Emerging Biomarkers and the Changing Landscape of Small Cell Lung Cancer

Conventional chemotherapy: millions of cures, unresolved therapeutic index

In recent decades, millions of patients with cancer have been cured by chemotherapy alone. By 'cure', we mean that patients with cancers that would be fatal if left untreated receive a time-limited course of chemotherapy and their cancer disappears, never to return. In an era when hundreds of thousands of cancer genomes have been sequenced, a remarkable fact persists: in most patients who have been cured, we still do not fully understand the mechanisms underlying the therapeutic index by which the tumour cells are killed, but normal cells are somehow spared. In contrast, in more recent years, patients with cancer have benefited from targeted therapies that usually do not cure but whose mechanisms of therapeutic index are, at least superficially, understood. In this Perspective, we will explore the various and sometimes contradictory models that have attempted to explain why chemotherapy can cure some patients with cancer, and what gaps in our understanding of the therapeutic index of chemotherapy remain to be filled. We will summarize principles which have benefited curative conventional chemotherapy regimens in the past, principles which might be deployed in constructing combinations that include modern targeted therapies.

Personalized treatment using predictive biomarkers in solid organ malignancies: A review

In recent years, the influence of specific biomarkers in the diagnosis and prognosis of solid organ malignancies has been increasingly prominent. The relevance of the use of predictive biomarkers, which predict cancer response to specific forms of treatment provided, is playing a more significant role than ever before, as it affects diagnosis and initiation of treatment, monitoring for efficacy and side effects of treatment, and adjustment in treatment regimen in the long term. In the current review, we explored the use of predictive biomarkers in the treatment of solid organ malignancies, including common cancers such as colorectal cancer, breast cancer, lung cancer, prostate cancer, and cancers associated with high mortalities, such as pancreatic cancer, liver cancer, kidney cancer and cancers of the central nervous system. We additionally analyzed the goals and types of personalized treatment using predictive biomarkers, and the management of various types of solid organ malignancies using predictive biomarkers and their relative efficacies so far in the clinical settings.

The emerging role of Schlafen-11 (SLFN11) in predicting response to anticancer treatments: Focus on small cell lung cancer

Small cell lung cancer (SCLC) is characterized by a dismal prognosis. Many efforts have been made so far for identifying novel biomarkers for a personalized treatment for SCLC patients. Schlafen 11 (SLFN11) is a protein differently expressed in many cancers and recently emerged as a new potential biomarker. Lower expression of SLFN11 correlates with a worse prognosis in SCLC and other tumors. SLFN11 has a role in tumorigenesis, inducing replication arrest in the presence of DNA damage through the block of the replication fork. SLFN11 interacts also with chromatin accessibility, proteotoxic stress and mammalian target of rapamycin signalling pathway. The expression of SLFN11 is regulated by epigenetic mechanisms, including promoter methylation, histone deacetylation, and the histone methylation. The downregulation of SLFN11 correlates with a worse response to topoisomerase I and II inhibitors, alkylating agents, and poly ADP-ribose polymerase inhibitors in different cancer types. Some studies exploring strategies for overcoming drug resistance in tumors with low levels of SLFN11 showed promising results. One of these strategies includes the interaction with the Ataxia Telangiectasia and Rad3-related pathway, constitutively activated and leading to cell survival and tumor growth in the presence of low levels of SLFN11. Furthermore, the expression of SLFN11 is dynamic through time and different anticancer therapy and liquid biopsy seems to be an attractive tool for catching SLFN11 different expressions. Despite this, further investigations exploring SLFN11 as a predictive biomarker, its longitudinal changes, and new strategies to overcome drug resistances are needed.

Diagnostic potential of protein serum biomarkers for distinguishing small and non-small cell lung cancer in patients with suspicious lung lesions

BACKGROUND

Biomarkers play a role in identifying, managing, and predicting cancer outcomes. In lung cancer, they are used at various time points. Doubts remain regarding their accuracy for differential diagnosis and histological subtyping. A diagnostic test study was conducted. It included malignant lesions and controls with benign lesions. Before lung biopsy, all patients had the following biomarkers measured in serum (Pro-GRP,NSE,CYFRA21-1,SCC-Ag,CEA).

