Genomic and Immunophenotypic Landscape of Acquired Resistance to PD-(L)1 Blockade in Non-Small-Cell Lung Cancer

Deciphering the Immunomodulatory Function of GSN+ Inflammatory Cancer-Associated Fibroblasts in Renal Cell Carcinoma Immunotherapy: Insights From Pan-Cancer Single-Cell Landscape and Spatial Transcriptomics Analysis

The heterogeneity of cancer-associated fibroblasts (CAFs) could affect the response to immune checkpoint inhibitor (ICI) therapy. However, limited studies have investigated the role of inflammatory CAFs (iCAFs) in ICI therapy using pan-cancer single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics sequencing (ST-seq) analysis. We performed pan-cancer scRNA-seq and ST-seq analyses to identify the subtype of GSN+ iCAFs, exploring its spatial distribution characteristics in the context of ICI therapy. The pan-cancer scRNA-seq and bulk RNA-seq data are incorporated to develop the Caf.Sig model, which predicts ICI response based on CAF gene signatures and machine learning approaches. Comprehensive scRNA-seq analysis, along with in vivo and in vitro experiments, investigates the mechanisms by which GSN+ iCAFs influence ICI efficacy. The Caf.Sig model demonstrates well performances in predicting ICI therapy response in pan-cancer patients. A higher proportion of GSN+ iCAFs is observed in ICI non-responders compared to responders in the pan-cancer landscape and clear cell renal cell carcinoma (ccRCC). Using real-world immunotherapy data, the Caf.Sig model accurately predicts ICI response in pan-cancer, potentially linked to interactions between GSN+ iCAFs and CD8+ Tex cells. ST-seq analysis confirms that interactions and cellular distances between GSN+ iCAFs and CD8+ exhausted T (Tex) cells impact ICI efficacy. In a co-culture system of primary CAFs, primary tumour cells and CD8+ T cells, downregulation of GSN on CAFs drives CD8+ T cells towards a dysfunctional state in ccRCC. In a subcutaneously tumour-grafted mouse model, combining GSN overexpression with ICI treatment achieves optimal efficacy in ccRCC. Our study provides the Caf.Sig model as an outperforming approach for patient selection of ICI therapy, and advances our understanding of CAF biology and suggests potential therapeutic strategies for upregulating GSN in CAFs in cancer immunotherapy.

Phase 2 Trial of Combination Radiotherapy and Pembrolizumab Plus Chemotherapy in Patients With Previously Untreated Metastatic NSCLC: NJLCG 1902

Introduction

Treatment strategies that enhance the efficacy of immunotherapy are desired. Radiotherapy can enhance immunity, but the utility of adding radiotherapy to immunotherapy plus platinum-doubled chemotherapy in patients with metastatic NSCLC has not been explored.

Methods

This multicenter, single-arm phase 2 trial evaluated the efficacy and safety of combining radiotherapy with pembrolizumab plus chemotherapy in patients with previously untreated metastatic NSCLC. Patients begin receiving pembrolizumab plus platinum-doublet chemotherapy within 1 week of starting radiotherapy (30 Gy in 10 fractions). The primary end point was the 12-month progression-free survival (PFS) rate. The secondary end points included PFS, overall survival, and toxicity profiles.

Results

Forty patients were enrolled. In total, 37 and 38 patients were analyzed for efficacy and safety, respectively. The 12-month PFS rate was 44.3% (90% confidence interval [CI]: 30.3-57.3), which met the primary end point. The median PFS was 8.4 months (95% CI: 5.7-22.2), and the median overall survival was 30.1 months (95% CI: 22.3-not reached). Grade 3 or 4 adverse events occurred in 25 patients (65.8%), and one treatment-related death was reported. Pneumonitis was reported in 10 patients (26.3%), including two cases of grade 3 pneumonitis and one case of grade 5.

Conclusions

Adding radiotherapy to pembrolizumab plus platinum-doublet chemotherapy led to promising efficacy in patients with previously untreated metastatic NSCLC. Although caution should be exercised with regard to pneumonitis, adverse events were tolerable. Further research is needed to confirm the efficacy and safety of this strategy.

Tumor microenvironment-driven resistance to immunotherapy in non-small cell lung cancer: strategies for Cold-to-Hot tumor transformation

Non-small cell lung cancer (NSCLC) represents a formidable challenge in oncology due to its molecular heterogeneity and the dynamic suppressive nature of its tumor microenvironment (TME). Despite the transformative impact of immune checkpoint inhibitors (ICIs) on cancer therapy, the majority of NSCLC patients experience resistance, necessitating novel approaches to overcome immune evasion. This review highlights shared and subtype-specific mechanisms of immune resistance within the TME, including metabolic reprogramming, immune cell dysfunction, and physical barriers. Beyond well-characterized components such as regulatory T cells, tumor-associated macrophages, and myeloid-derived suppressor cells, emerging players - neutrophil extracellular traps, tertiary lymphoid structures, and exosomal signaling networks - underscore the TME's complexity and adaptability. A multi-dimensional framework is proposed to transform cold, immune-excluded tumors into hot, immune-reactive ones. Key strategies include enhancing immune infiltration, modulating immunosuppressive networks, and activating dormant immune pathways. Cutting-edge technologies, such as single-cell sequencing, spatial transcriptomics, and nanomedicine, are identified as pivotal tools for decoding TME heterogeneity and personalizing therapeutic interventions. By bridging mechanistic insights with translational innovations, this review advocates for integrative approaches that combine ICIs with metabolic modulators, vascular normalizers, and emerging therapies such as STING agonists and tumor vaccines. The synergistic potential of these strategies is poised to overcome resistance and achieve durable antitumor immunity. Ultimately, this vision underscores the importance of interdisciplinary collaboration and real-time TME profiling in refining precision oncology for NSCLC, offering a blueprint for extending these advances to other malignancies.

Acquired resistance to immunotherapy in solid tumors

Acquired resistance to immunotherapy (ARI) is a major challenge in solid tumors, limiting long-term success in up to 65% of patients who initially respond to immunotherapy. Defining ARI clinically remains complex, but ongoing efforts aim to establish standardized criteria. This review describes recent insights into ARI, revealing complex mechanisms involving both tumor-intrinsic mechanisms - such as antigen loss and presentation defects, interferon γ (IFNγ) insensitivity, tumor-mediated T cell exclusion, and metabolic reprogramming - as well as extrinsic factors such as inhibitory molecule upregulation, immunosuppressive cells, extracellular matrix (ECM) remodeling, and dysbiotic microbiota. Understanding the development of ARI is crucial for prevention and effective interventions. The integration of innovative strategies and translational research on appropriately collected samples is key to overcoming ARI and ensuring durable benefits for patients.

