The gut microbiota exhibits intricate connections with the body's immune system and holds significant implications for various diseases and cancers. Currently, accumulating evidence suggests a correlation between the composition of the gut microbiota and the development, treatment, and prognosis of melanoma. However, the underlying pathogenesis remains incompletely elucidated. In this comprehensive review, we present an in-depth review of the role played by gut microbiota in melanoma tumorigenesis, growth, metastasis, treatment response, and prognosis. Furthermore, we discuss the potential utility of gut microbiota as a promising prognostic marker. Lastly, we summarize three routes through which gut microbiota influences melanoma: immunity, aging, and the endocrine system. By modulating innate and adaptive immunity in patients with melanoma across different age groups and genders, the gut microbiota plays a crucial role in anti-tumor immune regulation from tumorigenesis to prognosis management, thereby impacting tumor growth and metastasis. This review also addresses current study limitations while highlighting future research prospects.

Tumor-associated macrophages (TAMs) play a key role in facilitating a range of cancerous processes by modulating the tumor microenvironment thus being a target for cancer treatment. Astragaloside III (AS-III), a compound derived from Astragalus triterpenoid saponins, has demonstrated immunomodulatory and anticancer properties, but the underlying mechanism remains unclear. Here, we demonstrated that AS-III suppressed metastasis, angiogenesis and induced apoptosis of lung cancer in vitro and in vivo by inhibiting macrophage M2 polarization and inducing M1 phenotype transformation. This was achieved through the inhibition of the MAPK signaling pathway. Furthermore, the tumor inhibitory effects of AS-III were found to be mediated by the Akt/mTOR pathway. Overall, these results highlight the role of AS-III in modifying the TAMs in TME, offering fresh perspectives on tumor immunotherapy by means of targeting macrophage.

This meta-analysis aimed to evaluate the efficacy and safety of combining pemetrexed and platinum with or without pembrolizumab for the treatment of advanced non-small-cell lung cancer (NSCLC).

A systematic search of PubMed, Embase, Cochrane Library, and Web Of Science databases was conducted to identify studies comparing pemetrexed and platinum with or without pembrolizumab in advanced NSCLC. Raw data were extracted from eligible studies to calculate Hazard Ratios (HR) for Progression-Free Survival (PFS) and Overall Survival (OS), as well as rates of adverse events of all grades and those of Grade 3 or higher.

Eight studies with 1639 patients occurred advanced NSCLC included. The group receiving pembrolizumab in combination with pemetrexed and platinum showed significant benefits in terms of OS (HR 0.63; 95% CI 0.54-0.73; p < 0.00001) and PFS (HR:0.64; 95% CI 0.48-0.85; p = 0.002) compared to the group receiving pemetrexed and platinum alone. However, this benefit was accompanied by a higher incidence of Grade 3 or higher adverse events (OR: 1.55; 95% CI 1.24-1.95; p = 0.0001).

The combination of pemetrexed and platinum with pembrolizumab is recommended as a first-line treatment option for advanced NSCLC due to its significant efficacy benefits. However, the increased risk of Grade 3 or higher adverse events suggests the need for careful consideration and assessment when considering this regimen for second-line or subsequent therapy.

Immune checkpoint inhibitors (ICIs) targeting programmed death ligand-1 (PD-L1) provide clinical benefits for various advanced malignancies. However, the predictive factors that determine sensitivity to ICIs have not been fully elucidated. We focused on tumor-derived CXCL10/11 as a pivotal factor that determines the response to PD-L1 blockade by regulating T cell accumulation and tumor angiogenesis. We previously reported that CXCL10/11 was upregulated by interferon (IFN)-γ in ICI-sensitive tumor cells but not in ICI-resistant cells, including mouse Lewis lung carcinoma (LLC). In the present study, gene silencing of tumor-derived CXCL10/11 induced resistance to PD-L1 blockade in AB1-HA mesothelioma cell-bearing mice. To identify the mechanisms underlying ICI resistance, we performed a microarray analysis to compare the IFN-γ-inducible genes between ICI-sensitive AB1-HA and ICI-resistant LLC in vitro. A pathway analysis based on microarray data indicated that hypoxia-inducible factor (HIF) 1A is the key signal that inhibits CXCL10/11 expression. We revealed that the HIF1A inhibitors echinomycin (EC) and YC-1 upregulated CXCL10/11 genes induced by IFN-γ in tumor cells in vitro. In addition, combination therapy with PD-L1 blockade and EC demonstrated synergistic antitumor effects in LLC-bearing mice. Combination therapy enhanced tumor infiltration of CD8 T cells and suppressed tumor angiogenesis. The present study suggests that HIF1A signaling in tumor cells dominates ICI resistance via the downregulation of tumor-derived CXCL10/11.

Immuno-oncology (IO) is one of the fastest growing therapeutic areas within oncology. IO agents work indirectly via the host's adaptive and innate immune system to recognize and eradicate tumor cells. Despite checkpoint inhibitors being only introduced to the market since 2011, they have become the second most approved product category. Current Food and Drug Administration (FDA)-approved classes of IO agents include: immune checkpoint inhibitors (ICIs), chimeric antigen receptor T-cell therapy (CAR-T), bi-specific T-cell engager (BiTE) antibody therapy, T-cell receptor (TCR) engineered T cell therapy, tumor-infiltrating lymphocyte (TIL) therapy, cytokine therapy, cancer vaccine therapy, and oncolytic virus therapy. Cancer immunotherapy has made progress in multiple cancer types including melanoma, non-small cell lung cancer (NSCLC), renal cell carcinoma (RCC), and urothelial carcinoma; however, several cancers remain refractory to immunotherapy. Future directions of IO include exploration in the neoadjuvant/perioperative setting, combination strategies, and optimizing patient selection through improved biomarkers.