METHODS

The predictive capacity of serum biomarkers was evaluated to discriminate between lung cancer and benign pathology. The accuracy was also assessed for distinguishing between SCLC and NSCLC and explored their ability to perform histological subtyping.

RESULTS

93 patients were included, 60 with lung cancer, 33 with benign pathology. Pro-GRP and NSE were elevated in SCLC compared with NSCLC or nonmalignant disease. The most accurate for differentiating between malignant and benign pathology were CEA and CYFRA21-1. Pro-GRP had a poor predictive capacity for distinguishing NSCLC from SCLC. However, combined with CEA and CYFRA21-1, performance improved. For SCLC, the diagnostic capacity of Pro-GRP increased by combining with biomarkers, such as NSE/CYFRA21-1.

CONCLUSIONS

Biomarkers lacked the sensitivity and specificity for independent differential diagnosis or histological subtyping. However, the observed patterns in biomarker levels associated with specific histological subtypes suggest potential utility in a multi-biomarker approach or in conjunction with other diagnostic tools. This insight could guide future research to improve diagnostic accuracy and personalized treatment strategies in lung cancer.

Correlation between immune-related adverse events and efficacy of PD-(L)1 inhibitors in small cell lung cancer: a multi-center retrospective study

BACKGROUND

Patients receiving PD-(L)1 inhibitors frequently encounter unusual side effects known as immune-related adverse events (irAEs). However, the correlation of irAEs development with clinical response in small cell lung cancer (SCLC) is unknown.

METHOD

This retrospective study enrolled 244 stage IV SCLC patients who receiving PD-(L)1 inhibitors from 3 cancer centers. The correlation of irAEs with objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) were evaluated.

RESULTS

140 in 244 (57%) patients experienced irAEs, with 122 (87.1%) experiencing one and 18 (12.9%) experiencing two or more. Compared to patient without irAEs, those developing irAEs had higher ORR (73.6% vs. 52.9%, P < 0.001) and DCR (97.9% vs. 79.8%, P < 0.001), as well as prolonged median PFS (8.8 vs. 4.5 months, P < 0.001) and OS (23.2 vs. 21.6 months, P < 0.05). Among the different spectra of irAEs, thyroid dysfunction, rash, and pneumonitis were the most powerful indicator for improved PFS. When analyzed as a time-dependent covariate, the occurrence of irAEs was associated with significant improvement in PFS rather than in OS. Furthermore, patients experiencing multisystem irAEs displayed a longer PFS and OS compared with single-system irAEs and the irAE-free ones. IrAEs grade and steroid use did not impact the predictive value of irAEs on PFS.

CONCLUSION

The presence of irAEs predicts superior clinical benefit in SCLC. Patients who develop multi-system irAEs may have an improved survival than those developed single-system irAEs and no-irAEs. This association persists even when systemic corticosteroids were used for irAEs management.

PARP1-DOT1L transcription axis drives acquired resistance to PARP inhibitor in ovarian cancer

BACKGROUND

Poly (ADP-ribose) polymerase inhibitor (PARPi) resistance poses a significant challenge in ovarian carcinoma (OC). While the role of DOT1L in cancer and chemoresistance is acknowledged, its specific role in PARPi resistance remains unclear. This study aims to elucidate the molecular mechanism of DOT1L in PARPi resistance in OC patients.

METHODS

This study analyzed the expression of DOT1L in PARPi-resistant cell lines compared to sensitive ones and correlated it with clinical outcomes in OC patients. Comprehensive in vitro and in vivo functional experiments were conducted using cellular and mouse models. Molecular investigations, including RNA sequencing, chromatin immunoprecipitation (ChIP) and Cleavage Under Targets and Tagmentation (CUT&Tag) assays, were employed to unravel the molecular mechanisms of DOT1L-mediated PARPi resistance.

RESULTS

Our investigation revealed a robust correlation between DOT1L expression and clinical PARPi resistance in non-BRCA mutated OC cells. Upregulated DOT1L expression in PARPi-resistant tissues was associated with diminished survival in OC patients. Mechanistically, we identified that PARP1 directly binds to the DOT1L gene promoter, promoting transcription independently of its enzyme activity. PARP1 trapping induced by PARPi treatment amplified this binding, enhancing DOT1L transcription and contributing to drug resistance. Sequencing analysis revealed that DOT1L plays a crucial role in the transcriptional regulation of PLCG2 and ABCB1 via H3K79me2. This established the PARP1-DOT1L-PLCG2/ABCB1 axis as a key contributor to PARPi resistance. Furthermore, we discovered that combining a DOT1L inhibitor with PARPi demonstrated a synergistic effect in both cell line-derived xenograft mouse models (CDXs) and patient-derived organoids (PDOs).

