Immunotherapy in Lung Cancer: From a Minor God to the Olympus

Enhancing Cancer Chemo-Immunotherapy: Innovative Approaches for Overcoming Immunosuppression by Functional Nanomaterials

Chemotherapy is a critical modality in cancer therapy to combat malignant cell proliferation by directly attacking cancer cells and inducing immunogenic cell death, serving as a vital component of multi-modal treatment strategies for enhanced therapeutic outcomes. However, chemotherapy may inadvertently contribute to the immunosuppression of the tumor microenvironment (TME), inducing the suppression of antitumor immune responses, which can ultimately affect therapeutic efficacy. Chemo-immunotherapy, combining chemotherapy and immunotherapy in cancer treatment, has emerged as a ground-breaking approach to target and eliminate malignant tumors and revolutionize the treatment landscape, offering promising, durable responses for various malignancies. Notably, functional nanomaterials have substantially contributed to chemo-immunotherapy by co-delivering chemo-immunotherapeutic agents and modulating TME. In this review, recent advancements in chemo-immunotherapy are thus summarized to enhance treatment effectiveness, achieved by reversing the immunosuppressive TME (ITME) through the exploitation of immunotherapeutic drugs, or immunoregulatory nanomaterials. The effects of two-way immunomodulation and the causes of immunoaugmentation and suppression during chemotherapy are illustrated. The current strategies of chemo-immunotherapy to surmount the ITME and the functional materials to target and regulate the ITME are discussed and compared. The perspective on tumor immunosuppression reversal strategy is finally proposed.

Immunotherapy in Lung Cancer: Are the Promises of Long-Term Benefit Finally Met?

Over the last few years, agents targeting immune checkpoints have shown potential to improve therapeutic outcomes in patients with lung cancer in multiple clinical settings. Inhibitors of PD-1/PD-L1 have been approved for the treatment of different types of lung cancer by the FDA either alone or in combination with chemotherapy or other immune checkpoint inhibitors, such as anti-CTLA-4 agents. The introduction of these agents in clinical practice has revolutionized the therapeutic approach to lung cancer, keeping the promises of long-term benefit in selected patient populations. The therapeutic indications of immunotherapy in lung cancer are rapidly growing, and multiple combinations entered clinical practice or are under active development. Furthermore, the quest for a reliable predictive biomarker is still ongoing to overcome the limits of currently approved tests for patients' selection. In this review, we summarized the current status and progress of anti-PD-1/PD-L1 agents in lung cancer treatment.

A New Generation of Vaccines in the Age of Immunotherapy

PURPOSE OF REVIEW

Cancer vaccines are one of the most extensively studied immunotherapy type in solid tumors. Despite favorable presuppositions, so far, the use of cancer vaccines has been associated with disappointing results. However, a new generation of vaccines has been developed, promising to revolutionize the immunotherapy field.

RECENT FINDINGS

In this review, we aim to highlight the advances in cancer vaccines and the remaining hurdles to overcome. Cancer vaccination has experienced tremendous progress in the last decade, with myriad promising developments. Future efforts should focus on optimization of target identification, streamlining of most appropriate vaccination strategies, and adjuvant development, as well as predictive biomarker identification. Cautious optimism is warranted in the face of early successes seen in recent clinical trials for oncolytic vaccines. If an approach were to prove successful, it could revolutionize cancer therapy the way ICIs did in the previous decade.

Immunotherapy Resistance in Non-Small Cell Lung Cancer: A Rubik's Cube to Assemble

Non-small cell lung cancer (NSCLC) is the most common form of lung cancer and is usually not diagnosed until an advanced-stage disease is present. Chemotherapy is the recommended treatment; however, it is known that chemotherapy alone has a low cure rate, harmful side effects, and a lack of sensitivity. Therefore, alternatives to improve the patient's experience and outcomes with immunotherapy are being used as first-line treatment in patients with NSCLC. Patients may develop primary or acquired resistance against immunotherapy, and the mechanisms of resistance are not yet fully understood. Currently, several new approaches are being developed to overcome immunotherapy resistance in NSCLC. Herein, we briefly discuss pathways driving resistance to immunotherapy and new alternatives that are being developed to overcome resistance.

Preliminary Report on Computed Tomography Radiomics Features as Biomarkers to Immunotherapy Selection in Lung Adenocarcinoma Patients

PURPOSE

To assess the efficacy of radiomics features obtained by computed tomography (CT) examination as biomarkers in order to select patients with lung adenocarcinoma who would benefit from immunotherapy.