Biomarker-guided designs are increasingly used to evaluate personalized treatments based on patients' biomarker status in Phase II and III clinical trials. With adaptive enrichment, these designs can improve the efficiency of evaluating the treatment effect in biomarker-positive patients by increasing their proportion in the randomized trial. While time-to-event outcomes are often used as the primary endpoint to measure treatment effects for a new therapy in severe diseases like cancer and cardiovascular diseases, there is limited research on biomarker-guided adaptive enrichment trials in this context. Such trials almost always adopt hazard ratio methods for statistical measurement of treatment effects. In contrast, restricted mean survival time (RMST) has gained popularity for analyzing time-to-event outcomes because it offers more straightforward interpretations of treatment effects and does not require the proportional hazard assumption. This paper proposes a two-stage biomarker-guided adaptive RMST design with threshold detection and patient enrichment. We develop sophisticated methods for identifying the optimal biomarker threshold and biomarker-positive subgroup, treatment effect estimators, and approaches for type I error rate, power analysis, and sample size calculation. We present a numerical example of re-designing an oncology trial. An extensive simulation study is conducted to evaluate the performance of the proposed design.

Lung cancer is the leading cause of cancer-related deaths worldwide. Patients with an amplification of the MTHFD2 gene have a particularly poor prognosis. MTHFD2 signaling has been associated with migration, metastasis, and proliferation of lung cancer cells mediated through ERK signaling. Although the enzymatic activity of the MTHFD2 protein is well understood, little is known about its larger role in chemoresistance.

Seventy-nine of non-small cell lung cancer (NSCLC) samples with clinical follow-up were subjected to immunohistochemical staining for MTHFD2 and sequenced using next generation sequencing (NGS) to determine EGFR status. MTHFD2 gene was knocked down in two NSCLC cell lines with wild type EGFR gene (HCC44 and H1993) where MTHFD2 signaling and chemotherapy resistance against pemetrexed were evaluated.

MTHFD2 expression data revealed a strong prognosis relevance in adenocarcinoma (LUAD). Immunoblotting of cell lines showed a MTHFD2 dependent and cell type specific ERK signaling in EGFR wild type cells. MTHFD2 expression induced proliferation of NSCLC cells and their resistance against pemetrexed. Knocking down the MTHFD2 gene induced cycle arrest, however, it did not activate apoptosis signaling within HCC44 cell line.

MTHFD2 expression is strongly associated with prognosis in LUAD patients, as well as with increased cellular proliferation and resistance to pemetrexed in LUAD patients with wild-type EGFR. These findings suggest that MTHFD2 could serve as a valuable biomarker for predicting treatment outcomes in LUAD. Further studies are needed to fully explore the clinical implications and potential combination therapies targeting MTHFD2 in LUAD.

In the treatment of non-small cell lung cancer (NSCLC), immune checkpoint inhibitors (ICIs) have markedly improved patient survival, yet some patients do not benefit. The existing prognostic factors are limited, highlighting the development of reliable and convenient predictive indicators.

A retrospective analysis was performed on 219 NSCLC patients treated with ICIs from June 2019 to January 2024. The nutritional risk screening (NRS 2002) and the neutrophil-to-lymphocyte ratio (NLR) were employed to evaluate the patients' nutritional status and inflammatory response, aiming to investigate the correlation between these markers and treatment outcomes.

The median follow-up duration for the overall population was 29 (IQR: 25.96-32.04) months. The analysis showed that the median progression-free survival (mPFS) and median overall survival (mOS) in the high nutritional risk group (NRS2002 ≥ 3, accounting for 23.74%) were significantly lower than those in the low nutritional risk group (NRS2002 < 3, accounting for 76.26%) (mPFS: 2.5 vs 16 months; mOS: 8 vs 16 months, both P < 0.001). Similarly, patients with high NLR values (> 4.92) had significantly shorter OS and PFS than those with low NLR (≤ 4.92) values (mOS: 7 vs 18 months; mPFS: 3 vs 17 months, both P < 0.001). Multivariate Cox analysis revealed that a high NRS 2002 score (HR = 2.76, 95% CI 1.68-4.54, P < 0.001) and high NLR (HR = 2.77, 95% CI 1.65-4.64, P < 0.001) were independent predictors of poor prognosis. Risk stratification was performed using a combined scoring system of NRS 2002 and NLR (0 points-low risk, 1 point-moderate risk, 2 points-high risk), and it was found that as the risk score increased, OS and PFS significantly decreased (mOS: 8 [2.61-13.39] vs 16 [13.04-18.96] vs NA [NA-NA] months; mPFS: 2.5 [0.99-4.02] vs 8.5 [5.47-11.53] vs 16 [11.41-20.59] months, respectively, both P < 0.001). The utility of the combined NLR and NRS2002 scoring model was assessed using a time-dependent receiver operating characteristic (ROC) curve, with results indicating that at 12 months, the AUC value of the combined scoring model was 0.81 (CI 0.72-0.90). At 24 and 36 months, the AUC values were 0.73 (CI 0.66-0.80) and 0.70 (CI 0.64-0.76), respectively. Moreover, the nomogram model exhibited high predictive accuracy in predicting survival prognosis, with AUC values of 0.84 (CI 0.77-0.91), 0.85 (CI 0.79-0.91), and 0.78 (CI 0.69-0.88) at 12, 24, and 36 months, respectively.

The combined NRS 2002 and NLR scoring can serve as an effective prognostic tool for NSCLC patients receiving ICIs treatment. This scoring system helps clinicians more accurately identify patients who will benefit from immunotherapy, thereby facilitating more personalized treatment plans. Further validation of this scoring system's applicability and reliability is warranted in future multicenter, large-sample prospective studies.

Since mediastinal lymph node dissection and radiotherapy (RT) have potential unclear impacts on pulmonary lymphatic system, this study aimed to assess the effectiveness of immune checkpoint inhibitors (ICIs) in recurrent/metastatic non-small-cell lung cancer (NSCLC) patients who previously received radical surgery with or without thoracic RT.

Clinical data of patients who underwent pulmonary lobectomy with systematic lymphadenectomy (2000.1.1-2021.7.2) and received immunotherapy after progression were retrospectively analyzed. Efficacy was mainly evaluated based on progression-free survival (PFS) from the start of the ICIs. Toxicity was defined as treatment discontinuation due to immune-related adverse effects (irAEs).