CONCLUSIONS

Our results demonstrate that DOT1L is an independent prognostic marker for OC patients. The PARP1-DOT1L/H3K79me2-PLCG2/ABCB1 axis is identified as a pivotal contributor to PARPi resistance. Targeted inhibition of DOT1L emerges as a promising therapeutic strategy for enhancing PARPi treatment outcomes in OC patients.

Effects of KEAP1 Silencing on NRF2 and NOTCH Pathways in SCLC Cell Lines

The KEAP1/NRF2 pathway is a master regulator of several redox-sensitive genes implicated in the resistance of tumor cells against therapeutic drugs. The dysfunction of the KEAP1/NRF2 system has been correlated with neoplastic patients' outcomes and responses to conventional therapies. In lung tumors, the growth and the progression of cancer cells may also involve the intersection between the molecular NRF2/KEAP1 axis and other pathways, including NOTCH, with implications for antioxidant protection, survival of cancer cells, and drug resistance to therapies. At present, the data concerning the mechanism of aberrant NRF2/NOTCH crosstalk as well as its genetic and epigenetic basis in SCLC are incomplete. To better clarify this point and elucidate the contribution of NRF2/NOTCH crosstalk deregulation in tumorigenesis of SCLC, we investigated genetic and epigenetic dysfunctions of the KEAP1 gene in a subset of SCLC cell lines. Moreover, we assessed its impact on SCLC cells' response to conventional chemotherapies (etoposide, cisplatin, and their combination) and NOTCH inhibitor treatments using DAPT, a γ-secretase inhibitor (GSI). We demonstrated that the KEAP1/NRF2 axis is epigenetically controlled in SCLC cell lines and that silencing of KEAP1 by siRNA induced the upregulation of NRF2 with a consequent increase in SCLC cells' chemoresistance under cisplatin and etoposide treatment. Moreover, KEAP1 modulation also interfered with NOTCH1, HES1, and DLL3 transcription. Our preliminary data provide new insights about the downstream effects of KEAP1 dysfunction on NRF2 and NOTCH deregulation in this type of tumor and corroborate the hypothesis of a cooperation of these two pathways in the tumorigenesis of SCLC.

Nucleic acid-sensing-related gene signature in predicting prognosis and treatment efficiency of small cell lung cancer patients

Introduction

Nucleic acid-sensing (NAS) pathways could induce innate and adaptive immune responses. However, rare evidence exhibited how the core genes of the NAS pathways affected the immune response and prognosis of small cell lung cancer (SCLC) patients.

Methods

We conducted a comprehensive bioinformatic analysis based on the RNA profiles of 114 SCLC patients, including 79 from cBioPortal, 21 from GSE30219, and 14 from our sequencing data. The multiplex immunohistochemistry (mIHC) was used to characterize the role of NAS related genes in the tumor microenvironment (TME) of SCLC.

Results

A prognostic model (7NAS risk model) was constructed based on 7 NAS-related genes which was demonstrated as an independent prognostic index. The low-risk group was identified to have a better prognosis and an immune-activated microenvironment in both the public datasets and our dataset. Intriguingly, mIHC data showed that CD45+ immune cells, CD8+ T lymphocytes, and CD68+ macrophages were prevalently enriched in low-risk SCLC patients and positively correlated with IRF1 expression. Additionally, Patients in the low-risk group might have superior responses to chemotherapy and immunotherapy.

Conclusion

Conclusively, this study created a new risk model based on genes associated with NAS pathways which could predict the prognosis and response of treatment in patients with SCLC.

Segmentation of patients with small cell lung cancer into responders and non-responders using the optimal cross-validation technique

BACKGROUND

The timing of treating cancer patients is an essential factor in the efficacy of treatment. So, patients who will not respond to current therapy should receive a different treatment as early as possible. Machine learning models can be built to classify responders and nonresponders. Such classification models predict the probability of a patient being a responder. Most methods use a probability threshold of 0.5 to convert the probabilities into binary group membership. However, the cutoff of 0.5 is not always the optimal choice.

