Recurrence after surgery in patients with NSCLC

Prognostic Impact and Clinical Features of Spread through Air Spaces in Operated Lung Cancer: Real-World Analysis

Background and Objectives: Lung cancer is the leading cause of cancer-related deaths. Spread through air spaces (STAS) is an adverse prognostic factor that has become increasingly known in recent years. This study aims to investigate the impact of STAS presence on overall survival (OS) and disease-free survival (DFS) in patients with surgically resected stage IA-IIIA lung cancer and to identify clinicopathological features associated with STAS. Materials and Methods: This research involved 311 lung cancer surgery patients. The relationship between the presence of STAS in the patients' surgical pathology and OS and DFS values was examined. Clinicopathological features associated with the presence of STAS were determined. Results: There were 103 (33%) STAS-positive patients. Adenocarcinoma histological subtype, perineural invasion (PNI), and lymphovascular invasion (LVI) were significantly correlated with being STAS positive. STAS significantly predicted DFS and OS. One-year and five-year DFS rates were significantly lower in the STAS-positive group compared to the STAS-negative group (65% vs. 88%, 29% vs. 62%, respectively, p ≤ 0.001). Similarly, one-year and five-year OS rates were significantly lower in the STAS-positive group compared to the STAS-negative group (92% vs. 94%, 54% vs. 88%, respectively, p ≤ 0.001). In multivariate analysis, STAS was found to be an independent prognostic factor for both DFS and OS (HR: 3.2 (95%CI: 2.1-4.8) and 3.1 (95%CI: 1.7-5.5), p < 0.001 and <0.001, respectively). Conclusions: In our study, STAS was found to be an independent prognostic biomarker in operated stage IA-IIIA lung cancer patients. It may be a beneficial pathological biomarker in predicting the survival of patients and managing their treatments.

Circulating cell-free and extracellular vesicles-derived microRNA as prognostic biomarkers in patients with early-stage NSCLC: results from RESTING study

BACKGROUND

Factors to accurately stratify patients with early-stage non-small cell lung cancer (NSCLC) in different prognostic groups are still needed. This study aims to investigate 1) the prognostic potential of circulating cell-free (CF) and extracellular vesicles (EVs)-derived microRNA (miRNAs), and 2) their added value with respect to known prognostic factors (PFs).

METHODS

The RESTING study is a multicentre prospective observational cohort study on resected stage IA-IIIA patients with NSCLC. The primary end-point was disease-free survival (DFS), and the main analyses were carried out separately for CF- and EV-miRNAs. CF- and EV-miRNAs were isolated from plasma, and miRNA-specific libraries were prepared and sequenced. To reach the study aims, three statistical models were specified: one using the miRNA data only (Model 1); one using both miRNAs and known PFs (age, gender, and pathological stage) (Model 2), and one using the PFs alone (Model 3). Five-fold cross-validation (CV) was used to assess the predictive performance of each. Standard Cox regression and elastic net regularized Cox regression were used.

RESULTS

A total of 222 patients were enrolled. The median follow-up time was 26.3 (95% CI 25.4-27.6) months. From Model 1, three CF-miRNAs and 21 EV-miRNAs were associated with DFS. In Model 2, two CF-miRNAs (miR-29c-3p and miR-877-3p) and five EV-miRNAs (miR-181a-2-3p, miR-182-5p, miR-192-5p, miR-532-3p and miR-589-5p) remained associated with DFS. From pathway enrichment analysis, TGF-beta and NOTCH were the most involved pathways.

CONCLUSION

This study identified promising prognostic CF- and EV-miRNAs that could be used as a non-invasive, cost-effective tool to aid clinical decision-making. However, further evaluation of the obtained miRNAs in an external cohort of patients is warranted.