Ninety-five patients were enrolled in the final cohort and 30 (31.6%) patients received thoracic RT before ICI treatment. ICIs were administered as a first-line systematic treatment in 52.6% of patients. The median follow-up time was 14.7 months (95% confidence interval [CI] 13.3-18.7 months). The median PFS was 12.3 months (95% CI 8.5-36.6 months). Six (6.3%) patients had treatment suspended due to irAEs. Patients who received RT had comparable median PFS with the non-RT group (17.0 months vs. 11.1 months, p = 0.16). Similar toxicity rates were observed. Similar mPFS were reported in the stage III subgroup (RT vs. non-RT, 8.10 vs. 8.45 months, p = 0.86) or the subgroup treated by ICIs as primary systematic therapy (RT vs. non-RT, 13.6 vs. 16.1 months, p = 0.45).

ICIs remained effective in recurrent/metastatic NSCLC patients with radical surgery and RT did not significantly compromise therapeutic effects.

Modern clinical trials can capture tens of thousands of clinicogenomic measurements per individual. Discovering predictive biomarkers, as opposed to prognostic markers, remains challenging. To address this, we present a neural network framework based on contrastive learning-the Predictive Biomarker Modeling Framework (PBMF)-that explores potential predictive biomarkers in an automated, systematic, and unbiased manner. Applied retrospectively to real clinicogenomic datasets, particularly for immuno-oncology (IO) trials, our algorithm identifies biomarkers of IO-treated individuals who survive longer than those treated with other therapies. We demonstrate how our framework retrospectively contributes to a phase 3 clinical trial by uncovering a predictive, interpretable biomarker based solely on early study data. Patients identified with this predictive biomarker show a 15% improvement in survival risk compared to those in the original trial. The PBMF offers a general-purpose, rapid, and robust approach to inform biomarker strategy, providing actionable outcomes for clinical decision-making.

Quantitative systems pharmacology (QSP) models of cancer immunity provide mechanistic insights into cellular dynamics and drug effects that are difficult to study clinically. However, their inability to predict patient survival mechanistically limits their utility in anti-cancer drug development. To overcome this, we link virtual patients from a QSP model to real clinical trial patients. Using data from atezolizumab trials in non-small cell lung cancer, we show that tumor-based linkage effectively captures survival outcomes. By treating linked survival and censoring as weak supervision labels, we trained survival models using only QSP model covariates, without clinical covariates. Our approach also predicts survival for treatments not included in training data. Specifically, we accurately estimated survival hazard ratios (HR) for chemotherapy monotherapy and atezolizumab plus chemotherapy combination. The predicted HR of 0.70 (95% prediction interval [PI] 0.55-0.86) closely matches the observed HR of 0.79 (95% PI 0.64-0.98) from the IMpower130 trial.

Bone metastases are a major concern in cancer management since they significantly contribute to morbidity and mortality. Metastatic lesions, commonly arising from breast, prostate, lung, and kidney cancers, affect approximately 25% of cancer patients, leading to severe complications such as pain, fractures, and neurological deficits. This narrative review explores contemporary approaches to bone metastases, emphasizing a multidisciplinary strategy and the evolving concept of oligometastatic disease. Oligometastases, defined by limited metastatic spread (1-5 lesions), offer a potential window for curative treatment through aggressive interventions, including stereotactic ablative radiotherapy and resection surgery. Tumor boards, integrating systemic therapies with local interventions, are crucial to optimize treatment. Despite promising results, gaps remain in defining optimal treatment sequences and refining patient selection criteria. Future research should focus on personalized approaches, leveraging biomarkers and advanced imaging to enhance outcomes and the quality of life in patients with bone metastases.

Upper aerodigestive squamous cell carcinoma (UASCC) presents significant challenges in clinical management due to its aggressive nature. Here, we elucidate the role of MLL3 mutations as early, clonal genomic events in UASCC tumorigenesis, highlighting their role as foundational drivers of cancer development. Utilizing CRISPR-edited, cross-species organoid modeling, we demonstrate that loss of MLL3 contributes to early squamous neoplastic evolution. Furthermore, we identify an MLL3/GRHL2 protein complex that regulates the UASCC epigenome, particularly impacting immune response pathways. Notably, a novel MLL3/GRHL2-IRF1 axis promotes the expression of Th1 chemokines, enhancing anti-tumor immunity by facilitating T cell infiltration into the tumor microenvironment. Consequently, MLL3 regulates the in vivo efficacy of immune checkpoint blockade (ICB) therapy, corroborated by the strong association between MLL3 expression and human patients' clinical response to ICB therapy. Our work underscores the significance of MLL3 in UASCC pathogenesis and highlights the interplay between MLL3/GRHL2 and immune response pathways as potential therapeutic targets for UASCC treatment.

Programmed death-ligand 1 (PD-L1) immunohistochemistry is a predictive biomarker for anti-PD-(L)1 therapy in non-small cell lung cancer (NSCLC). It is not a reliable predictor of clinical benefit with non-invasive imaging providing a potential solution. We present the PECan study, the aim of which to assess the relationship of [99mTc]-labeled anti-PD-L1 single-domain antibody (NM-01) single-photon emission computed tomography (SPECT)/CT with metabolic response to anti-PD-(L)1.

PD-L1 tumour proportion score (TPS) measured using SP263 assay. [99mTc]NM-01 SPECT/CT and [18F]FDG PET/CT performed before and 9-weeks following pembrolizumab with/without chemotherapy in patients with advanced NSCLC. Tumor (T) to blood pool (BP) maximum region of interest (ROImax) measurements performed in primary and metastatic lesions using SPECT/CT images.

Fifteen patients were included (median age 63 years, 9 male). Intertumoural heterogeneity evident in 10(67%) patients. Mean [99mTc]NM-01 T:BP demonstrated moderate correlation with PD-L1 TPS (r = 0.45, p < 0.05). Depth of [18F]FDG PET/CT metabolic response at 9-weeks (n = 13), correlated strongly with baseline [99mTc]NM-01 T:BP (r = -0.73, p < 0.05), but only moderately with PD-L1 TPS (r = -0.46, p = 0.06).