METHODS

In this study, we propose a novel data-driven approach to select a better cutoff value based on the optimal cross-validation technique. To illustrate our novel method, we applied it to three clinical trial datasets of small-cell lung cancer patients. We used two different datasets to build a scoring system to segment patients. Then the models were applied to segment patients into the test data.

RESULTS

We found that, in test data, the predicted responders and non-responders had significantly different long-term survival outcomes. Our proposed novel method segments patients better than the standard approach using a cutoff of 0.5. Comparing clinical outcomes of responders versus non-responders, our novel method had a p-value of 0.009 with a hazard ratio of 0.668 for grouping patients using the Cox proportion hazard model and a p-value of 0.011 using the accelerated failure time model which approved a significant difference between responders and non-responders. In contrast, the standard approach had a p-value of 0.194 with a hazard ratio of 0.823 using the Cox proportion hazard model and a p-value of 0.240 using the accelerated failure time model indicating the responders and non-responders do not differ significantly in survival.

CONCLUSION

In summary, our novel prediction method can successfully segment new patients into responders and non-responders. Clinicians can use our prediction to decide if a patient should receive a different treatment or stay with the current treatment.

Real-life clinical management patterns in extensive-stage small cell lung cancer across France: a multi-method study

BACKGROUND

We designed this study based on both a physician practice survey and real-world patient data to: (1) evaluate clinical management practices in extensive-stage small cell lung cancer (ES-SCLC) among medical centers located across France; and (2) describe first-line treatment patterns among patients with ES-SCLC following the introduction of immunotherapy into clinical practice.

METHODS

A 50-item questionnaire was completed by physicians from 45 medical centers specialized in SCLC management. Responses were collected from June 2022 to January 2023. The survey questions addressed diagnostic workup of ES-SCLC, chemoimmunotherapy in first-line and second-line settings, and use of prophylactic cranial irradiation (PCI) and radiotherapy. In parallel, using a chart review approach, we retrospectively analyzed aggregated information from 548 adults with confirmed ES-SCLC receiving first-line treatment in the same centers.

RESULTS

In ES-SCLC, treatment planning is based on chest computed tomography (CT) (as declared by 100% of surveyed centers). Mean time between diagnosis and treatment initiation was 2-7 days, as declared by 82% of centers. For detection of brain metastases, the most common imaging test was brain CT (84%). The main exclusion criteria for first-line immunotherapy in the centers were autoimmune disease (87%), corticosteroid therapy (69%), interstitial lung disease (69%), and performance status ≥ 2 (69%). Overall, 53% and 36% of centers considered that patients are chemotherapy-sensitive if they relapse within ≥ 3 months or ≥ 6 months after first-line chemoimmunotherapy, respectively. Among the 548 analyzed patients, 409 (75%) received chemoimmunotherapy as a first-line treatment, 374 (91%) of whom received carboplatin plus etoposide and 35 (9%) cisplatin plus etoposide. Overall, 340/548 patients (62%) received maintenance immunotherapy. Most patients (68%) did not receive radiotherapy or PCI.

CONCLUSIONS

There is an overall alignment of practices reflecting recent clinical guidelines among medical centers managing ES-SCLC across France, and a high prescription rate of immunotherapy in the first-line setting.

Efficacy and safety of first-line PD-L1/PD-1 inhibitors in limited-stage small cell lung cancer: a multicenter propensity score matched retrospective study

Background

The prognosis of small cell lung cancer (SCLC) patients is poor, and the standard first-line treatment for limited-stage small cell lung cancer (LS-SCLC) is still chemotherapy and thoracic radiotherapy. The primary objectives of our study were to confirm the superior efficacy of first-line immune checkpoint inhibitors (ICIs) plus etoposide and platinum (EP) for LS-SCLC and find crucial biomarkers.

Methods

We analyzed LS-SCLC patients from three medical centers, employing propensity score matching for group comparability. Survival outcomes were estimated by Kaplan-Meier and Cox regression analyses. Additionally, we conducted univariate and multivariate analyses to investigate potential predictive factors.