Resistance in Lung Cancer Immunotherapy and How to Overcome It: Insights from the Genetics Perspective and Combination Therapies Approach

Lung cancer with the highest number of new cases diagnosed in Europe and in Poland, remains an example of malignancy with a very poor prognosis despite the recent progress in medicine. Different treatment strategies are now available for cancer therapy based on its type, molecular subtype and other factors including overall health, the stage of disease and cancer molecular profile. Immunotherapy is emerging as a potential addition to surgery, chemotherapy, radiotherapy or other targeted therapies, but also considered a mainstay therapy mode. This combination is an area of active investigation in order to enhance efficacy and overcome resistance. Due to the complexity and dynamic of cancer's ecosystem, novel therapeutic targets and strategies need continued research into the cellular and molecular mechanisms within the tumour microenvironment. From the genetic point of view, several signatures ranging from a few mutated genes to hundreds of them have been identified and associated with therapy resistance and metastatic potential. ML techniques and AI can enhance the predictive potential of genetic signatures and model the prognosis. Here, we present the overview of already existing treatment approaches, the current findings of key aspects of immunotherapy, such as immune checkpoint inhibitors (ICIs), existing molecular biomarkers like PD-L1 expression, tumour mutation burden, immunoscore, and neoantigens, as well as their roles as predictive markers for treatment response and resistance.

Impact of Co-mutations and Transcriptional Signatures in Non-Small Cell Lung Cancer Patients Treated with Adagrasib in the KRYSTAL-1 Trial

PURPOSE

KRAS inhibitors are revolutionizing the treatment of non-small cell lung cancer (NSCLC), but clinico-genomic determinants of treatment efficacy warrant continued exploration.

EXPERIMENTAL DESIGN

Patients with advanced KRASG12C-mutant NSCLC treated with adagrasib [KRYSTAL-1 (NCT03785249)] were included in the analysis. Pretreatment next-generation sequencing data were collected per protocol. HTG EdgeSeq Transcriptome Panel was used for gene expression profiling. Clinical endpoints included objective response, progression-free survival (PFS), and overall survival (OS). KRASG12C-mutant NSCLC cell lines and xenograft models were used for sensitivity analyses and combination drug screens.

RESULTS

KEAP1 MUT and STK11MUT were associated with shorter survival to adagrasib [KEAP1: PFS 4.1 vs. 9.9 months, HR 2.7, P < 0.01; OS 5.4 vs. 19.0 months, HR 3.6, P < 0.01; STK11: PFS 4.2 vs. 11.0 months, HR 2.2, P < 0.01; OS 9.8 months vs. not reached (NR), HR 2.6, P < 0.01]. KEAP1WT/STK11WT status identified adagrasib-treated patients with significantly longer PFS (16.9 months) and OS (NR). Preclinical analyses further validate the association between KEAP1 loss of function and adagrasib resistance. Adagrasib and mTOR inhibitor combinations produced higher treatment efficacy in NSCLC models harboring STK11 and KEAP1 co-mutations. NRF2HIGH signaling was associated with shorter survival to adagrasib (PFS: 4.2 vs. 8.4 months, HR 2.0, P = 0.02; OS: 6.5 vs. 19.0 months, HR 2.8, P < 0.01) even in patients with KEAP1WT NSCLC. KEAP1WT/STK11WT/NRF2LOW status identified patients-32%-with longer survival to adagrasib (PFS 12.0 vs. 4.2 months, HR 0.2, P < 0.01; OS NR vs. 8.0 months, HR 0.1, P < 0.01).

CONCLUSIONS

KEAP1, STK11, and NRF2 status define patients with KRASG12C-mutant NSCLC with markedly distinct outcomes to adagrasib. These results further support the use of genomic features-mutational and nonmutational-for the treatment selection of patients with KRASG12C-mutant NSCLC.

New insights into cancer immune checkpoints landscape from single-cell RNA sequencing

Immune checkpoint blockade (ICB) therapy represents a pivotal advancement in tumor immunotherapy by restoring the cytotoxic lymphocytes' anti-tumor activity through the modulation of immune checkpoint functions. Nevertheless, many patients experience suboptimal therapeutic outcomes, likely due to the immunosuppressive tumor microenvironment, drug resistance, and other factors. Single-cell RNA sequencing has assisted to precisely investigate the immune infiltration patterns before and after ICB treatment, enabling a high-resolution depiction of previously unrecognized functional interaction among immune checkpoints. This review addresses the heterogeneity between tumor microenvironments that respond to or resist ICB therapy, highlighting critical factors underlying the variation in immunotherapy efficacy and elucidating treatment failure. Furthermore, a comprehensive examination is provided of how specific ICBs modulate immune and tumor cells to achieve anti-tumor effects and generate treatment resistance, alongside a summary of emerging immune checkpoints identified as promising targets for cancer immunotherapy through single-cell RNA sequencing applications.

A phase II trial of mTORC1/2 inhibition in STK11 deficient non small cell lung cancer

There are no current stratified medicine options for STK11-deficient NSCLC. STK11 loss mediates mTORC activation, GLUT1 up-regulation and increased glycolysis. This metabolic reprogramming might represent a therapeutic vulnerability targetable with mTORC1/2 inhibition. In arm B2 of the National Lung Matrix Trial 54 patients with NSCLC received vistusertib, of which 49 were STK11-deficient (30 with KRAS mutation (B2D), 19 without (B2S)). Objective response (OR) and durable clinical benefit (DCB) rates with 95% credible intervals (CrI) were estimated from posterior probability distributions generated using Bayesian beta-binomial conjugate analysis. In B2D, 2 per-protocol patients obtained OR (estimated true OR rate (95%CrI) 9.8% (2.4-24.3). Estimates of true DCB rate (95%CrI): B2D 24.4% (11.1-42.3), B2S 14.6% (3.6-34.7). Overall, vistusertib cannot be recommended in this context. Longitudinal ctDNA analysis demonstrates enrichment of SMARCA4 mutations post-treatment. In vitro studies show adaptive resistance to mTORC1/2 inhibition via AKT reactivation. (NCT02664935, ISRCTN38344105, EudraCT 2014-000814-73, 10 June 2015).