Nrf2-Mediated Antioxidant Response and Drug Efflux Transporters Upregulation as Possible Mechanisms of Resistance in Photodynamic Therapy of Cancers

Photodynamic therapy (PDT) is a groundbreaking approach involving the induction of cytotoxic reactive oxygen species (ROS) within tumors through visible light activation of photosensitizers (PS) in the presence of molecular oxygen. This innovative therapy has demonstrated success in treating various cancers. While PDT proves highly effective in most solid tumors, there are indications that certain cancers exhibit resistance, and some initially responsive cancers may develop intrinsic or acquired resistance to PDT. The molecular mechanisms underlying this resistance are not fully understood. Recent evidence suggests that, akin to other traditional cancer treatments, the activation of survival pathways, such as the KEAP1/Nrf2 signaling pathway, is emerging as an important mechanism of post-PDT resistance in many cancers. This article explores the dual role of Nrf2, highlighting evidence linking aberrant Nrf2 expression to treatment resistance across a range of cancers. Additionally, it delves into the specific role of Nrf2 in the context of photodynamic therapy for cancers, emphasizing evidence that suggests Nrf2-mediated upregulation of antioxidant responses and induction of drug efflux transporters are potential mechanisms of resistance to PDT in diverse cancer types. Therefore, understanding the specific role(s) of Nrf2 in PDT resistance may pave the way for the development of more effective cancer treatments using PDT.

Non-Small Cell Lung Cancer Imaging Using a Phospholipase A2 Activatable Fluorophore

Lung cancer, the most common cause of cancer-related death in the United States, requires advanced intraoperative detection methods to improve evaluation of surgical margins. In this study we employed DDAO-arachidonate (DDAO-A), a phospholipase A2 (PLA2) activatable fluorophore, designed for the specific optical identification of lung cancers in real-time during surgery. The in vitro fluorescence activation of DDAO-A by porcine sPLA2 was tested in various liposomal formulations, with 100 nm extruded EggPC showing the best overall characteristics. Extruded EggPC liposomes containing DDAO-A were tested for their stability under various storage conditions, demonstrating excellent stability for up to 4 weeks when stored at -20 °C or below. Cell studies using KLN 205 and LLC1 lung cancer cell lines showed DDAO-A activation was proportional to cell number. DDAO-A showed preferential activation by human recombinant cPLA2, an isoform highly specific to arachidonic acid-containing lipids, when compared to a control probe, DDAO palmitate (DDAO-P). In vivo studies with DBA/2 mice bearing KLN 205 lung tumors recapitulated these results, with preferential activation of DDAO-A relative to DDAO-P following intratumoral injection. Topical application of DDAO-A-containing liposomes to human (n = 10) and canine (n = 3) lung cancers ex vivo demonstrated the preferential activation of DDAO-A in tumor tissue relative to adjacent normal lung tissue, with fluorescent tumor-to-normal ratios (TNR) of up to 5.2:1. The combined results highlight DDAO-A as a promising candidate for clinical applications, showcasing its potential utility in intraoperative and back-table imaging and topical administration during lung cancer surgeries. By addressing the challenge of residual microscopic disease at resection margins and offering stability in liposomal formulations, DDAO-A emerges as a potentially valuable tool for advancing precision lung cancer surgery and improving curative resection rates.

Deep learning in pulmonary nodule detection and segmentation: a systematic review

OBJECTIVES

The accurate detection and precise segmentation of lung nodules on computed tomography are key prerequisites for early diagnosis and appropriate treatment of lung cancer. This study was designed to compare detection and segmentation methods for pulmonary nodules using deep-learning techniques to fill methodological gaps and biases in the existing literature.

METHODS

This study utilized a systematic review with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, searching PubMed, Embase, Web of Science Core Collection, and the Cochrane Library databases up to May 10, 2023. The Quality Assessment of Diagnostic Accuracy Studies 2 criteria was used to assess the risk of bias and was adjusted with the Checklist for Artificial Intelligence in Medical Imaging. The study analyzed and extracted model performance, data sources, and task-focus information.

RESULTS

After screening, we included nine studies meeting our inclusion criteria. These studies were published between 2019 and 2023 and predominantly used public datasets, with the Lung Image Database Consortium Image Collection and Image Database Resource Initiative and Lung Nodule Analysis 2016 being the most common. The studies focused on detection, segmentation, and other tasks, primarily utilizing Convolutional Neural Networks for model development. Performance evaluation covered multiple metrics, including sensitivity and the Dice coefficient.