Results

Among 150 patients in our study, we successfully matched 41 pairs. The median overall survival (OS) was 29.5 months in the EP + ICIs group and 20.0 months in the EP group {hazard ratio (HR) =0.64 [95% confidence interval (CI): 0.41-1.02], P=0.059}. The median progression-free survival (PFS) was significantly extended in the EP + ICIs group (14.6 months), compared to the EP group (8.6 months) [HR =0.42 (95% CI: 0.28-0.63), P<0.001]. After matching, patients receiving chemo-immunotherapy had a median OS of 36.1 months, significantly surpassing those receiving chemotherapy alone (19.0 months) [HR =0.51 (95% CI: 0.28-0.93), P=0.02]. And the patients in the EP + ICIs group also had longer PFS after matching [HR =0.42 (95% CI: 0.25-0.71), P=0.001]. No significant difference in the objective response rate (ORR) and treatment-related adverse events (trAEs) between the two groups was found (ORR: EP: 81.0%, EP + ICIs: 90.0%, P=0.14; trAEs: EP: grade 1-2, 49.3%; grade 3-4, 42.5%; EP + ICIs: grade 1-2, 40.0%; grade 3-4, 49.1%, P=0.62). The multivariate analysis presented that the history of immunotherapy [EP + PD-1 inhibitors: HR =0.33 (95% CI: 0.17-0.62), P=0.001; EP + PD-L1 inhibitors: HR =0.18 (95% CI: 0.06-0.60), P=0.005] and baseline lung immune prognostic index (LIPI) [intermediate: HR =2.22 (95% CI: 1.20-4.13), P=0.01; poor: HR =2.03 (95% CI: 0.71-5.77), P=0.18] were independent prognostic factors for PFS among all LS-SCLC cases. However, no independent prognostic factor was identified for OS.

Conclusions

Our real-world data showed promising clinical efficacy and tolerable safety of first-line programmed cell death protein 1 (PD-1) inhibitors or programmed cell death ligand 1 (PD-L1) inhibitors in cases with LS-SCLC. Additionally, LIPI may serve as a valuable prognostic factor.

Expression patterns and clinical implications of PDL1 and DLL3 biomarkers in small cell lung cancer retrospectively studied: Insights for therapeutic strategies and survival prediction

Lung cancer is a leading cause of cancer-related deaths globally, includes small cell lung cancer (SCLC), characterized by its aggressive nature and advanced disease at diagnosis. However, the identification of reliable biomarkers for SCLC has proven challenging, as no consistent predictive biomarker has been established. Nonetheless, certain tumor-associated antigens, including programmed death-ligand 1 (PDL1) and Delta-Like Ligand 3 (DLL3), show promise for targeted antibody-based immunotherapy. To ensure optimal patient selection, it remains crucial to comprehend the relationship between PDL1 and DLL3 expression and clinicopathological characteristics in SCLC. In this study, we investigated the expression patterns of PDL1 and DLL3 biomarkers in endobronchial samples from 44 SCLC patients, examining their association with clinical characteristics and survival. High PDL1 expression (>1%) was observed in 14% of patients, while the majority the SCLC patients (73%) exhibited high DLL3 expression (>75%). Notably, we found a positive correlation between high PDL1 expression (>1%) and overall survival. However, we did not observe any significant differences in the biomarkers expression concerning age, sex, disease status, smoking status, or distant metastases. Further subgroup analysis revealed that a high co-expression of both PDL1 (>1%) and DLL3 (100%) antigens was associated with improved overall survival. This suggests that SCLC expressing PDL1 and DLL3 antigens may exhibit increased sensitivity to therapy, indicating their potential as therapeutic targets. Thus, our findings provide novel insights into the simultaneous evaluation of PDL1 and DLL3 biomarkers in SCLC patients. These insights have significant clinical implications for therapeutic strategies, survival prediction, and development of combination immunotherapies.

Updates on lung neuroendocrine neoplasm classification

Lung neuroendocrine neoplasms (NENs) are a heterogeneous group of pulmonary neoplasms showing different morphological patterns and clinical and biological characteristics. The World Health Organisation (WHO) classification of lung NENs has been recently updated as part of the broader attempt to uniform the classification of NENs. This much-needed update has come at a time when insights from seminal molecular characterisation studies revolutionised our understanding of the biological and pathological architecture of lung NENs, paving the way for the development of novel diagnostic techniques, prognostic factors and therapeutic approaches. In this challenging and rapidly evolving landscape, the relevance of the 2021 WHO classification has been recently questioned, particularly in terms of its morphology-orientated approach and its prognostic implications. Here, we provide a state-of-the-art review on the contemporary understanding of pulmonary NEN morphology and the potential contribution of artificial intelligence, the advances in NEN molecular profiling with their impact on the classification system and, finally, the key current and upcoming prognostic factors.