Comprehensive immunophenotyping reveals distinct tumor microenvironment alterations in anti-PD-1 sensitive and resistant syngeneic mouse model

The advent of immune checkpoint inhibitors targeting the PD-1/PD-L1 pathway has revolutionized cancer treatment, resulting in improved clinical outcomes. However, resistance remains a critical challenge. This study aimed to comparatively elucidate immunophenotypic changes in syngeneic mouse models sensitive (MC-38) or resistant (LLC1) to anti-PD-1 monoclonal antibody (mAb) treatment. In the sensitive MC-38 model, anti-PD-1 therapy increased dendritic cells (DCs) and macrophages, while decreasing myeloid-derived suppressor cells (MDSCs) within the tumor microenvironment. Enhanced expression of antigen presentation molecules (MHC I/II) and costimulatory molecules (CD80/CD86) was observed on tumor-associated DCs and macrophages. Tumor-infiltrating CD4+T, CD8+T, regulatory T, NK, and NKT cells also significantly increased. Importantly, treatment boosted lymphocyte cytotoxic potential, with perforin identified as a key marker of efficacy. Notably, perforin expression in CD4+T and NKT cells strongly negatively correlated with tumor volume. In contrast, the resistant LLC1 model exhibited minimal immunophenotypic changes upon treatment. These findings highlight critical immune modifications induced by anti-PD-1 therapy, particularly the role of perforin, and the DC/MDSC ratio in predicting therapeutic outcomes. This research offers valuable insights into potential predictive biomarkers and informs strategies to overcome resistance, emphasizing the complex interplay between anti-PD-1 treatment and the tumor microenvironment, ultimately aiming to improve immunotherapy response rates.

Primary and Acquired Resistance to Immunotherapy with Checkpoint Inhibitors in NSCLC: From Bedside to Bench and Back

Immunotherapy with checkpoint inhibitors has become the cornerstone of systemic treatment for non-oncogene addicted non-small-cell lung cancer. Despite its pivotal role, a significant proportion of patients-approximately 70-85%-either exhibit primary resistance to PD-1 blockade or develop acquired resistance following an initial benefit, even in combination with chemotherapy and/or anti-CTLA-4 agents. The phenomenon of primary and acquired resistance to immunotherapy represents a critical clinical challenge, largely based on our incomplete understanding of the mechanisms of action of immunotherapy, and the resulting lack of accurate predictive biomarkers. Here, we review the definitions and explore the proposed mechanisms of primary and acquired resistance, including those related to the tumor microenvironment, systemic factors, and intrinsic tumor characteristics. We also discuss translational data on adaptive changes within tumor cells and the immune infiltrate following exposure to checkpoint inhibitors. Lastly, we offer a comprehensive overview of current and emerging therapeutic strategies designed to prevent primary resistance and counteract acquired resistance.

Hallmarks of artificial intelligence contributions to precision oncology

The integration of artificial intelligence (AI) into oncology promises to revolutionize cancer care. In this Review, we discuss ten AI hallmarks in precision oncology, organized into three groups: (1) cancer prevention and diagnosis, encompassing cancer screening, detection and profiling; (2) optimizing current treatments, including patient outcome prediction, treatment planning and monitoring, clinical trial design and matching, and developing response biomarkers; and (3) advancing new treatments by identifying treatment combinations, discovering cancer vulnerabilities and designing drugs. We also survey AI applications in interventional clinical trials and address key challenges to broader clinical adoption of AI: data quality and quantity, model accuracy, clinical relevance and patient benefit, proposing actionable solutions for each.

Clinical-genomic nomogram for predicting sensitivity to second-line immunotherapy for advanced non-small cell lung cancer

Background

The introduction of immune checkpoint inhibitors (ICIs) has significantly improved the outcomes of patients with advanced non-small cell lung cancer (NSCLC). However, ICIs only benefit a subset of patients. The study aimed to identify genomic biomarkers and construct models to predict the response to second-line ICI therapy.

Methods

We retrospectively collected clinical data and genetic testing results from patients with NSCLC treated with second-line ICI at a single medical center between August 2018 and June 2021. We reanalyzed the raw sequence data of clinical genetic testing and defined the common detection region among the different testing panels. Immunotherapy sensitivity was evaluated using the immune-based Response Evaluation Criteria in Solid Tumors.

Results

We included 102 patients as a training cohort and 46 as a test cohort. In the training cohort, we examined the relationship between ICI response and the mutation status of 343 genes. Mutations in the EGFR gene were significantly more common in the resistant group than in the sensitive group (41.0% vs. 20.6%; P=0.04), while mutations in the EP300 gene were associated with greater sensitivity to ICIs (39.7% vs. 15.4%; P=0.01). A nomogram was built based on clinical variables, genomic data, and programmed death-ligand 1 (PD-L1) expression. The total nomogram points were significantly higher in the sensitive group than in the resistance group in both cohorts, and the areas under the receiver operating characteristic curve were 0.780 in the training cohort and 0.720 in the test cohort. The higher nomogram points also indicated better progression-free survival.

Conclusions

Based on real-world clinical settings, the clinical genomic nomogram, which involved limited input variables that were economical and easy to obtain, demonstrated a good ability to predict the response to second-line ICI treatment in advanced NSCLC.

Resistance to immunotherapy in non-small cell lung cancer: Unraveling causes, developing effective strategies, and exploring potential breakthroughs

Over the last two decades, advancements in deciphering the intricate interactions between oncology and immunity have fueled a meteoric rise in immunotherapy for non-small cell lung cancer, typified by an explosive growth of immune checkpoint inhibitors. However, resistance to immunotherapy remains inevitable. Herein we unravel the labyrinthine mechanisms of resistance to immunotherapy, characterized by their involvement of nearly all types of cells within the body, beyond the extrinsic cancer cells, and importantly, such cells are not only (inhibitory or excitatory, or both) signal recipients but also producers, acting in a context-dependent manner. At the molecular level, these mechanisms underlie genetic and epigenetic aberrations, which are regulated by or regulate various protein kinases, growth factors, and cytokines with inherently dynamic and spatially heterogeneous properties. Additionally, macroscopic factors such as nutrition, comorbidities, and the microbiome within and around organs or tumor cells are involved. Therefore, developing therapeutic strategies combined with distinct action informed by preclinical, clinical, and real-world evidence, such as radiotherapy, chemotherapy, targeted therapy, antibody-drug conjugates, oncolytic viruses, and cell-based therapies, may stand as a judicious reality, although the ideality is to overcome resistance point-by-point through a novel drug. Notably, we highlight a realignment of treatment aims, moving the primary focus from eliminating cancer cells -- such as through chemotherapy and radiotherapy -- to promoting immune modulation and underscore the value of regulating various components within the host macro- or micro-environment, as their effects, even if seemingly minimal, can cumulatively contribute to visible clinical benefit when applied in combination with ICIs. Lastly, this review also emphasizes the current hurdles scattered throughout preclinical and clinical studies, and explores evolving directions in the landscape of immunotherapy for NSCLC.