CONCLUSIONS

This study highlights the potential power of deep learning in lung nodule detection and segmentation. It underscores the importance of standardized data processing, code and data sharing, the value of external test datasets, and the need to balance model complexity and efficiency in future research.

CLINICAL RELEVANCE STATEMENT

Deep learning demonstrates significant promise in autonomously detecting and segmenting pulmonary nodules. Future research should address methodological shortcomings and variability to enhance its clinical utility.

KEY POINTS

Deep learning shows potential in the detection and segmentation of pulmonary nodules. There are methodological gaps and biases present in the existing literature. Factors such as external validation and transparency affect the clinical application.

Comparative Efficacy of Neoadjuvant Nivolumab Plus Chemotherapy versus Conventional Comparator Treatments in Resectable Non-Small-Cell Lung Cancer: A Systematic Literature Review and Network Meta-Analysis

BACKGROUND

This study aimed to estimate the relative efficacy of neoadjuvant nivolumab in combination with chemotherapy (neoNIVO + CT) compared to relevant treatments amongst resectable non-metastatic non-small-cell lung cancer (rNSCLC) patients.

METHODS

Treatment comparisons were based on a network meta-analysis (NMA) using randomized clinical trial data identified via systematic literature review (SLR). The outcomes of interest were event-free survival (EFS) and pathological complete response (pCR). NeoNIVO + CT was compared to neoadjuvant chemotherapy (neoCT), neoadjuvant chemoradiotherapy (neoCRT), adjuvant chemotherapy (adjCT), and surgery alone (S). Due to the potential for effect modification by stage, all-stage and stage-specific networks were considered. Fixed-effect (FE) and random-effects Bayesian NMA models were run (EFS = hazard ratios [HR]; pCR = odds ratios [OR]; 95% credible intervals [CrI]).

RESULTS

Sixty-one RCTs were identified (base case = 9 RCTs [n = 1978 patients]). In the all-stages FE model, neoNIVO + CT had statistically significant EFS improvements relative to neoCT (HR = 0.68 [95% CrI: 0.49, 0.94]), S (0.59 [0.42, 0.82]), adjCT (0.66 [0.45, 0.96]), but not relative to neoCRT (HR = 0.77 [0.52, 1.16]). NeoNIVO + CT (5 RCTs) had statistically significant higher odds of pCR relative to neoCT (OR = 12.53 [5.60, 33.82]) and neoCRT (7.15 [2.31, 24.34]). Stage-specific model findings were consistent.

CONCLUSIONS

This NMA signals improved EFS and/or pCR of neoNIVO + CT relative to comparators among patients with rNSCLC.

Prognostic significance of immunotherapy in postoperative recurrent non-small cell lung cancer without EGFR mutations or ALK rearrangements

Background

Limited reports exist regarding postoperative recurrent non-small cell lung cancer (NSCLC) without major driver mutations [epidermal growth factor receptor (EGFR) mutations or anaplastic lymphoma kinase (ALK) rearrangements] treated with immune checkpoint inhibitors (ICIs) when programmed cell death ligand 1 (PD-L1) is expressed in a real-world setting. The aim of this study was to evaluate the effect of ICIs for those NSCLC.

Methods

We enrolled 255 patients with postoperative recurrent NSCLC lacking EGFR mutations or ALK rearrangements who underwent lobectomy or more extensive resection between 2012 and 2021. Factors associated with post-recurrence survival (PRS) were determined using the Cox proportional hazards model. PRS was analyzed using Kaplan-Meier curves and compared using the log-rank test.

Results

Multivariable analysis demonstrated that squamous cell carcinoma, pathological stage III, and an Eastern Cooperative Oncology Group (ECOG) performance status ≥2 were significantly associated with worse PRS. Conversely, ICI use at first line was associated with improved PRS. Patients who used ICIs during the first line and subsequent therapies had better PRS than those who received chemotherapy alone. Among patients who used ICIs, there was no significant difference in response rate at the first line, nor in PRS among those with PD-L1 expression ≥50%, 1-49%, and <1% in surgically resected specimens.