[99mTc]NM-01 SPECT/CT allows non-invasive quantification of PD-L1 in primary tumour and metastases in NSCLC. [99mTc]NM-01 uptake moderately correlates with PD-L1 immunohistochemistry, determines heterogeneity, and is associated with early metabolic response to anti-PD-1 pembrolizumab.

PD-L1 Expression in Cancer (PECan) study (NCT04436406), registered 18 June 2020 https://clinicaltrials.gov/ct2/show/NCT04436406.

To identify imaging biomarkers of primary tumors and lymph nodes in patients with stage III-IV non-small cell lung cancer (NSCLC) and assess their predictive ability for treatment response (response vs. non-response) to immune checkpoint inhibitors (ICIs) after 6 months.

Retrospective analysis of 83 NSCLC patients treated with ICIs. Quantitative imaging features of the maximum primary lung tumors and lymph nodes on contrast-enhanced CT imaging were extracted at baseline (time point 0, TP0) and after 2-3 cycles of immunotherapy (time point 1, TP1). Delta-radiomics features (delta-RFs) were defined as the net changes in radiomics features (RFs) between TP0 and TP1. Interobserver interclass coefficient (ICC) and Pearson correlation analyses were applied for feature selection, and logistic regression (LR) was used to build a model for predicting treatment response.

Four and five important delta-RFs were selected to construct the nodal and tumor models, respectively. Δ Tumor diameter was used for constructing the clinical prediction model. The predictive efficacy of the nodal model for the treatment response status was higher than that of the tumor and clinical models. In the training set, the AUC values for the three models were 0.96 (95% CI = 0.90-1.00), 0.86 (95% CI = 0.76-0.95), and 0.82 (95% CI = 0.71-0.93), respectively. In the validation set, the AUC values were 0.94 (95% CI = 0.85-1.00), 0.77 (95% CI = 0.56-0.98), and 0.74 (95% CI = 0.48-1.00), respectively.

The nodal model based on delta-RFs performed well in distinguishing responders from non-responders and could identify patients more likely to benefit from immunotherapy. Finally, the nodal model exhibited a higher classification performance than the tumor model.

Immune checkpoint inhibitors (ICIs) have significantly improved the efficacy and prognosis of patients with non-small cell lung cancer (NSCLC). However, there remains a lack of optimal predictive biomarkers for assessing the response of ICIs. This study aimed to evaluate peripheral inflammatory factors as potential predictive biomarkers for NSCLC patients treated with ICIs. We retrospectively analyzed the correlation between peripheral inflammatory factors and the efficacy and prognosis of 124 patients with driver gene-negative advanced NSCLC who received first-line ICIs at our center from September 2018 to June 2022. Progression-free survival (PFS) was estimated using the Kaplan-Meier method. The association between the factors and multiple endpoints were investigated using univariate and multivariate analyses. A total of 124 patients were enrolled in this study. The objective response rate (ORR) was 49.2% and the disease control rate (DCR) was 97.6%, respectively. The median PFS was 12.7 months. The ORR differed statistically between groups based on the NLR, SII, with higher ORR observed in patients with an NLR ratio < 0.68, SII at 6 weeks < 531.26, and SII ratio < 0.74 (p < 0.05). The univariate analysis indicated that ECOG 0-1, smoking, NLR at 6 weeks < 2.72, NLR ratio < 0.68, LMR < 1.34, LMR ratio ≥ 1.38, and SII at 6 weeks < 531.26 were associated with longer PFS (p < 0.05). The multivariate analysis revealed that smoking (p = 0.013), baseline LMR (p = 0.015), and SII at 6 weeks (p = 0.010) were independent predictors of PFS. NLR, LMR, and SII maybe biomarkers for predicting the efficacy and prognosis of first-line ICIs therapy in driver gene-negative advanced NSCLC.

Protein tyrosine kinase 7 (PTK7) overexpression in lung cancer is associated with tumor progression. Cofetuzumab pelidotin (Cofe-P) is an antibody-drug conjugate comprising an anti-PTK7 antibody conjugated to a microtubule inhibitor. Herein, we report the results of a phase 1b study evaluating Cofe-P safety, efficacy, and pharmacokinetics in patients with recurrent non-small cell lung cancer (NSCLC).

This signal-seeking phase 1b, open-label, multicenter, single-arm study enrolled patients with PTK7-expressing recurrent NSCLC. Cofe-P was administered at 2.8 mg/kg intravenously once every 3 weeks. The primary endpoint was objective response rate (ORR) and secondary endpoints were duration of response (DOR), progression-free survival (PFS), and overall survival (OS).

Overall, 65 patients received Cofe-P; 51 had PTK7 expression of ≥90 % tumor cells with ≥2+ staining intensity by immunohistochemistry. All patients reported adverse events (AEs), most commonly alopecia (52 %) and decreased neutrophil count (43 %); 69 % had grade ≥3 AEs, including grade ≥3 neutropenia in 25 %. Treatment-related AEs were reported in 94 % of patients; none were fatal. Overall, ORR was 18 %; in patients with PTK7 expression of ≥90 % tumor cells with ≥2+ staining and non-squamous epidermal growth factor receptor (EGFR) wild type or mutant, or squamous NSCLC, ORR was 21 %, 15 %, and 13 %, respectively. Overall, median DOR was 7.2 months, median PFS was 5.5 months, and median OS was 12.6 months; longest DOR (median 9.0 months), PFS (median 6.8 months), and OS (median 12.6 months) were in patients with non-squamous EGFR-mutant NSCLC.

Cofe-P demonstrated a manageable safety profile and preliminary efficacy across NSCLC histologies and EGFR mutation status. These data support PTK7 as a valid therapeutic target for NSCLC.

