide an overview of the currently established definition of oligometastatic and oligoprogressive disease, to define first line and subsequent lines targeted therapies and the role of consolidative non-invasive local ablative treatments (LATs) in these settings. The potential benefit of local treatment (LT) such as radiotherapy (RT) or surgery might be represented by an overall reduction of switching to subsequent systemic treatments lowering the risk of further systemic dissemination. Further randomized clinical trials will clarify the role of LT and their correct timing in relation to systemic targeted therapies.

The prognosis of lung carcinoma has changed since the discovery of molecular targets and their specific drugs. Somatic Epidermal Growth Factor Receptor (EGFR) mutations have been reported in lung carcinoma, and these mutant proteins act as substrates for targeted therapies. However, in a resource-constrained country like India, panel-based next-generation sequencing cannot be made available to the population at large. Additional challenges such as adequacy of tissue in case of lung core biopsies and locating suitable tumour tissues as a result of innate intratumoral heterogeneity indicate the necessity of an AI-based end-to-end pipeline capable of automatically detecting and learning more effective lung nodule features from CT images and predicting the probability of the EGFR-mutant. This will help the oncologists and patients in resource-limited settings to achieve near-optimal care and appropriate therapy.

The EGFR gene sequencing and CT imaging data of 2277 patients with lung carcinoma were included from three cohorts in India and a White population cohort collected from TCIA. Another cohort LIDC-IDRI was used to train the AIPS-Nodule (AIPS-N) model for automatic detection and characterisation of lung nodules. We explored the value of combining the results of the AIPS-N with the clinical factors in the AIPS-Mutation (AIPS-M) model for predicting EGFR genotype, and it was evaluated by area under the curve (AUC).

AIPS-N achieved an average AP50 of 70.19% in detecting the location of nodules within the lung region of interest during validation and predicted the score of five lung nodule properties. The AIPS-M machine learning (ML) and deep learning (DL) models achieved AUCs ranging from 0.587 to 0.910.

The AIPS suggests that CT imaging combined with a fully automated lung-nodule analysis AI system can predict EGFR genotype and identify patients with an EGFR mutation in a cost-effective and non-invasive manner.

This work was supported by a grant provided by Conquer Cancer Foundation of ASCO [2021IIG-5555960128] and Pfizer Products India Pvt. Ltd.

Breast cancer (BC) continues to be a major health challenge globally, ranking as the fifth leading cause of cancer mortality among women, despite advancements in cancer detection and treatment. In this study, we identified four novel compounds from marine organisms that effectively target and inhibit the Epidermal Growth Factor Receptor (EGFR), crucial for BC cell growth and proliferation. These compounds not only induced early apoptosis through Caspase-3 activation but also showed significant inhibitory effects on EGFR mutations associated with drug resistance (T790M, L858R, and L858R/T790M), demonstrating high EGFR kinase selectivity. Cell Thermal Shift Assay (CETSA) experiments indicated that Tandyukisin stabilizes EGFR in a concentration-dependent manner. Furthermore, binding competition assays using surface plasmon resonance technology revealed that Tandyukisin and Trichoharzin bound to distinct sites on EGFR and that their combined use enhanced apoptosis in BC cells. This discovery may pave the way for developing new marine-derived EGFR inhibitors, offering a promising avenue for innovative cancer treatment strategies and addressing EGFR-mediated drug resistance.

Introduction: The use of osimertinib in the first-line (1L) setting is an effective treatment option for sensitizing EGFR-mutations (EGFRm+) and has significantly altered the standard of care practice for EGFRm+ disease in Canada. Unfortunately, acquired resistance to osimertinib is almost universal, and outcomes are disparate. Post-progression treatment patterns and the outcome of real-world Canadian EGFRm+ patients receiving 1L osimertinib were the focus of this retrospective review. Methods: The Glans-Look Lung Cancer Research database was used to identify and collect demographic, clinical, treatment, and outcome data on EGFRm+ patients who received 1L osimertinib in the Canadian province of Alberta between 2018 and 2022. Results: A total of 150 patients receiving 1L osimertinib were identified. In total, 86 developed progressive disease, with 56 (65%) continuing systemic therapy, 73% continuing osimertinib, and 27% switching to second-line (2L) systemic therapy. Patients were similar both in clinical characteristics at 1L osimertinib initiation and patterns of treatment failure at progression; those continuing 1L osimertinib post-progression had a longer time to progression (13.5 vs. 8.8 months, p = 0.05) and subsequent post-osimertinib initiation survival (34.7 vs. 22.8 months, p = 0.11). Conclusions: The continuation of osimertinib post-progression is an effective disease management strategy for select real-world EGFRm+ patients, providing continued clinical benefit, potentially due to different underlying disease pathogenesis.