Loss of JAK1 Function Causes G2/M Cell Cycle Defects Vulnerable to Kif18a Inhibition

To gain insight into biological mechanisms that cause resistance to DNA damage, we performed parallel pooled genetic CRISPR-Cas9 screening for survival in high risk HNSCC subtypes. Surprisingly, and in addition to ATM, DNAPK, and NFKB signaling, JAK1 was identified as a driver of tumor cell radiosensitivity. Knockout of JAK1 in HNSCC increases cell survival by enhancing the DNA damage-induced G2 arrest, and both knockout and JAK1 inhibition with abrocitinib prevent subsequent formation of radiation-induced micronuclei. Loss of JAK1 function does not affect canonical CDK1 signaling but does reduce activation of PLK1 and AURKA, kinases that regulate both G2 and M phase progression. Correspondingly, JAK1 KO was found to cause mitotic defects using both EdU labeling and live cell imaging techniques. Given this insight, we evaluated Kif18a inhibition as an approach to exacerbate mitotic stress and enhance the efficacy of radiation. These studies establish Kif18a inhibition as a novel strategy to counteract therapeutic resistance to DNA damage mediated by G2 cell cycle arrest.

Spatially resolved transcriptomics reveal the determinants of primary resistance to immunotherapy in NSCLC with mature tertiary lymphoid structures

Effectiveness of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) has been linked to the presence of mature tertiary lymphoid structures (mTLSs) within the tumor microenvironment (TME). However, only a subset of mTLS-positive NSCLC derives benefit, thus highlighting the need to unravel ICI response determinants. The comprehensive analysis of ICI-treated patients with NSCLC (n = 509) from the Bergonié Institute Profiling (BIP) study (NCT02534649) reveals that the presence of mTLSs correlates with improved clinical outcomes, independently of programmed death ligand 1 (PD-L1) expression and genomic features. Employing spatial transcriptomics alongside multiplex immunofluorescence (mIF), we show that two distinct subsets of cancer-associated fibroblasts (CAFs) are essential factors in mediating primary resistance to ICIs in mTLS-positive NSCLC. These CAFs are associated with immune exclusion, CD8+ T cell exhaustion, and increased regulatory CD4+ T cell infiltration, underscoring an immunosuppressive TME. Our study highlights the pivotal role of specific CAF subsets in thwarting ICIs, proposing new therapeutic targets to enhance immunotherapy efficacy.

Loss of CDKN2A Enhances the Efficacy of Immunotherapy in EGFR-Mutant Non-Small Cell Lung Cancer

Mutant EGFR is a common driver of non-small cell lung cancer (NSCLC). Although mutant EGFR has been reported to limit the efficacy of immunotherapy, a subset of patients with EGFR-mutant NSCLC benefit from treatment with immune checkpoint inhibitors. A better understanding of how co-occurring genomic alterations in oncogenic driver genes impact immunotherapy efficacy may provide a more complete understanding of cancer heterogeneity and identify biomarkers of response. Here, we investigated the effects of frequent EGFR co-mutations in EGFR-mutant lung cancer models and identified loss-of-function mutation of CDKN2A as a potential sensitizer to anti-PD-1 treatment in vitro and in vivo. Mechanistically, CDKN2A loss impacted the composition of the tumor immune microenvironment by promoting the expression of PD-L2 through reduced ubiquitination of c-MYC, and mutant EGFR cooperating to upregulate c-MYC and PD-L2 by activating the MAPK pathway. Blocking PD-L2 induced antitumor immune responses mediated by CD8+ T cells in EGFR/CDKN2A co-mutated lung cancer. Importantly, a small-molecule PD-L2 inhibitor, zinc undecylenate, remodeled the tumor immune microenvironment of EGFR/CDKN2A co-mutant tumors and enhanced the antitumor efficacy of EGFR tyrosine kinase inhibitors. Collectively, these results identify EGFR/CDKN2A co-mutation as a distinct subtype of NSCLC that shows superior sensitivity to immune checkpoint blockade and reveals a potential combined therapeutic strategy for treating this NSCLC subtype. Significance: Upregulation of c-MYC driven by co-mutation of CDKN2A and EGFR increases PD-L2 to abrogate CD8+ T-cell activity in lung cancer, which confers sensitivity to PD-L2 blockade in combination with tyrosine kinase inhibitors.

Technological advances in clinical individualized medication for cancer therapy: from genes to whole organism

Efforts have been made to leverage technology to accurately identify tumor characteristics and predict how each cancer patient may respond to medications. This involves collecting data from various sources such as genomic data, histological information, functional drug profiling, and drug metabolism using techniques like polymerase chain reaction, sanger sequencing, next-generation sequencing, fluorescence in situ hybridization, immunohistochemistry staining, patient-derived tumor xenograft models, patient-derived organoid models, and therapeutic drug monitoring. The utilization of diverse detection technologies in clinical practice has made "individualized treatment" possible, but the desired level of accuracy has not been fully attained yet. Here, we briefly summarize the conventional and state-of-the-art technologies contributing to individualized medication in clinical settings, aiming to explore therapy options enhancing clinical outcomes.

Longitudinal genomic profiling using liquid biopsies in metastatic nonsquamous NSCLC following first line immunotherapy

Tumor genomic profiling is often limited to one or two timepoints due to the invasiveness of tissue biopsies, but longitudinal profiling may provide deeper clinical insights. Using ctDNA data from IMpower150 study, we examined genetic changes in metastatic non-squamous NSCLC post-first-line immunotherapy. Mutations were most frequently detected in TP53, KRAS, SPTA1, FAT3, and LRP1B at baseline and during treatment. Mutation levels rose prior to radiographic progression in most progressing patients, with specific mutations (SPTA1, STK11, KEAP1, SMARCA4, TBX3, CDH2, and MLL3) significantly enriched in those with progression or nondurable response. However, ctDNA's role in detecting hyperprogression and pseudoprogression remains uncertain. STK11, SMARCA4, KRAS, SLT2, and KEAP1 mutations showed the strongest correlation with poorer overall survival, while SMARCA4, STK11, SPTA1, TBX3, and KEAP1 mutations correlated with shorter progression-free survival. Overall, longitudinal liquid biopsy profiling provided valuable insights into lung cancer biology post-immunotherapy, potentially guiding personalized therapies and future drug development.