METHODS

Seventy-four patients (median age 63 years, range 42-86 years) with histologically confirmed lung cancer who underwent immunotherapy as first- or second-line therapy and who had baseline CT studies were enrolled in this approved retrospective study. As a control group, we selected 50 patients (median age 66 years, range 36-86 years) from 2005 to 2013 with histologically confirmed lung adenocarcinoma who underwent chemotherapy alone or in combination with targeted therapy. A total of 573 radiomic metrics were extracted: 14 features based on Hounsfield unit values specific for lung CT images; 66 first-order profile features based on intensity values; 43 second-order profile features based on lesion shape; 393 third-order profile features; and 57 features with higher-order profiles. Univariate and multivariate statistical analysis with pattern recognition approaches and the least absolute shrinkage and selection operator (LASSO) method were used to assess the capability of extracted radiomics features to predict overall survival (OS) and progression free survival (PFS) time.

RESULTS

A total of 38 patients (median age 61; range 41-78 years) with confirmed lung adenocarcinoma and subjected to immunotherapy satisfied inclusion criteria, and 50 patients in a control group were included in the analysis The shift in the center of mass of the lesion due to image intensity was significant both to predict OS in patients subjected to immunotherapy and to predict PFS in patients subjected to immunotherapy and in patients in the control group. With univariate analysis, low diagnostic accuracy was reached to stratify patients based on OS and PFS time. Regarding multivariate analysis, considering the robust (two morphological features, three textural features and three higher-order statistical metrics) application of the LASSO approach and all patients, a support vector machine reached the best results for stratifying patients based on OS (area under curve (AUC) of 0.89 and accuracy of 81.6%). Alternatively, considering the robust predictors (six textural features and one higher-order statistical metric) and application of the LASSO approach including all patients, a decision tree reached the best results for stratifying patients based on PFS time (AUC of 0.96 and accuracy of 94.7%).

CONCLUSIONS

Specific radiomic features could be used to select patients with lung adenocarcinoma who would benefit from immunotherapy because a subset of imaging radiomic features useful to predict OS or PFS time were different between the control group and the immunotherapy group.

Genetic and Epigenetic landscape of leukocyte infiltration identifies an immune prognosticator in lung adenocarcinoma

BACKGROUND

Leukocyte infiltration plays an critical role in outcome of various diseases including Lung adenocarcinoma (LUAD).

OBJECTIVES

To understand the genetic and epigenetic factors affecting leukocyte infiltration and identification and validation of immune based biomarkers.

METHOD

Correlation analysis was done to get the associations of the factors. CIBERSORT analysis was done for immune cell infiltration. Genetic and epigenetic analysis were performed. Cox regression was carried out for survival.

RESULTS

We categorized the TCGA-LUAD patients based on Leukocyte fraction (LF) and performed extensive immunogenomic analysis. Interestingly, we showed that LF has a negative correlation with copy number variation (CNV) but not with mutational load. However, several individual genetic mutations, including KRAS and KEAP1, were significantly linked with LF. Also, as expected, patients with high LF showed significantly increased expression of genes involved in leukocyte migration and activation. DNA methylation changes also showed a strong association with LF and regulated a significant proportion of genes associated with LF. We also developed and validated an independent prognostic immune signature using the top six prognostic genes associated with LF.

CONCLUSION

Together, we have identified clinical, genetic, and epigenetic variations associated with LUAD LF and developed an immune gene-based signature for disease prognostication.

Modern Challenges for Early-Phase Clinical Trial Design and Biomarker Discovery in Metastatic Non-Small-Cell Lung Cancer

Oncology research has changed extensively due to the possibility to categorize each cancer type into smaller subgroups based on histology and particularly on different genetic alterations due to their heterogeneity. The consequences of this heterogeneity are particularly evident in the management of metastatic non-small-cell lung cancer (NSCLC). This review will discuss the benefits and challenges of incorporating precision medicine into early- through late-phase metastatic NSCLC clinical trials, discussing examples of drug development programs in oncogene- and non-oncogene-addicted NSCLC. The experiences of clinical development of crizotinib, gefitinib and osimertinib are depicted showing that when a targeted drug is administrated in a study population not selected by any biomarker, trials could produce negative results. However, the early detection of biomarker-driven biology helps to obtain a greater benefit for a selected population and can reduce the required time for drug approval. Early clinical development programs involving nivolumab, pembrolizumab and avelumab, immune checkpoint inhibitors, taught us that, beyond safety and activity, the optimal selection of patients should be based on pre-specified biomarkers. Overall, the identification of predictive biomarkers is one of the greatest challenges of NSCLC research that should be optimized with solid methodological trial designs to maximize the clinical outcomes.