Although lung cancer is a major cause of cancer incidence and mortality worldwide, lung cancer studies in sub-Saharan Africa are scarce. Here, we present outputs from a designated lung cancer program in western Kenya, part of the Multi-National Lung Cancer Control Program, which focused on case finding, diagnosis, and treatment.

We retrospectively reviewed patients with pathologically confirmed non-small cell lung cancer (NSCLC) enrolled in this program at Moi Teaching and Referral Hospital from January 2018 to December 2022. Clinical data were analyzed using descriptive statistics, Kaplan-Meier methods, and proportional hazards regression model.

Two hundred forty-nine patients diagnosed with NSCLC were included with a median age at diagnosis of 61 (IQR, 52-70) years. Most patients were married (n = 177; 71%) and nonsmokers (n = 177; 71%) with 58 (23%) having received tuberculosis treatment and 93 (37%) having Eastern Cooperative Oncology Group (ECOG) performance status (PS) of ≥ 2. At diagnosis, adenocarcinoma was the prominent histology (n = 187; 75%) along with clinical stage IV (n = 195; 78% stage IV) or unstaged (n = 40; 16%) disease. Most patients received chemotherapy and radiotherapy (n = 176; 71%) with few palliative care referrals (n = 2; 0.8%). The median overall survival (OS) was only 3.7 months (IQR, 2.7-5.4). ECOG PS (3 or 4) and being unstaged were predictors of poor 1-year OS.

Patients with NSCLC enrolled in this program presented with advanced disease and poor survival. Despite a designated case finding effort, late diagnosis remained common and highlights a need for locally relevant interventions targeting community and provider education as well as innovative diagnostics that can improve early recognition of lung cancer. These interventions must also be paired with access to proven treatments including molecular therapies and palliative care which can extend lung cancer survival.

We report a series of three patients who developed checkpoint inhibitor-related myocarditis with orbital myositis and/or myasthenia gravis overlap syndrome, with varying degrees of severity. In all cases, checkpoint inhibitor therapy was immediately discontinued upon diagnosis and corticosteroids were initiated. While two patients achieved substantial recovery, one patient passed away on hospital day three. These cases underscore the critical need for prompt recognition of adverse events associated with immune checkpoint inhibitors.

The age-related decline in immunity appears to be associated not only with cancer development but also with differential responses to immune checkpoint inhibitors (ICIs). Despite their increasing utility across various malignancies and therapeutic settings, limited data -derived primarily from subgroup analyses of randomized controlled trials (RCTs), pooled meta-analyses, and retrospective studies- are available on the effects of aging on their efficacy and toxicity. Immunosenescence, characterized by the progressive decline of the function of the immune system, and inflammaging, a state of persistent low-grade sterile inflammation, may influence ICI outcomes. Additionally, the incidence, severity, and subtypes of immune-related adverse events (irAEs) may differ between older and younger individuals due to loss of immunotolerance. In the current review, starting from a a comprehensive discussion of the pathophysiology of immunosenescence, we proceed to critically review age-related retrospective and randomized evidence supporting FDA-approved ICIs. We highlight similarities or differences across age groups and the clinical benefit of ICIs in elderly versus younger cancer patients. The optimal integration of ICIs in geriatric oncology necessitates greater inclusion of this patient demographic in RCTs along with real-world data in order to acquire robust data which will guide evidence-based treatment decisions for this population.

Restricted mean survival time (RMST) is gaining attention as a measure to quantify the treatment effect on survival outcomes in randomized clinical trials. Several methods to determine sample size based on the RMST-based tests have been proposed. However, to the best of our knowledge, there is no discussion about the power and sample size regarding the augmented version of RMST-based tests, which utilize baseline covariates for a gain in estimation efficiency and in power for testing no treatment effect. The conventional event-driven study design based on the logrank test allows us to calculate the power for a given hazard ratio without specifying the survival functions. In contrast, the existing sample size determination methods for the RMST-based tests relies on the adequacy of the assumptions of the entire survival curves of two groups. Furthermore, to handle the augmented test, the correlation between the baseline covariates and the martingale residuals must be handled. To address these issues, we propose an approximated sample size formula for the augmented version of the RMST-based test, which does not require specifying the entire survival curve in the treatment group, and also a sample size recalculation approach to update the correlations between the baseline covariates and the martingale residuals with the blinded data. The proposed procedure will enable the studies to have the target power for a given RMST difference even when correct survival functions cannot be specified at the design stage.

Next-generation sequencing in non-small cell lung cancer (NSCLC) identifies somatic genomic variants (SGVs) in cancer susceptibility genes (CSGs). We hypothesized that SGVs would be associated with poorer overall survival (OS) but greater benefit with immune checkpoint inhibitors over chemotherapy. We investigated the prevalence and predictive value of SGVs, using data from OAK and POPLAR trials comparing atezolizumab with docetaxel.

We curated a list of SGVs (excluding TP53, EGFR, ALK, and ROS1) on the basis of CSGs associated with tumorigenesis. We classified participants as SGV mutant or wild-type using baseline plasma analyzed by the FoundationOne Liquid CDx assay. Cox regression analyses and interaction tests between SGV status and treatment were performed.

Of 762 participants, 29% harbored an SGV. The SGV mutant group had worse OS (hazard ratio [HR], 1.28, 95% CI, 1.06 to 1.54), and within each treatment arm (docetaxel: HR, 1.31; atezolizumab: HR, 1.27). In the atezolizumab arm, the SGV mutant group compared with wild-type had worse OS in the PD-L1 high (HR, 1.31 [95% CI, 0.59 to 2.91]) and low (HR, 1.38 [95% CI, 0.98 to 1.93]) subgroups. SGV with missense, splice, and nonsense mutations had significantly worse OS than wild-type in the docetaxel arm (log-rank P = .01) but not in the atezolizumab arm (log-rank P = .33). SGV status did not predict greater OS benefit with atezolizumab over docetaxel (interaction P = .67).

In advanced NSCLC after chemotherapy progression, plasma-detected SGVs are common, and associated with inferior OS. Plasma SGV status should be considered as a stratification factor in future trials.