Hypoxia is linked to acquired resistance to immune checkpoint inhibitors in lung cancer

Despite the established use of immune checkpoint inhibitors (ICIs) to treat non-small cell lung cancer (NSCLC), only a subset of patients benefit from treatment and ∼50% of patients whose tumors respond eventually develop acquired resistance (AR). To identify novel drivers of AR, we generated murine Msh2 knock-out (KO) lung tumors that initially responded but eventually developed AR to anti-PD-1, alone or in combination with anti-CTLA-4. Resistant tumors harbored decreased infiltrating T cells and reduced cancer cell-intrinsic MHC-I and MHC-II levels, yet remained responsive to IFNγ. Resistant tumors contained extensive regions of hypoxia, and a hypoxia signature derived from single-cell transcriptional profiling of resistant cancer cells was associated with decreased progression-free survival in a cohort of NSCLC patients treated with anti-PD-1/PD-L1 therapy. Targeting hypoxic tumor regions using a hypoxia-activated pro-drug delayed AR to ICIs in murine Msh2 KO tumors. Thus, this work provides a rationale for targeting tumor metabolic features, such as hypoxia, in combination with immune checkpoint inhibition.

CAR T Cells and T-Cell Therapies for Cancer: A Translational Science Review

Importance

Chimeric antigen receptor (CAR) T cells are T lymphocytes that are genetically engineered to express a synthetic receptor that recognizes a tumor cell surface antigen and causes the T cell to kill the tumor cell. CAR T treatments improve overall survival for patients with large B-cell lymphoma and progression-free survival for patients with multiple myeloma.

Observations

Six CAR T-cell products are approved by the US Food and Drug Administration (FDA) for 6 hematologic malignancies: B-cell acute lymphoblastic leukemia, large B-cell lymphoma, follicular lymphoma, mantle cell lymphoma, chronic lymphocytic leukemia, and multiple myeloma. Compared with standard chemotherapy followed by stem cell transplant, CAR T cells improved 4-year overall survival in patients with large B-cell lymphoma (54.6% vs 46.0%). Patients with pediatric acute lymphoblastic leukemia achieved durable remission after CAR T-cell therapy. At 3-year follow-up, 48% of patients were alive and relapse free. In people with multiple myeloma treated previously with 1 to 4 types of non-CAR T-cell therapy, CAR T-cell therapy prolonged treatment-free remissions compared with standard treatments (in 1 trial, CAR T-cell therapy was associated with progression-free survival of 13.3 months compared with 4.4 months with standard therapy). CAR T-cell therapy is associated with reversible acute toxicities, such as cytokine release syndrome in approximately 40% to 95% of patients, and neurologic disorders in approximately 15% to 65%. New CAR T-cell therapies in development aim to increase efficacy, decrease adverse effects, and treat other types of cancer. No CAR T-cell therapies are FDA approved for solid tumors, but recently, 2 other T lymphocyte-based treatments gained approvals: 1 for melanoma and 1 for synovial cell sarcoma. Additional cellular therapies have attained responses for certain solid tumors, including pediatric neuroblastoma, synovial cell sarcoma, melanoma, and human papillomavirus-associated cancers. A common adverse effect occurring with these T lymphocyte-based therapies is capillary leak syndrome, which is characterized by fluid retention, pulmonary edema, and kidney dysfunction.

Conclusions and Relevance

CAR T-cell therapy is an FDA-approved therapy that has improved progression-free survival for multiple myeloma, improved overall survival for large B-cell lymphoma, and attained high rates of cancer remission for other hematologic malignancies such as acute lymphoblastic leukemia, follicular lymphoma, and mantle cell lymphoma. Recently approved T lymphocyte-based therapies demonstrated the potential for improved outcomes in solid tumor malignancies.

Next-generation immunotherapy: igniting new hope for lung cancer

Adoption of immunotherapy has completely transformed the treatment landscape of cancer. Patients with advanced cancer treated with immunotherapy may benefit from durable tumor response and long-term survival. The most widely used immunotherapy in solid tumors is anti-programmed-death (ligand) protein (PD-(L)1), which is now an integral part of non-small cell lung cancer (NSCLC) treatment irrespective of histological cell types and tumor stage. However, the vast majority of patients with advanced NSCLC treated with anti-PD-(L)1 still develop therapeutic resistance, and the prognosis after anti-PD-(L)1 resistance is poor. Resistance mechanisms to PD-1 blockade are often complex and encompass a combination of defects within the cancer-immunity cycle. These defects include failure in antigen presentation and T-cell priming, presence of co-inhibitory immune checkpoints, inability of immune cells to infiltrate the tumor, and presence of immunosuppressive tumor microenvironment. Recently, advances in drug design, genomic sequencing, and gene editing technologies have led to development of next-generation immunotherapies that may potentially overcome these resistance mechanisms. In this review, we will discuss the anti-PD-(L)1 resistance mechanism landscape in NSCLC and four novel modalities of immunotherapy in detail, namely novel immune checkpoint inhibitor and targeted therapy combinations, bispecific antibodies, cancer vaccine, and cell therapy. These novel therapeutics have all demonstrated early clinical data in NSCLC treatment and may work synergistically with each other to restore anticancer immunity. In addition, we share our perspectives on the future promises and challenges in the transformation of these novel immunotherapies to standard clinical care.

Spatial transcriptomics reveals profound subclonal heterogeneity and T-cell dysfunction in extramedullary myeloma

ABSTRACT

Extramedullary disease (EMD) is a high-risk feature of multiple myeloma (MM) and remains a poor prognostic factor, even in the era of novel immunotherapies. Here, we applied spatial transcriptomics (RNA tomography for spatially resolved transcriptomics [tomo-seq] [n = 2] and 10x Visium [n = 12]) and single-cell RNA sequencing (n = 3) to a set of 14 EMD biopsies to dissect the 3-dimensional architecture of tumor cells and their microenvironment. Overall, infiltrating immune and stromal cells showed both intrapatient and interpatient variations, with no uniform distribution over the lesion. We observed substantial heterogeneity at the copy number level within plasma cells, including the emergence of new subclones in circumscribed areas of the tumor, which is consistent with genomic instability. We further identified the spatial expression differences between GPRC5D and TNFRSF17, 2 important antigens for bispecific antibody therapy. EMD masses were infiltrated by various immune cells, including T cells. Notably, exhausted TIM3+/PD-1+ T cells diffusely colocalized with MM cells, whereas functional and activated CD8+ T cells showed a focal infiltration pattern along with M1 macrophages in tumor-free regions. This segregation of fit and exhausted T cells was resolved in the case of response to T-cell-engaging bispecific antibodies. MM and microenvironment cells were embedded in a complex network that influenced immune activation and angiogenesis, and oxidative phosphorylation represented the major metabolic program within EMD lesions. In summary, spatial transcriptomics has revealed a multicellular ecosystem in EMD with checkpoint inhibition and dual targeting as potential new therapeutic avenues.