Emergency rigid bronchoscopy and immunotherapy: successful combination in dramatic respiratory debut of pulmonary adenocarcinoma

Malignant central airway obstruction is a life-threatening condition that often causes respiratory failure. In many cases, treatment of tumor in rigid bronchoscopy must be performed urgently, soothing respiratory symptoms and improving patient quality of life, in many cases reducing time to and allowing application of oncologic therapies. Immuno-oncologic therapies target the immune system selectively and are therefore much less toxic than standard chemotherapies, sometimes leading to outstanding results in advanced cancers for which there were no effective treatments until a few years ago. This report shows the effect of the joint application of rigid bronchoscopy and targeted immunotherapy in an emergency scenario, resulting in an unexpected extraordinary therapeutic success.

Small Cell Lung Cancer: State of the Art of the Molecular and Genetic Landscape and Novel Perspective

Simple Summary

Small cell lung cancer (SCLC) continues to carry a poor prognosis with a five-year survival rate of 3.5% and a 10-year survival rate of 1.8%. The pathogenesis remains unclear, and there are no known predictive or diagnostic biomarkers. The current SCLC classification as a single entity hinders effective targeted therapies against this heterogeneous neoplasm. Despite dedicated decades of research and clinical trials, there has been no change in the SCLC treatment paradigm. This review summarizes the body of literature available on SCLC’s genomic landscape to describe SCLC’s molecular/genetic aspects, regardless of therapeutic strategy.

Abstract

Small cell lung cancer (SCLC) is a highly proliferative lung cancer that is not amenable to surgery in most cases due to the high metastatic potential. Precision medicine has not yet improved patients’ survival due to the lack of actionable mutations. Intra- and intertumoral heterogeneity allow the neoplasms to adapt to various microenvironments and treatments. Further studying this heterogeneous cancer might yield the discovery of actionable mutations. First-line SCLC treatment has added immunotherapy to its armamentarium. There has been renewed interest in SCLC, and numerous clinical trials are underway with novel therapeutic approaches. Understanding the molecular and genetic landscape of this heterogeneous and lethal disease will pave the way for novel drug development.

The Importance of STK11/LKB1 Assessment in Non-Small Cell Lung Carcinomas

Despite the recent implementation of immunotherapy as a single treatment or in combination with chemotherapy for first-line treatment of advanced non-small cell lung cancer (NSCLC), many patients do not benefit from this regimen due to primary treatment resistance or toxicity. Consequently, there is an urgent need to develop efficient biomarkers that can select patients who will benefit from immunotherapy thereby providing the appropriate treatment and avoiding toxicity. One of the biomarkers recently described for the stratification of NSCLC patients undergoing immunotherapy are mutations in STK11/LKB1, which are often associated with a lack of response to immunotherapy in some patients. Therefore, the purpose of this review is to describe the different cellular mechanisms associated with STK11/LKB1 mutations, which may explain the lack of response to immunotherapy. Moreover the review addresses the co-occurrence of additional mutations that may influence the response to immunotherapy and the current clinical studies that have further explored STK11/LKB1 as a predictive biomarker. Additionally this work includes the opportunities and limitations to look for the STK11/LKB1 status in the therapeutic strategy for NSCLC patients.

Single bioengineered ncRNA molecule for dual-targeting toward the control of non-small cell lung cancer patient-derived xenograft tumor growth