Conclusions

ICI use at any treatment line improved the PRS of NSCLC patients without major driver mutations, irrespective of PD-L1 expression, in a real-world setting.

The genomic landscape of the immune system in lung cancer: present insights and continuing investigations

Lung cancer is one of the most prevalent malignancies worldwide, contributing to over a million cancer-related deaths annually. Despite extensive research investigating the genetic factors associated with lung cancer susceptibility and prognosis, few studies have explored genetic predispositions regarding the immune system. This review discusses the most recent genomic findings related to the susceptibility to or protection against lung cancer, patient survival, and therapeutic responses. The results demonstrated the effect of immunogenetic variations in immune system-related genes associated with innate and adaptive immune responses, cytokine, and chemokine secretions, and signaling pathways. These genetic diversities may affect the crosstalk between tumor and immune cells within the tumor microenvironment, influencing cancer progression, invasion, and prognosis. Given the considerable variability in the individual immunegenomics profiles, future studies should prioritize large-scale analyses to identify potential genetic variations associated with lung cancer using highthroughput technologies across different populations. This approach will provide further information for predicting response to targeted therapy and promotes the development of new measures for individualized cancer treatment.

In-vitro study of cytotoxic and apoptotic potential of Thalassia hemprichii (Ehren.) Asch. And Enhalus acoroides (L.f.) Royle against human breast cancer cell line (MCF-7) with correlation to their chemical profile

BACKGROUND

Breast cancer is the most common type of cancer diagnosed in women. Finding novel therapeutic agents with significant cytotoxic action and minimal adverse impact on normal cells becomes crucial. Today, natural anticancer agents present an unconventional method of treating cancer, either as a curative or preventative agent, with considerable concern for marine organisms.

METHODS

The anticancer effect of the alcoholic extract of different Red Sea Seagrasses on MCF-7 human breast cancer cell line has been investigated. Seagrasses were collected from Wadi El Gamal, Red Sea and extracted. Qualitative HPLC analysis was performed on the extracts for the identification of their active biomarkers. This study was aimed to explore the cytotoxic impact of Thalassia hemprichii (Ehren.) and Enhalus acoroides (L.f.) Royle on MCF-7 and their mode of action. Their anti-proliferative effects on cancer cells were performed using Neutral red assay. On the other hand, their apoptotic effect and their capacity to induce cell cycle arrest were investigated by flow cytometry assay. The effect of Seagrasses on the mitochondrial membrane potential (ΔψM) was studied by using JC-1 mitochondrial membrane potential assay kit in Seagrasses treated cancer cells to Δψ Caspases 3/7activity was examined using the colorimetric method. Gene expression analysis and quantitative real time RT-PCR for the sea grasses on MCF-7 was performed. Immune-blotting technique for Bcl-2 and p53 was investigated.

RESULTS

HPLC analysis demonstrated that the extracts contained mainly flavonoids and polyphenols such as Caffeic acid, Chlorogenic acids, catechin and kaempferol that might be responsible for these anticancer effects. Seagrasses alcoholic crude extract markedly suppressed the growth and expansion of MCF-7 cells concentration-dependently with no toxicity against normal human skin fibroblast HSF. Thalassia hemprichii and Enhalus acoroides trigger mode of cell death primarily via apoptosis as confirmed by the flow cytometry. Additionally, they have ability to induce G0/S cell cycle arrest in MCF-7. The data showed the depletion in mitochondrial membrane potential (ΔψM) in the treated cells dose-dependently Caspases 3/7activities markedly increased following 24 h treatment. Finally, Gene expression analysis showed a marked reduction in Bcl-2, Survivin and CDC2 gene expression levels and a significant increase in the expression of p53 and CC2D1A as compared to control cells.