Worldwide research trends on bone metastases of lung cancer: a bibliometric analysis

Background

Lung cancer has the highest fatality rate among all malignancies worldwide. Within this disease, bone metastasis (BM) emerges as a particularly deleterious site of metastatic dissemination, marked by a dismal prognosis. The objective of this investigation is to shed light on the current international research efforts and the development trajectory on lung cancer BM through a bibliometric analysis (performance and visualization analysis).

Method

Data were obtained from the Web of Science Core Collection repository on lung cancer BM from 1 January 2012 to 1 January 2022. Subsequently, the collected data underwent scrutiny using the VOSviewer software to reveal patterns of co-authorship, co-citation, and keyword analysis, while the CiteSpace software facilitated the generation of keyword cluster maps and performed burst analyses.

Results

The study included 327 papers of 2,154 authors, 587 organizations, and 41 countries, and explored the cooperation between them and the relationships between citations. Over the past decade, published papers showed a steady growth trend. China had the highest production with 189 papers, and USA had the highest collaboration with other countries, with 43 total link strength. Lung Cancer exhibited the highest frequency of co-cited journals, with a co-citation time of 412 and an IF/JCR partition of 6.081/Q1 in 2021. The most frequently co-cited article, authored by Tsuya A and published in Lung Cancer in 2007, amassed 70 co-citations. High-frequency keywords were categorized into four clusters: pathogenesis, treatment and clinical manifestations, prognosis, and diagnosis. In recent years, there has been a significant increase in the strong citation burst strength of keywords such as "predictor," "skeletal-related events," "efficacy," "migration," "docetaxel," and "impact." Lung adenocarcinoma is the most common type of tumor.

Conclusion

This bibliometric study provides a comprehensive analysis of lung cancer BM in the recent 10 years. The field of early diagnosis, pathogenesis, and new treatments is entering a phase of rapid development and remains valuable for future research.

Genetic variants of LRRC8C, OAS2, and CCL25 in the T cell exhaustion-related genes are associated with non-small cell lung cancer survival

Background

T cell exhaustion is a state in which T cells become dysfunctional and is associated with a decreased efficacy of immune checkpoint inhibitors. Lung cancer has the highest mortality among all cancers. However, the roles of genetic variants of the T cell exhaustion-related genes in the prognosis of non-small cell lung cancer (NSCLC) patients has not been reported.

Methods

We conducted a two-stage multivariable Cox proportional hazards regression analysis with two previous genome-wide association study (GWAS) datasets to explore associations between genetic variants in the T cell exhaustion-related genes and survival of NSCLC patients. We also performed expression quantitative trait loci analysis for functional validation of the identified variants.

Results

Of all the 52,103 single nucleotide polymorphisms (SNPs) in 672 T cell exhaustion-related genes, 1,721 SNPs were found to be associated with overall survival (OS) of 1185 NSCLC patients of the discovery GWAS dataset from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, and 125 of these 1,721 SNPs remained significant after validation in an additional independent replication GWAS dataset of 984 patients from the Harvard Lung Cancer Susceptibility (HLCS) Study. In multivariable stepwise Cox model analysis, three independent SNPs (i.e., LRRC8C rs10493829 T>C, OAS2 rs2239193 A>G, and CCL25 rs3136651 T>A) remained significantly associated with OS with hazards ratios (HRs) of 0.86 (95% confidence interval (CI) = 0.77-0.96, P = 0.008), 1.48 (95% CI = 1.18-1.85, P < 0.0001) and 0.78 (95% CI = 0.66-0.91, P = 0.002), respectively. Further combined analysis for these three SNPs suggested that an unfavorable genotype score was associated with a poor OS and disease-specific survival. Expression quantitative trait loci analysis suggested that the LRRC8C rs10493829 C allele was associated with elevated LRRC8C mRNA expression levels in normal lymphoblastoid cells, lung tissue, and whole blood.

Conclusion

Our findings suggested that these functional SNPs in the T cell exhaustion-related genes may be prognostic predictors for survival of NSCLC patients, possibly via a mechanism of modulating corresponding gene expression.

Predicting resistance and pseudoprogression: are minimalistic immunoediting mathematical models capable of forecasting checkpoint inhibitor treatment outcomes in lung cancer?

BACKGROUND

The increased application of immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 in lung cancer treatment generates clinical need to reliably predict individual patients' treatment outcomes.

METHODS

To bridge the prediction gap, we examine four different mathematical models in the form of ordinary differential equations, including a novel delayed response model. We rigorously evaluate their individual and combined predictive capabilities with regard to the patients' progressive disease (PD) status through equal weighting of model-derived outcome probabilities.

RESULTS

Fitting the complete treatment course, the novel delayed response model (R2=0.938) outperformed the simplest model (R2=0.865). The model combination was able to reliably predict patient PD outcome with an overall accuracy of 77% (sensitivity = 70%, specificity = 81%), solely through calibration with primary tumor longest diameter measurements. It autonomously identified a subset of 51% of patients where predictions with an overall accuracy of 81% (sensitivity = 81%, specificity = 81%) can be achieved. All models significantly outperformed a fully data-driven machine learning-based approach.

IMPLICATIONS

These modeling approaches provide a dynamic baseline framework to support clinicians in treatment decisions by identifying different treatment outcome trajectories with already clinically available measurement data.

LIMITATIONS AND FUTURE DIRECTIONS

Conjoint application of the presented approach with other predictive tools and biomarkers, as well as further disease information (e.g. metastatic stage), could further enhance treatment outcome prediction. We believe the simple model formulations allow widespread adoption of the developed models to other cancer types. Similar models can easily be formulated for other treatment modalities.

Companion Tests and Personalized Cancer Therapy: Reaching a Glass Ceiling

The use of companion diagnostics has become a standard in precision oncology in the context of ongoing therapeutic innovation. However, certain limitations make their application imperfect in current practice. This position paper underscores the need to broaden the notion of companion testing, considering the potential of emerging technologies, including computational biology, to overcome these limitations. This wave of progress should impact not only our representation of the analytical tool itself but also the nature of the tumoral sample under analysis (liquid biopsies). The complex inter-relationship between companion test guided-personalized therapy, and health agency policies for new drug agreements will also be discussed.