Although immune checkpoint inhibitors (ICI) have extended survival in patients with non-small-cell lung cancer (NSCLC), acquired resistance (AR) to ICI frequently develops after an initial benefit. However, the mechanisms of AR to ICI in NSCLC are largely unknown.

Comprehensive tumor genomic profiling, machine learning-based assessment of tumor-infiltrating lymphocytes, multiplexed immunofluorescence, and/or HLA-I immunohistochemistry (IHC) were performed on matched pre- and post-ICI tumor biopsies from patients with NSCLC treated with ICI at the Dana-Farber Cancer Institute who developed AR to ICI. Two additional cohorts of patients with intervening chemotherapy or targeted therapies between biopsies were included as controls.

We performed comprehensive genomic profiling and immunophenotypic characterization on samples from 82 patients with NSCLC and matched pre- and post-ICI biopsies and compared findings with a control cohort of patients with non-ICI intervening therapies between biopsies (chemotherapy, N = 32; targeted therapies, N = 89; both, N = 17). Putative resistance mutations were identified in 27.8% of immunotherapy-treated cases and included acquired loss-of-function mutations in STK11, B2M, APC, MTOR, KEAP1, and JAK1/2; these acquired alterations were not observed in the control groups. Immunophenotyping of matched pre- and post-ICI samples demonstrated significant decreases in intratumoral lymphocytes, CD3e+ and CD8a+ T cells, and PD-L1-PD1 engagement, as well as increased distance between tumor cells and CD8+PD-1+ T cells. There was a significant decrease in HLA class I expression in the immunotherapy cohort at the time of AR compared with the chemotherapy (P = .005) and the targeted therapy (P = .01) cohorts.

These findings highlight the genomic and immunophenotypic heterogeneity of ICI resistance in NSCLC, which will need to be considered when developing novel therapeutic strategies aimed at overcoming resistance.

Resistance to tyrosine kinase inhibitors (TKIs) in non-small cell lung carcinoma (NSCLC) remains a significant clinical challenge. Osimertinib, a third-generation TKI, has demonstrated efficacy in overcoming resistance, but novel resistance mechanisms continue to emerge. This case report presents a unique instance of histologic transformation from NSCLC to carcinosarcoma, representing a previously unreported manifestation of osimertinib resistance. We describe the clinical course of a 63-year-old female with epidermal growth factor receptor (EGFR)-mutant NSCLC who initially responded to osimertinib but eventually developed carcinosarcoma. The transformation was associated with additional EGFR mutations and alterations in RB and TP53. Despite aggressive treatment, the patient's condition deteriorated, emphasizing the limited therapeutic options for carcinosarcoma. This case underscores the need for further research to elucidate the molecular mechanisms behind histologic transformation and explore novel therapeutic strategies to address osimertinib resistance in NSCLC. Understanding and addressing these mechanisms are crucial for improving outcomes in patients facing this challenging form of resistance.

Epidermal growth factor receptor (EGFR) mutations have been identified as promising therapeutic targets for non-small cell lung cancer. Osimertinib, a third-generation EGFR-tyrosine kinase inhibitor-targeting drug, has good anti-tumor ability and excellent intracranial effects. However, management of osimertinib resistance is a clinical challenge. The clinical benefit of osimertinib combined with the antiangiogenic drug, bevacizumab, remains to be determined.

A 40-year-old female with right lung adenocarcinoma (cT2aN3M1c, IVb) was confirmed positive for EGFR exon 19 deletion mutation (c.2235_2249del, 1.3%). After receiving 5 months of osimertinib (80 mg, qd) therapy, the patient's disease progressed and she subsequently accepted treatment with osimertinib (80 mg, qd) plus bevacizumab (15 mg/kg, q21d) and achieved notable clinical remission for 23 months until renal impairment occurred, after which bevacizumab was discontinued. The patient had 6 months of remission before progression, after which bevacizumab was added again. To date, the disease has been under control. The brain lesion showed partial response again, and the side effects of bevacizumab were tolerable. The overall survival time exceeded 4 years.

This case report describes a treatment strategy for osimertinib-resistant patients with EGFR exon 19 deletion mutations. Metronomic treatment with osimertinib plus bevacizumab was achieved for more than 4 years.