Advances in new targets for immunotherapy of small cell lung cancer

Small cell lung cancer (SCLC) is one of the highly aggressive malignancies characterized by rapid growth and early metastasis, but treatment options are limited. For SCLC, carboplatin or cisplatin in combination with etoposide chemotherapy has been considered the only standard of care, but the standard first-line treatment only results in 10-month survival. The majority of patients relapse within a few weeks to months after treatment, despite the relatively sensitive response to chemotherapy. Over the past decade, immunotherapy has made significant progress in the treatment of SCLC patients. However, there have been limited improvements in survival rates for SCLC patients with the current immune checkpoint inhibitors PD-1/PD-L1 and CTLA-4. In the face of high recurrence rates, small beneficiary populations, and low survival benefits, the exploration of new targets for key molecules and signals in SCLC and the development of drugs with novel mechanisms may provide fresh hope for immunotherapy in SCLC. Therefore, the aim of this review was to explore four new targets, DLL3, TIGIT, LAG-3, and GD2, which may play a role in the immunotherapy of SCLC to find useful clues and strategies to improve the outcome for SCLC patients.

Assessment of Lung Cancer YouTube Videos for Patient Education

The internet is essential for obtaining information about lung cancer, which is the leading contributor to global cancer deaths. YouTube is a video-streaming platform that is popular among health consumers; however, the reliability of videos is variable, and few studies have evaluated their role in lung cancer education. This study uses a systematic approach to assess the characteristics, reliability and use of best practices of lung cancer YouTube videos for patient education. Using the search term "lung cancer," the first 50 YouTube videos were identified after applying exclusion criteria and removing duplicates. Two reviewers used a video assessment tool to evaluate 10 videos with minimal discrepancies. The remaining 40 videos were evaluated by one reviewer following a design based research approach. Under half the videos were published within 3 years. Mean video length was 6 min and 12 s. Video publishers were commonly from the USA (70%); were affiliated with a health care facility/ organization (30%), non-profit (26%) or commercial organization (30%); had a physician presenter (46%); were targeted towards patients (68%); and had subtitles (96%). Seventy four percent of videos supported optimal learning by including effective audio and visual channels. Lung cancer epidemiology, risk factors, and definitions (nature of the disease and classification) were among the most common topics covered. Prognostic and diagnostic information was covered less than expected. The reliability of the videos (measured by Modified DISCERN score) varied by presenter type; however, these results should be interpreted cautiously due to the absence of gold standard tools. This study encourages those producing health education videos to continue following best practices for video learning and provides strategies for healthcare providers and patients to support patient education.

Preliminary investigation of elevated collagen and blood-clotting markers as potential noninvasive biomarkers for small cell lung cancer

BACKGROUND

Small cell lung cancer (SCLC) is highly aggressive with limited therapeutic options and a poor prognosis. Moreover, noninvasive biomarker tools for detecting disease and monitoring treatment response are lacking. To address this, we evaluated serum biomarkers of extracellular matrix proteins not previously explored in SCLC.

METHODS

We measured biomarkers in the serum of 16 patients with SCLC before and after chemotherapy as well as in the serum of 11 healthy individuals.

RESULTS

Our findings demonstrated that SCLC serum had higher levels of collagen type I degradation, collagen type III formation, and collagen type XI formation than healthy controls. In addition, we observed higher levels of type XIX and XXII collagens, fibrinogen, and von Willebrand factor A formation in SCLC serum. The formation of type I collagen did not exhibit any discernible variation. However, we observed a decrease in the degradation of type I collagen following chemotherapy.

CONCLUSION

Overall, our findings revealed elevated levels of collagen and blood-clotting markers in the serum of SCLC patients, indicating the potential of ECM proteins as noninvasive biomarkers for SCLC.