Comparative analysis of PD-L1 expression and molecular alterations in primary versus metastatic lung adenocarcinoma: a real-world study in China

Objectives

Programmed death-ligand 1 (PD-L1) is the only Food and Drug Administration-approved biomarker for monitoring response to immune checkpoint inhibitor (ICI) therapy in patients with lung adenocarcinoma. Understanding the nuances of molecular phenotypes, clinical attributes, and PD-L1 expression levels in primary and metastatic lung adenocarcinoma may help predict response to therapy and assist in the clinical management of lung adenocarcinoma.

Methods

A total of 235 primary and metastatic lesion specimens from patients with non-small cell lung cancer (NSCLC) an institution in Shandong, China were analyzed. PD-L1 expression was assessed by immunohistochemistry using the 22C3 antibody, and the molecular phenotype was determined by next-generation sequencing of 450 genes. The molecular phenotypes of the primary and metastatic lesions were compared.

Results

Elevated PD-L1 expression was significantly associated with advanced and metastatic disease (P = 0.001). The distribution of PD-L1 expression varied based on the anatomical location, showing a higher frequency of elevated PD-L1 expression in distal metastases than in the primary tumor. Metastatic lesions exhibited a higher proportion of carcinogenic pathway gene alterations and a greater number of DNA damage-repair pathway gene alterations than the primary lesions. Notably, CDKN2A copy number deletions were more prevalent in metastatic lesions than in primary lesions. Clinical data stemming from research conducted at the Memorial Sloan Kettering Cancer Center revealed an association between the absence of CDKN2A expression and a poorer prognosis in stage I lung adenocarcinoma.

Conclusion

Samples of metastatic tumors exhibited a higher proportion of elevated PD-L1 expression, a greater number of pathway alterations, and a higher occurrence of CDKN2A copy number deletions than primary samples. This highlights the importance of reinforcing the clinical management and follow-up of patients with CDKN2A deficiency, particularly within the subset of stage I lung adenocarcinoma.

Unsuccessful rechallenge with nivolumab in a patient with advanced non-small cell lung cancer who had a 6-year complete response and treatment-free period: Case report

Several predictive factors of immune checkpoint inhibitor response have been reported, but there has not been sufficient exploration of which patients benefit from immune checkpoint inhibitor rechallenge. We report the case of a patient with non-small cell lung cancer who had 6 years of complete response with initial nivolumab treatment. After relapse, however, rechallenge with nivolumab did not result in tumour shrinkage or long-term response. Even in patients who had an exceptional response to the initial immune checkpoint inhibitor, long-term efficacy may not be achieved by immune checkpoint inhibitor rechallenge. Thorough investigation of biomarkers that predict efficacy of immune checkpoint inhibitor rechallenge is warranted.

Expanding the repertoire of Antibody Drug Conjugate (ADC) targets with improved tumor selectivity and range of potent payloads through in-silico analysis

Antibody-Drug Conjugates (ADCs) have emerged as a promising class of targeted cancer therapeutics. Further refinements are essential to unlock their full potential, which is currently limited by a lack of validated targets and payloads. Essential aspects of developing effective ADCs involve the identification of surface antigens, ideally distinguishing target tumor cells from healthy types, uniformly expressed, accompanied by a high potency payload capable of selective targeting. In this study, we integrated transcriptomics, proteomics, immunohistochemistry and cell surface membrane datasets from Human Protein Atlas, Xenabrowser and Gene Expression Omnibus utilizing Lantern Pharma's proprietary AI platform Response Algorithm for Drug positioning and Rescue (RADR®). We used this in combination with evidence based filtering to identify ADC targets with improved tumor selectivity. Our analysis identified a set of 82 targets and a total of 290 target indication combinations for effective tumor targeting. We evaluated the impact of tumor mutations on target expression levels by querying 416 genes in the TCGA mutation database against 22 tumor subtypes. Additionally, we assembled a catalog of compounds to identify potential payloads using the NCI-Developmental Therapeutics Program. Our payload mining strategy classified 729 compounds into three subclasses based on GI50 values spanning from pM to 10 nM range, in combination with sensitivity patterns across 9 different cancer indications. Our results identified a diverse range of both targets and payloads, that can serve to facilitate multiple choices for precise ADC targeting. We propose an initial approach to identify suitable target-indication-payload combinations, serving as a valuable starting point for development of future ADC candidates.

New promises and challenges in the treatment of advanced non-small-cell lung cancer

Targeted therapies and immunotherapies have radically improved treatment for advanced non-small-cell lung cancer (NSCLC). Tyrosine kinase inhibitors targeting oncogenic driver mutations continue to evolve over multiple generations to enhance effectiveness and tackle drug resistance. Immune checkpoint inhibitors remain integral for the treatment of NSCLCs that do not have specific actionable genetic mutations. Antibody-drug conjugates and bispecific antibodies are being integrated into treatment guidelines, and emerging therapies include T-cell engagers, cellular therapies, cancer vaccines, and external devices. Despite these advances, challenges remain in identifying predictive biomarkers to individually tailor treatments, abrogate resistance, reduce costs, and ensure optimal cancer treatment accessibility.

Dysregulated gene expression of SUMO machinery components induces the resistance to anti-PD-1 immunotherapy in lung cancer by upregulating the death of peripheral blood lymphocytes

Background

The majority of patients with lung cancer exhibit drug resistance after anti-PD-1 immunotherapy, leading to shortened patient survival time. Previous studies have suggested an association between epigenetic abnormalities such as methylation and clinical response to anti-PD-1 immunotherapy, while the role of SUMOylation in resistance to anti-PD-1 antibody immunotherapy is still unclear.

Methods

Here, the mRNA expression of 15 SUMO machinery components in PBMC from lung cancer patients receiving anti-PD-1 immunotherapy were analyzed using real-time PCR. Base on the percentage change in mRNA levels, the relationship between the expression of SUMO machinery components and outcomes of anti-PD-1 immunotherapy, and the influencing factors of SUMOylation were evaluated. PBMC was treated with different concentrations of 2-D08 (a specific inhibitor of SUMOylation) in vitro, and analyzed the activation and the death rates of lymphocyte subsets by flow cytometry analysis.

Results

A predictive method, base on the gene expression of three SUMO machinery components (SUMO1, SUMO3 and UBE2I), were developed to distinguish non-responders to PD-1 inhibitors. Furthermore, the number of lymphocytes in peripheral blood significantly reduced in the dysregulated SUMOylation groups (the percentage change >100 or -50 ~ -100 groups). In vitro studies confirmed that lightly low SUMOylation level improved the activation status of T and NK lymphocytes, but extremely low SUMOylation level lead to the increased death rates of lymphocytes.