Although immune checkpoint inhibitors (ICIs) have been successfully utilized in patients with non-small cell lung cancer (NSCLC), EGFR-mutated patients didn't benefit from ICIs. The underlying mechanisms for the poor efficacy of this subgroup remain unclear.

CD8+T cells cytotoxicity, DCs phagocytosis and immunofluorescence assay were applied to examine the immunosuppressive microenvironment of NSCLC. m6A RNA immunoprecipitation, luciferase assay and immunohistochemistry were used to explore the relationship between CD47 and ALKBH5 in EGFR-TKI resistant NSCLC. Autochthonous EGFR-driven lung tumor mouse model and PDXs were performed to explore the therapeutic potential of CD47 antibody and EGFR-TKI combination.

We found that EGFR-TKI resistance promoted a more immunosuppressive tumor microenvironment and inhibited anti-tumor functions of CD8+ T cells. Mechanistically, the m6A eraser ALKBH5 was inhibited in EGFR-TKI resistant NSCLC, which subsequently upregulates CD47 by catalyzing m6A demethylation and causes immunosuppression. Combined treatment with EGFR-TKI and inhibitors of CD47 enhances antitumor immunity and EGFR-TKI efficacy in vivo.

Collectively, our findings reveal the possible underlying mechanism for poor immune response of ICIs in EGFR-TKI resistant NSCLC and provide preclinical evidence that targeted therapy combined with innate immune checkpoint blockade may provide synergistic effects in NSCLC treatment.

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

Predicting response to immunotherapy is crucial for advanced non-small cell lung cancer (NSCLC) treatment planning, but effective predictive markers for immunotherapy efficacy are still lacking. This study aimed to develop an explainable machine learning model for predicting immunotherapy responses in advanced NSCLC patients.

A total of 245 advanced NSCLC patients from two centers who received immunotherapy were retrospectively enrolled. For each primary tumor, three regions of interest were analyzed, namely, the intratumoral region (ITR), peritumoral region (PTR), and combined intratumoral and PTR (IPTR). Pre-radiomics features and delta-radiomics features reflecting the rate of change between radiomics features before and after treatment were extracted. Models for predicting immunotherapy responses were established via the extreme gradient boosting (XGBoost) classifier and assessed in terms of discrimination, calibration, and clinical utility. The SHapley Additive exPlanations (SHAP) tool was employed to explore the interpretability of the model. Kaplan-Meier (KM) analysis of progression-free survival (PFS) was conducted to evaluate the prognostic value of the prediction models.

The delta-radiomics models of ITR and IPTR demonstrated optimal performance in predicting immunotherapy response, significantly improving the area under the curve (AUC) to 0.85 and 0.83 in the internal validation cohort and 0.84 and 0.86 in the external validation cohort. SHAP revealed a strong relationship between the delta-radiomics feature values and the model-predicted probabilities. KM curves indicated that the high-risk groups identified by the delta-radiomics models had significantly worse PFS than did the low-risk groups across all cohorts.

The results demonstrated that a model based on multiple time points outperformed one based on a single time point. The delta-radiomics model has been proved a noninvasive approach for assessing the response of advanced NSCLC patients to immunotherapy and facilitates individualized treatment decision making.

Immune checkpoint inhibitors (ICIs), namely, anti-cytotoxic T lymphocyte-associated protein 4 (CTLA-4) monoclonal antibody Ipilimumab and anti- and programmed cell death 1 (PD-1) monoclonal antibodies Nivolumab, and Pembrolizumab, have improved the treatment outcomes for many other cancer types. However, their impact on fertility remains under-explored.

The possible direct effects of ICIs on human sperm was investigated. Spermatozoa from ten normozoospermic donors were exposed to Ipilimumab, Nivolumab, or Pembrolizumab at concentrations ranging from 1 to 100 ng/mL. Sperm motility was assessed through standard laboratory process. Cell viability and apoptosis markers were evaluated by flow-cytometry using fluorescent Annexin-V probe and Terminal Uridine Nick-End Label (TUNEL) assays. Protein-A-purified therapeutic antibodies (IgG) were also evaluated.

Spermatozoa had high PD-1 (>99%) and negligible CTLA-4 expression. Exposure to ICIs, was associated with a concentration-dependent impairment of sperm motility, noticeable for Pembrolizumab and Ipilimumab since 10 ng/mL, and for Nivolumab since 100 ng/mL. However, no significant effect on cell apoptosis or viability was shown. Purified IgG from ICIs maintained the adverse effect on cell motility without affecting viability.

ICIs, specifically Pembrolizumab, Nivolumab, and Ipilimumab, adversely affect human sperm motility in vitro. Further research is required to understand the underlying mechanisms and clinical implications.

(1) Background: Exploring real-world data (RWD) regarding immune-related adverse events (irAEs) is crucial to better understand the efficacy and safety of immunotherapy in cancer patient populations excluded from clinical trials. An analysis was conducted to evaluate the presumptive predictive causality between endocrine irAEs and the efficacy of immune check-point inhibitors (ICIs) in metastatic non-small-cell lung cancer (mNSCLC) patients treated in daily practice in Romania. (2) Methods: This was a retrospective cohort study of mNSCLC patients treated with ICIs in a tertiary level hospital in Romania for a period of almost seven years, from November 2017 till July 2024. Endocrine irAEs were well defined as any occurring autoimmune endocrinopathy during ICIs and related to immunotherapy. The hospital endocrinologist (M.C.C.O) diagnosed, treated, and followed these endocrine irAEs in a multidisciplinary approach. We investigated multiple medical variables to assess their impact on ICI effectiveness. Descriptive and statistical analyses were performed. (3) Results: Of 487 cancer patients treated with ICIs, we identified 215 mNSCLC patients who were evaluated for endocrine irAEs and co-medications during ICI therapy. Forty-seven (21.8%) patients experienced endocrine irAEs, thyroiditis being the most frequent and prevalent autoimmune endocrinopathy in 60% of cases. Endocrine irAEs were statistically significant, correlated with ICI efficacy (p = 0.002) for survival analysis. Steroids and proton-pump inhibitors used as co-medication during ICIs had a negative impact on response to therapy. (4) Conclusions: Endocrine irAEs might be considered predictive biomarkers for successful immunotherapy in mNSCLC patients. Co-medication during ICIs had a major influence on the effectiveness of these cutting-edge therapies. RWD plays an important role for oncology daily practice whenever clinical trial evidence is not available to guide decision.