Lung cancer remains the leading cause of cancer deaths worldwide and accounts for more than 22% of all cancer-related deaths in the US. Developing new therapies is essential to combat against deadly lung cancer, especially the most common type, non-small cell lung cancer (NSCLC). With the discovery of genome-derived functional small noncoding RNA (ncRNA), namely microRNAs (miRNA or miR), restoration of oncolytic miRNAs lost or downregulated in NSCLC cells represents a new therapeutic strategy. Very recently, we have developed a novel technology that achieves in vivo fermentation production of bioengineered miRNA agents (BERA) for research and development. In this study, we aimed at simultaneously introducing two miRNAs into NSCLC cells by using single recombinant "combinatorial BERA" (CO-BERA) molecule. Our studies show that single CO-BERA molecule (e.g., let-7c/miR-124) was successfully processed to two miRNAs (e.g., let-7c-5p and miR-124-3p) to combinatorially regulate the expression of multiple targets (e.g., RAS, VAMP3 and CDK6) in human NSCLC cells, exhibiting greater efficacy than respective BERA miRNAs in the inhibition of cell viability and colony formation. Furthermore, we demonstrate that CO-BERA let-7c/miR-124-loaded lipopolyplex nanomedicine was the most effective among tested RNAs in the control of tumor growth in NSCLC patient-derived xenograft mouse models. The anti-tumor activity of CO-BERA let-7c/miR-124 was associated with the suppression of RAS and CDK6 expression, and enhancement of apoptosis. These results support the concept to use single ncRNA agent for dual-targeting and offer insight into developing new RNA therapeutics for the treatment of lethal NSCLC.

Infections and Immunotherapy in Lung Cancer: A Bad Relationship?

Infectious diseases represent a relevant issue in lung cancer patients. Bacterial and viral infections might influence the patients’ prognosis, both directly affecting the immune system and indirectly impairing the outcome of anticancer treatments, mainly immunotherapy. In this analysis, we aimed to review the current evidence in order to clarify the complex correlation between infections and lung cancer. In detail, we mainly explored the potential impact on immunotherapy outcome/safety of (1) bacterial infections, with a detailed focus on antibiotics; and (2) viral infections, discriminating among (a) human immune-deficiency virus (HIV), (b) hepatitis B/C virus (HBV-HCV), and (c) Sars-Cov-2. A series of studies suggested the prognostic impact of antibiotic therapy administration, timing, and exposure ratio in patients treated with immune checkpoint inhibitors, probably through an antibiotic-related microbiota dysbiosis. Although cancer patients with HIV, HBV, and HCV were usually excluded from clinical trials evaluating immunotherapy, some retrospective and prospective trials performed in these patient subgroups reported similar results compared to those described in not-infected patients, with a favorable safety profile. Moreover, patients with thoracic cancers are particularly at risk of COVID-19 severe outcomes and mortality. Few reports speculated about the prognostic implications of anticancer therapy, including immunotherapy, in lung cancer patients with concomitant Sars-Cov-2 infection, showing, to date, inconsistent results. The correlation between infectious diseases and immunotherapy remains to be further explored and clarified in the context of dedicated trials. In clinical practice, the accurate and prompt multidisciplinary management of lung cancer patients with infections should be encouraged in order to select the best treatment options for these patients, avoiding unexpected toxicities, while maintaining the anticancer effect.

A Minimal PKPD Interaction Model for Evaluating Synergy Effects of Combined NSCLC Therapies

This paper introduces a mathematical compartmental formulation of dose-effect synergy modelling for multiple therapies in non small cell lung cancer (NSCLC): antiangiogenic, immuno- and radiotherapy. The model formulates the dose-effect relationship in a unified context, with tumor proliferating rates and necrotic tissue volume progression as a function of therapy management profiles. The model accounts for inter- and intra-response variability by using surface model response terms. Slow acting peripheral compartments such as fat and muscle for drug distribution are not modelled. This minimal pharmacokinetic-pharmacodynamic (PKPD) model is evaluated with reported data in mice from literature. A systematic analysis is performed by varying only radiotherapy profiles, while antiangiogenesis and immunotherapy are fixed to their initial profiles. Three radiotherapy protocols are selected from literature: (1) a single dose 5 Gy once weekly; (2) a dose of 5 Gy × 3 days followed by a 2 Gy × 3 days after two weeks and (3) a dose of 5 Gy + 2 × 0.075 Gy followed after two weeks by a 2 Gy + 2 × 0.075 Gy dose. A reduction of 28% in tumor end-volume after 30 days was observed in Protocol 2 when compared to Protocol 1. No changes in end-volume were observed between Protocol 2 and Protocol 3, this in agreement with other literature studies. Additional analysis on drug interaction suggested that higher synergy among drugs affects up to three-fold the tumor volume (increased synergy leads to significantly lower growth ratio and lower total tumor volume). Similarly, changes in patient response indicated that increased drug resistance leads to lower reduction rates of tumor volumes, with end-volume increased up to 25–30%. In conclusion, the proposed minimal PKPD model has physiological value and can be used to study therapy management protocols and is an aiding tool in the clinical decision making process. Although developed with data from mice studies, the model is scalable to NSCLC patients.