CONCLUSION

In summary, the Methanolic extract of seagrass, Thalassia hemperchii and Enhalus ocoroides are able to induce concentration-dependent cytotoxic effects in human MCF-7 cells through intrinsic pathway of apoptosis in MCF-7 cells. This study reveals the beneficial importance of sea grasses as a source of anticancer agents. Further in vivo study is recommended for the active isolated biomolecules.

Predictive model based on multiple immunofluorescence quantitative analysis for pathological complete response to neoadjuvant immunochemotherapy in lung squamous cell carcinoma

Objective

This study aims to establish a prediction model for neoadjuvant immunochemotherapy (NICT) in lung squamous cell carcinoma to guide clinical treatment.

Methods

This retrospective study included 50 patients diagnosed with lung squamous cell carcinoma who received NICT. The patients were divided into the pathological complete response (PCR) group and the non-PCR group. HE staining and multiple immunofluorescence (mIF) techniques were utilized to analyze the differences in the immune microenvironment between these groups. LASSO regression and optimal subset regression were employed to identify the most significant variables and construct a prediction model.

Results

The PCR group showed higher densities of lymphocyte nuclei and karyorrhexis based on HE staining. Furthermore, based on mIF analysis, the PCR group showed higher cell densities of CD8+, PD-L1+, and CD8+PD-L1+ in the tumor region, while showing lower cell densities of CD3+Foxp3+, Foxp3+, and CD163+. Logistic univariate analysis revealed CD8+PD-L1+, PD-L1+, CD8+, CD4+LAG-3+, lymphocyte nuclei, and karyorrhexis as significant factors influencing PCR. By using diverse screening methods, the three most relevant variables (CD8+, PD-L1+, and CD8+PD-L1+ in the tumor region) were selected to establish the prediction model. The model exhibited excellent performance in both the training set (AUC=0.965) and the validation set (AUC=0.786). In the validation set, In comparison to the conventional TPS scoring criteria, the model attained superior accuracy (0.85), specificity(0.67), and sensitivity (0.92).

Conclusion

NICT treatment might induce anti-tumor effects by enriching immune cells and reactivating exhausted T cells. CD8+, PD-L1+, and CD8+PD-L1+ cell abundances within the tumor region have been closely associated with therapeutic efficacy. Incorporating these three variables into a predictive model allows accurate forecasting of treatment outcomes and provides a reliable basis for selecting NICT treatment strategies.

The significance of regular chest computed tomography in postoperative surveillance for surgically resected non-small cell lung cancer based on TNM 8th staging system

OBJECTIVES

Although several societies recommend regular chest computed tomography (CT) scans for the surveillance of surgically resected non-small cell lung cancer (NSCLC), there is paucity of evidence to support these statements. This study aimed to clarify whether regular CT scans improved the prognosis of patients with surgically resected NSCLC based on TNM 8th classification.

METHODS

Patients with pathologic Stage 0-III NSCLC who underwent complete surgical resection other than sublobar resection procedures were enrolled in the study. For these patients, clinicopathological data and postoperative surveillance data were collected by the retrospective review of medical records. Patients were categorized into the chest X-ray (CXR) group or the CT group according to whether they were followed-up with basic examinations including CXR or basic examinations plus regular chest CT. Postoperative overall survival was compared between the two groups.

RESULTS

Six hundred sixty five patients were categorized into the CXR (n = 245) and CT (n = 420) groups. The clinicopathological backgrounds did not differ to a statistically significant extent. Recurrence was seen in 68 (27.3%) patients in the CXR group and 117 (27.8%) patients in the CT group. The 5-year overall survival rates of the two groups did not differ to a statistically significant extent (CXR, 76.5%; CT, 78.3%, P = 0.22).

CONCLUSION

Regular chest CT scans may not improve the prognosis of surgically resected NSCLC. Further study is warranted to precisely evaluate the benefit of CT-based postoperative surveillance of NSCLC.