Lung cancer remains the leading cause of cancer-related mortality worldwide, with a 5-year survival rate ranging from 10% to 20%. The majority of cases are categorized as non-small cell lung cancer (NSCLC) (80%) and small cell lung cancer (SCLC) (20%), with NSCLC being the more prevalent type. Tobacco use, particularly cigarette smoking, is a significant contributor to over 80% of lung cancer cases. Early diagnosis is challenging due to limitations in screening methods, resulting in many cases being identified only in advanced stages. Moreover, current treatment options often exhibit low efficacy, partly due to an inadequate understanding of the disease's pathogenesis. This narrative review aims to summarize recent discoveries and advancements in lung cancer research, focusing on improvements in diagnosis, treatment, and understanding of the disease.

A comprehensive literature review was performed utilizing the PubMed Central database to identify recent studies relevant to lung cancer. This review synthesizes findings from various research articles to provide a cohesive summary of advancements in the field.

In the past decade, notable progress has been achieved in lung cancer research, particularly concerning diagnostics and treatment strategies. Novel therapeutic approaches, including immunotherapy and genomic-targeted therapies, have demonstrated promising results. Understanding the tumor microenvironment (TME) and the role of T lymphocytes has become crucial for developing effective treatments. Additionally, advancements in immune checkpoint inhibitors (ICIs) have shown potential in enhancing patient outcomes. Improvements in tumor detection technologies are also anticipated to facilitate earlier diagnosis, ultimately contributing to better survival rates.

Significant strides have been made in lung cancer research over the last ten years, particularly in diagnostics and treatment methodologies. Future research should prioritize exploring the TME, the function of T lymphocytes, and the efficacy of ICIs while continuing to innovate in tumor detection technologies. Such efforts are essential for enhancing treatment outcomes and improving the overall quality of life for lung cancer patients.

Immune checkpoint inhibitors (ICIs) have revolutionized the management of advanced non-small cell lung cancer (NSCLC). Emerging evidence suggests a potential association between elevated body mass index (BMI) and enhanced ICI efficacy, yet this relationship remains inconclusive and warrants further investigation. This study aims to evaluate the impact of BMI on treatment efficacy and survival outcomes in advanced NSCLC patients treated with first-line ICI therapy.

A retrospective study was conducted at a multi-center registry to evaluate the impact of baseline BMI on overall survival (OS) and progression-free survival (PFS) in patients with stage IV NSCLC who received first-line ICI therapies. Treatment regimens included pembrolizumab or the combination of ipilimumab and nivolumab, administered either as monotherapy or in combination with chemotherapy, at the oncology department between January 2018 and December 2023. BMI was categorized according to the World Health Organization (WHO) classification, and OS and PFS were evaluated using Kaplan-Meier survival analysis and the Cox proportional hazards regression model.

Among 346 patients, 12.72% were underweight, 45.38% normal weight, 29.19% overweight, and 12.72% obese. Overweight and obese patients were more likely to receive pembrolizumab (p = 0.039) and less likely to undergo chemotherapy (p = 0.012). No significant differences in median overall survival (OS, log-rank: p = 0.155) or progression-free survival (PFS, log-rank: p = 0.370) were observed across BMI categories. However, differences emerged upon further analysis of PD-L1 levels (OS, log-rank: p = 0.029; PFS, log-rank: p = 0.044), additional chemotherapy (OS, log-rank: p = 0.009; PFS, log-rank: p = 0.021), type of immune checkpoint inhibitor (OS, log-rank: p < 0.001; PFS, log-rank: p < 0.001), and histologic diagnosis (OS, log-rank: p = 0.011; PFS, log-rank: p = 0.003).

BMI was not an independent predictor of survival outcomes in advanced NSCLC treated with ICI. Incorporating BMI with other patient-specific factors into personalized immunotherapy strategies highlights the importance of tailored approaches to improve patient care and clinical outcomes.

This study aims to evaluate the prognostic significance of peripheral blood biomarkers in relation to outcomes and immune-related adverse events (irAEs) among patients with stage IV driver gene-negative lung adenocarcinoma receiving treatment with immune checkpoint inhibitors (ICIs).

We conducted a retrospective analysis of clinicopathological data from 102 patients diagnosed with stage IV driver gene-negative lung adenocarcinoma who were treated with ICIs at the Fourth Hospital of Hebei Medical University between January 1, 2019, and December 31, 2023. We employed the Kaplan-Meier method to perform a univariate analysis of progression-free survival (PFS) and overall survival (OS), generated survival curves, and assessed differences in survival between groups using the log-rank test. The Cox regression model was utilized for multivariate analysis of PFS and OS. Additionally, we assessed the predictive value of peripheral blood markers for irAEs using logistic regression models.

The 1-, 3-, and 5-year PFS rates for the cohort of 102 patients were recorded at 35.3%, 3.9%, and 0%, respectively; similarly, the OS rates at these time points were observed to be 66.7%, 8.8%, and 2.9%. Multivariate analysis identified that the prognostic nutritional index (PNI) and metastatic status served as independent prognostic factors influencing PFS outcomes in this patient population; furthermore, D-dimer levels, PNI, metastatic status, and the occurrence of irAEs emerged as independent prognostic indicators impacting OS rates among patients. Subsequent logistic regression analysis revealed that both platelet-to-lymphocyte ratio (PLR) and lymphocyte-to-monocyte ratio (LMR) functioned as independent predictors of irAEs with statistical significance (P=0.032; P=0.02).