Conclusion

Our findings implied that dysregulated gene expression of SUMO machinery components could induce the resistance of anti-PD-1 immunotherapy in lung cancer by upregulating the death of peripheral blood lymphocytes. These data might provide effective circulating biomarkers for predicting the efficacy of anti-PD-1 immunotherapy, and uncovered a novel regulatory mechanism of resistance to anti-PD-1 immunotherapy.

Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology

Advancements in imaging technologies have revolutionized our ability to deeply profile pathological tissue architectures, generating large volumes of imaging data with unparalleled spatial resolution. This type of data collection, namely, spatial proteomics, offers invaluable insights into various human diseases. Simultaneously, computational algorithms have evolved to manage the increasing dimensionality of spatial proteomics inherent in this progress. Numerous imaging-based computational frameworks, such as computational pathology, have been proposed for research and clinical applications. However, the development of these fields demands diverse domain expertise, creating barriers to their integration and further application. This review seeks to bridge this divide by presenting a comprehensive guideline. We consolidate prevailing computational methods and outline a roadmap from image processing to data-driven, statistics-informed biomarker discovery. Additionally, we explore future perspectives as the field moves toward interfacing with other quantitative domains, holding significant promise for precision care in immuno-oncology.

SMARCA4 mutation induces tumor cell-intrinsic defects in enhancer landscape and resistance to immunotherapy

Cancer genomic studies have identified frequent alterations in components of the SWI/SNF (SWItch/Sucrose Non- Fermenting) chromatin remodeling complex including SMARCA4 and ARID1A . Importantly, clinical reports indicate that SMARCA4 -mutant lung cancers respond poorly to immunotherapy and have dismal prognosis. However, the mechanistic basis of immunotherapy resistance is unknown. Here, we corroborated the clinical findings by using immune-humanized, syngeneic, and genetically engineered mouse models of lung cancer harboring SMARCA4 deficiency. Specifically, we show that SMARCA4 loss caused decreased response to anti-PD1 immunotherapy associated with significantly reduced infiltration of dendritic cells (DCs) and CD4+ T cells into the tumor microenvironment (TME). Mechanistically, we show that SMARCA4 loss in tumor cells led to profound downregulation of STING, IL1β and other components of the innate immune system as well as inflammatory cytokines that are required for efficient recruitment and activity of immune cells. We establish that this deregulation of gene expression is caused by cancer cell-intrinsic reprogramming of the enhancer landscape with marked loss of chromatin accessibility at enhancers of genes involved in innate immune response such as STING, IL1β, type I IFN and inflammatory cytokines. Interestingly, we observed that transcription factor NF-κB binding motif was highly enriched in enhancers that lose accessibility upon SMARCA4 deficiency. Finally, we confirmed that SMARCA4 and NF-κB co-occupy the same genomic loci on enhancers associated with STING and IL1β, indicating a functional interplay between SMARCA4 and NF-κB. Taken together, our findings provide the mechanistic basis for the poor response of SMARCA4 -mutant tumors to anti-PD1 immunotherapy and establish a functional link between SMARCA4 and NF-κB on innate immune and inflammatory gene expression regulation.

[Research Progress on Predictive Biomarkers of Immunotherapy Efficacy in Non-small Cell Lung Cancer]

Lung cancer is one of the most common malignant tumors in the world, of which non-small cell lung cancer (NSCLC) is the majority. The emergence of immune checkpoint inhibitors (ICIs) has greatly changed the treatment strategy of NSCLC and improved the prognosis of patients. However, in reality, only a small number of patients can achieve long-term benefit. Therefore, the identification of reliable predictive biomarkers is essential for the selection of treatment modalities. With the development of molecular biology and genome sequencing technology in recent years, as well as the in-depth understanding of tumor and its host immune microenvironment, research on biomarkers has emerged in an endless stream. This review focuses on the predictive biomarkers of immunotherapy efficacy in NSCLC, in order to provide some guidance for precision immunotherapy.
.

Immune checkpoint blockade resistance in lung cancer: emerging mechanisms and therapeutic opportunities

Immune checkpoint blockade (ICB) therapy works by inhibiting suppressive checkpoints that become upregulated after T cell activation, like PD-1/PD-L1 and CTLA-4. While the initial FDA approvals of ICB have revolutionized cancer therapies and fueled a burgeoning immuno-oncology field, more recent clinical development of new agents has been slow. Here, focusing on lung cancer, we review the latest research uncovering tumor cell intrinsic and extrinsic ICB resistance mechanisms as major hurdles to treatment efficacy and clinical progress. These include genomic and non-genomic tumor cell alterations, along with host and microenvironmental factors like the microbiome, metabolite accumulation, and hypoxia. Together, these factors can cooperate to promote immunosuppression and ICB resistance. Opportunities to prevent resistance are constantly evolving in this rapidly expanding field, with the goal of moving toward personalized immunotherapeutic regimens.

Beyond Chemoimmunotherapy in Advanced Non-Small Cell Lung Cancer: New Frontiers, New Challenges

Chemoimmunotherapy is currently the preferred first-line treatment option for the majority of patients with advanced non-small cell lung cancer without driver genetic alterations. Most of these patients, however, will experience disease progression within the first year after treatment initiation and both patients and their physicians will be confronted with the dilemma of the optimal second-line treatment. Identification of molecular targets, such as KRASG12C, BRAFV600X, METexon14, and human epidermal growth factor receptor 2 mutations, and RET rearrangements offer therapeutic opportunities in pretreated patients with corresponding alterations. For those tumors that do not harbor oncogenic drivers, second-line treatment with docetaxel remains the current standard of care despite modest efficacy. Strategies to challenge docetaxel include the combination of immune checkpoint inhibitors (ICIs) with tyrosine inhibitors of multiple kinases or with DNA damage response inhibitors, antibody-drug conjugates, and locoregional treatments for oligoprogressive disease. Next-generation immunotherapy strategies, such as T-cell engagers, immune-mobilizing monoclonal T-cell receptors, chimeric antigen receptor cell therapy, tumor infiltrating lymphocytes, and T-cell receptor cell therapy are being currently investigated in the quest to reverse resistance to ICIs. Importantly, the advent of these new agents heralds a novel spectrum of toxicities that require both the physician's and the patient's education. Herein, we review current and future strategies aiming to outperform docetaxel after chemoimmunotherapy failure, and we provide practical information on how to best communicate to our patients the unique toxicity aspects associated with immunotherapy.