Clinical factors and major pathological response after neoadjuvant chemoimmunotherapy in potentially resectable lung squamous cell carcinoma

Objective

Major pathological response (MPR) helps evaluate the prognosis of patients with lung squamous cell carcinoma (LUSC). However, the clinical factors that affect the achievement of MPR after neoadjuvant chemoimmunotherapy (NCIO) in patients with LUSC remain unclear. This study aimed to explore the clinical factors affecting the MPR after NCIO in patients with potentially resectable LUSC.

Methods

This retrospective study included patients with stage IIB-IIIC LUSC who underwent surgical resection after receiving NCIO at a center between March 2020 and November 2022. In addition to the postoperative pathological remission rate, sex, age, body mass index (BMI), smoking history, TNM stage, hematological and imaging test results, and other indicators were examined before NCIO. According to the pathological response rate of the surgically removed tumor tissue, the patients were split into MPR and non-MPR groups.

Results

In total, 91 LUSC patients who met the study's eligibility criteria were enrolled: 32 (35%) patients in the non-MPR group and 59 (65%) in the MPR group, which included 43 cases of pathological complete remission (pCR). Pre-treatment lymphocyte level (LY) (odds ratio [OR] =5.997), tumor burden (OR=0.958), N classification (OR=15.915), radiographic response (OR=11.590), pulmonary atelectasis (OR=5.413), and PD-L1 expression (OR=1.028) were independently associated with MPR (all P < 0.05). Based on these six independent predictors, we developed a nomogram model of prediction having an area under the curve (AUC) of 0.914 that is simple to apply clinically to predict the MPR. The MPR group showed greater disease-free survival (DFS) than the non-MPR group, according to the survival analysis (P < 0.001).

Conclusion

The MPR rate of NCIO for potentially resectable LUSC was 65%. LY, tumor burden, N classification, radiographic response, pulmonary atelectasis, and PD-L1 expression in patients with LUSC before NCIO were the independent and ideal predictors of MPR. The developed nomogram demonstrated a good degree of accuracy and resilience in predicting the MPR following NCIO, indicating that it is a useful tool for assuring customized therapy for patients with possibly resectable LUSC.

GRAS1 non-coding RNA protects against DNA damage and cell death by binding and stabilizing NKAP

Non-coding RNA (ncRNA) gene products are involved in diverse biological processes including splicing, epigenetic regulation, gene expression, proliferation, and metabolism. The biological mechanisms by which ncRNAs contribute to cell survival remain poorly understood. We found that the Growth Regulator Antisense 1 (GRAS1) long non-coding RNA (lncRNA) transcript promotes growth in multiple human cell types by protecting against DNA damage. Knockdown of GRAS1 induced DNA damage and cell death, along with significant expression changes in DNA damage response, intrinsic apoptotic signaling, and cellular response to environmental stimulus genes. Extensive DNA damage occurred after GRAS1 knockdown, with numerous double strand breaks occurring in each cell. The number of cells undergoing apoptosis and with fragmented nuclei increased significantly after GRAS1 knockdown. We used RNA antisense purification and mass spectrometry (RAP-MS) to identify the NF-κB activating protein (NKAP) as a direct protein interaction partner of GRAS1 lncRNA. NKAP protein was degraded after GRAS1 knockdown, in a proteasome-dependent manner. Overexpression of GRAS1 or NKAP mitigated the DNA damage effects of GRAS1 knockdown. In summary, GRAS1 and NKAP directly interact to protect against DNA damage and cell death in multiple human cell lines.

Advances in lymphatic metastasis of non-small cell lung cancer

Lung cancer is a deeply malignant tumor with high incidence and mortality. Despite the rapid development of diagnosis and treatment technology, abundant patients with lung cancer are still inevitably faced with recurrence and metastasis, contributing to death. Lymphatic metastasis is the first step of distant metastasis and an important prognostic indicator of non-small cell lung cancer. Tumor-induced lymphangiogenesis is involved in the construction of the tumor microenvironment, except promoting malignant proliferation and metastasis of tumor cells, it also plays a crucial role in individual response to treatment, especially immunotherapy. Thus, this article reviews the current research status of lymphatic metastasis in non-small cell lung cancer, in order to provide some insights for the basic research and clinical and translational application in this field.