Exosome nanovesicles as potential biomarkers and immune checkpoint signaling modulators in lung cancer microenvironment: recent advances and emerging concepts

Lung cancer remains the leading cause of cancer-related deaths globally, and the survival rate remains low despite advances in diagnosis and treatment. The progression of lung cancer is a multifaceted and dynamic phenomenon that encompasses interplays among cancerous cells and their microenvironment, which incorporates immune cells. Exosomes, which are small membrane-bound vesicles, are released by numerous cell types in normal and stressful situations to allow communication between cells. Tumor-derived exosomes (TEXs) possess diverse neo-antigens and cargoes such as proteins, RNA, and DNA and have a unique molecular makeup reflecting tumor genetic complexity. TEXs contain both immunosuppressive and immunostimulatory factors and may play a role in immunomodulation by influencing innate and adaptive immune components. Moreover, they transmit signals that contribute to the progression of lung cancer by promoting metastasis, epithelial-mesenchymal transition (EMT), angiogenesis, and immunosuppression. This makes them a valuable resource for investigating the immune environment of tumors, which could pave the way for the development of non-invasive biomarkers that could aid in the prognosis, diagnosis, and immunotherapy of lung cancer. While immune checkpoint inhibitor (ICI) immunotherapy has shown promising results in treating initial-stage cancers, most patients eventually develop adaptive resistance over time. Emerging evidence demonstrates that TEXs could serve as a prognostic biomarker for immunotherapeutic response and have a significant impact on both systemic immune suppression and tumor advancement. Therefore, understanding TEXs and their role in lung cancer tumorigenesis and their response to immunotherapies is an exciting research area and needs further investigation. This review highlights the role of TEXs as key contributors to the advancement of lung cancer and their clinical significance in lung immune-oncology, including their possible use as biomarkers for monitoring disease progression and prognosis, as well as emerging shreds of evidence regarding the possibility of using exosomes as targets to improve lung cancer therapy.

Small Cell Lung Carcinoma: Current Diagnosis, Biomarkers, and Treatment Options with Future Perspectives

Small cell lung cancer (SCLC) is an aggressive malignancy characterized by rapid proliferation, early dissemination, acquired therapy resistance, and poor prognosis. Early diagnosis of SCLC is crucial since most patients present with advanced/metastatic disease, limiting the potential for curative treatment. While SCLC exhibits initial responsiveness to chemotherapy and radiotherapy, treatment resistance commonly emerges, leading to a five-year overall survival rate of up to 10%. New effective biomarkers, early detection, and advancements in therapeutic strategies are crucial for improving survival rates and reducing the impact of this devastating disease. This review aims to comprehensively summarize current knowledge on diagnostic options, well-known and emerging biomarkers, and SCLC treatment strategies and discuss future perspectives on this aggressive malignancy.

Emerging therapies targeting the delta-like ligand 3 (DLL3) in small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive neuroendocrine carcinoma with a poor prognosis. Initial responses to standard-of-care chemo-immunotherapy are, unfortunately, followed by rapid disease recurrence in most patients. Current treatment options are limited, with no therapies specifically approved as third-line or beyond. Delta-like ligand 3 (DLL3), a Notch inhibitory ligand, is an attractive therapeutic target because it is overexpressed on the surface of SCLC cells with minimal to no expression on normal cells. Several DLL3-targeted therapies are being developed for the treatment of SCLC and other neuroendocrine carcinomas, including antibody-drug conjugates (ADCs), T-cell engager (TCE) molecules, and chimeric antigen receptor (CAR) therapies. First, we discuss the clinical experience with rovalpituzumab tesirine (Rova-T), a DLL3-targeting ADC, the development of which was halted due to a lack of efficacy in phase 3 studies, with a view to understanding the lessons that can be garnered for the rapidly evolving therapeutic landscape in SCLC. We then review preclinical and clinical data for several DLL3-targeting agents that are currently in development, including the TCE molecules-tarlatamab (formerly known as AMG 757), BI 764532, and HPN328-and the CAR T-cell therapy AMG 119. We conclude with a discussion of the future challenges and opportunities for DLL3-targeting therapies, including the utility of DLL3 as a biomarker for patient selection and disease progression, and the potential of rational combinatorial approaches that can enhance efficacy.

Dithiocarbazate-copper complex loaded thermosensitive hydrogel for lung cancer therapy via tumor in situ sustained-release

The Pluronic F127 thermosensitive hydrogels containing copper complex 3 were constructed, which could delay A549 tumor xenograft growth effectively with lower systemic toxicity.