For patients with stage IV driver gene-negative lung adenocarcinoma undergoing ICI therapy, PNI and metastatic status can serve as initial predictors of PFS. Additionally, D-dimer levels, PNI, metastatic status, and the presence of irAEs can initially predict OS, aiding in the identification of populations that may benefit from ICI therapy in clinical practice. Furthermore, our findings indicate a need for heightened attention to PLR and LMR concerning the occurrence of irAEs.

Cutaneous immune-related adverse events (cirAEs) represent a prevalent manifestation of adverse reactions linked to immune checkpoint inhibitors (ICIs) therapy, substantially affecting patients' quality of life. This systematic review and meta-analysis aimed to quantify the pooled incidence of cirAEs in this population and strengthen clinical awareness for early recognition and management.

A comprehensive search of PubMed, Embase, CINAHL, Cochrane Library, CBM, CNKI, and Wanfang databases was conducted from inception to December 2022. Literature that reported the incidence of cirAEs in patients with lung cancer receiving ICIs therapy was included. A meta-analysis was conducted using R software, version 4.4.1 to estimate the pooled incidence of cirAEs, and a random-effects model was used for data synthesis. Begg's rank correlation and funnel plots were used to assess publication bias.

A total of 99 articles involving 23,814 patients with lung cancer receiving ICIs therapy were included, with publication dates ranging from 2012 to 2022. The meta-analysis results reveal that the incidence of cirAEs in patients with lung cancer was 20.26% (95% confidence interval [CI (17.12-23.81)]. Significant differences were observed between all subgroups, including continent, study type, combination therapy, dual ICIs therapy, and diagnostic criteria for cirAEs for Grade 1-2 and Grade 3-4 incidences.

The incidence of cirAEs in patients with lung cancer is relatively high, particularly undergoing combined or dual ICIs therapy. To comprehensively characterize cirAEs in patients with lung cancer, large-scale multicenter studies integrating real-world pharmacovigilance data are warranted to establish precise incidence estimates and identify clinically significant risk factors.

This review's insights aroused clinical staff's attention and concern about cirAEs, potentially enhancing the quality of life of patients with cancer.

The benefit of programmed cell death protein-1 (PD-1)/programmed cell death protein ligand-1 (PD-L1) inhibitors remains unclear in non-small cell lung cancer (NSCLC) patients with poor performance status (PS). In the current multi-centre retrospective cohort study, advanced or recurrent NSCLC patients treated with PD-1/PD-L1 inhibitors were enrolled. Of the 219 patients enrolled, 44 had PS 2-4. The objective response rate (ORR) of patients with PS 2-4 in 1st line was 33%. Among 1st line group, median progression-free survival (PFS) in patients with PS 2 was significantly longer compared to that in patients with PS 3-4 (15.3 months vs. 0.9 months, P = 0.039, Log-rank test). Among previously treated patients, the ORR of patients with PS 2-4 was only 4%, and PFS and overall survival was poor even in patients with PS 2. PD-1/PD-L1 inhibitors can be an option for PS 2 NSCLC patients in 1st line setting.

Background: The prognosis for lung adenocarcinoma (LUAD) is poor, and the recurrence rate is high. Thus, to evaluate patients' prognoses and direct therapy choices, new prognostic markers are desperately needed. Methods: First, gene modules associated with LUAD were identified by weighted gene coexpression network analysis (WGCNA) analysis. The expression profiles obtained were intersected with the differential expressed genes taken between LUAD samples and paracancerous samples. Afterward, stepwise regression analysis and the LASSO were used to compress the genes further, and a risk model was created. Furthermore, a nomogram based on risk scores and clinical features was created to validate the model. After that, the distinctions between the pertinent biological processes and signaling pathways among the various subgroups were investigated. Additionally, drug sensitivity testing, immunotherapy, immune infiltration analysis, and enrichment analysis were carried out. Finally, the biological role of ANLN in LUAD was explored by qPCR, cell scratch assay, and transwell. Results: A total of 257 intersected genes were obtained by taking the intersection of the differential genes between 2866 LUAD samples and paraneoplastic samples with the module genes after we screened two particular modules that had the strongest link with LUAD by WGCNA. ANLN, CASS4, and NMUR1 were found to be distinctive genes for the development of risk models after the intersecting genes were screened to find 176 genes linked to the prognosis for LUAD. Based on risk assessments, high- and low-risk groups of LUAD patients were divided. Low-risk patients exhibited a significantly higher overall survival (OS) than those in the high-risk group. Expression of model genes correlates with infiltration of the vast majority of immune cells. Significant differences in the biological pathways, immune microenvironment, and abundance of immune cell infiltration were found between the two groups. The drug sensitivity study showed that patients in the high-risk group had higher IC50 values for BMS-754807_2171 and Doramapimod_10424. Finally, in vitro experiments demonstrated that knocking down ANLN noticeably inhibited the viability, migration, and invasion of A549 cells. Conclusion: This study may provide a theoretical reference for future exploration of potential diagnostic and prognostic biomarkers for LUAD.

Anti-PD-(L)1 treatment is standard for non-small cell lung cancer (NSCLC), but patients show variable responses to the same regimen. The tumor immune microenvironment (TIME) is associated with immunotherapy response, yet the heterogeneous underlying therapeutic outcomes remain underexplored. We applied single-cell RNA and TCR sequencing (scRNA/TCR-seq) to analyze surgical tumor samples from 234 NSCLC patients post-neoadjuvant chemo-immunotherapy. Analyses revealed five distinct TIME subtypes with varying major pathological response (MPR) rates. MPR patients had elevated levels of FGFBP2+ NK/NK-like T cells, memory B cells, or effector T cells, while non-MPR patients showed higher CCR8+ Tregs. T cell clonal expansion analyses unveiled heterogeneity in non-MPR patients, marked by varying expansions of Tex-relevant cells and CCR8+ Tregs. Precursor exhausted T cells (Texp cells) correlated with recurrence-free survival, identifying a patient subgroup with reduced recurrence risk despite lack of MPR. Our study dissects TIME heterogeneity in response to chemoimmunotherapy, offering insights for NSCLC management.

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

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

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

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