Postoperative ctDNA in indicating the recurrence risk and monitoring the effect of adjuvant therapy in surgical non-small cell lung cancer

BACKGROUND

Circulating tumor DNA (ctDNA) has emerged as a potential novel biomarker to predict molecular residual disease (MRD) in lung cancer after definitive treatment. Herein, we investigated the value of ctDNA in prognosing risk of relapse and monitoring the effect of adjuvant therapy in surgical non-small cell lung cancer (NSCLC).

METHODS

We enrolled 58 NSCLC patients in a real-world setting, and 58 tumor tissues and 325 plasma samples were analyzed. Tumor tissues and plasma samples were subjected to targeted next-generation sequencing (NGS) of 1021 cancer-related and ultra-deep targeted NGS covering 338 genes, respectively.

RESULTS

ctDNA was detected in 31.0% of cases at the first postoperative time, which was associated with advanced tumor stage, T stage and KEAP1 or GRIN2A mutations in tissues. ctDNA positivity at landmark and longitudinal indicated the shorter disease-free survival. For patients with ctDNA positivity at the first postoperative time, regardless of adjuvant therapy, all patients who were persistently ctDNA positive during postoperative surveillance had disease recurrence. Among the patients who were ctDNA negative, only two patients (15.4%, 2/13) receiving adjuvant therapy relapsed, while one patient (50.0%, 1/2) without adjuvant therapy relapsed. For the first postoperative ctDNA negative patients, the recurrence rate of patients with adjuvant therapy was and higher than without adjuvant therapy (22.6% [7/31] vs. 11.1% [1/9]). The patients who became ctDNA positive may also benefit from intervention therapy.

CONCLUSION

Postoperative ctDNA is a prognostic marker, and ctDNA-detection may facilitate personalized adjuvant therapy, and applying adjuvant therapy to the patients with detectable ctDNA could bring clinical benefits for them.

Osimertinib in the treatment of resected EGFR-mutated non-small cell lung cancer: a cost-effectiveness analysis in the United States

Background: In the double-blind phase III ADAURA randomized clinical trial, adjuvant osimertinib showed a substantial overall survival benefit in patients with stage IB to IIIA, EGFR-mutated, completely resected non-small cell lung cancer (NSCLC). We conduct a cost-effectiveness analysis comparing the use of adjuvant osimertinib to placebo in patients with stage IB to IIIA, EGFR-mutated, resected NSCLC. Methods: Based on the results obtained from the ADAURA trial, a Markov model with three-state was employed to simulate patients who were administered either osimertinib or placebo until disease recurrence or completion of the study period (3 years). Quality-adjusted life-years (QALYs), lifetime costs, and incremental cost-effectiveness ratio (ICER) were calculated with a willingness-to-pay (WTP) threshold of $150,000 per QALY. Both univariate and probabilistic sensitivity analyses were carried out to explore the robustness of the model. Results: Osimertinib produced additional 1.59 QALYs with additional costs of $492,710 compared to placebo, giving rise to ICERs of $309,962.66/QALY. The results of the univariate sensitivity analysis indicated that the utility of disease-free survival (DFS), cost of osimertinib, and discount rate had the greatest impact on the outcomes. Probabilistic sensitivity analysis showed that osimertinib exhibited a 0% chance of being considered cost-effective for patients using a WTP threshold $150,000/QALY. Conclusion: In our model, osimertinib was unlikely to be cost-effective compared to placebo for stage IB to IIIA, EGFR-mutated, completely resected NSCLC patients from the perspective of a U.S. payer at a WTP threshold of $150,000 per QALY.

Beneficial implications of adjuvant chemotherapy for stage IB lung adenocarcinoma exhibiting elevated SUVmax in FDG-PET/CT: a retrospective study from a single center

Background

Controversy surrounds the efficacy of adjuvant chemotherapy (ACT) in the treatment of stage I lung adenocarcinoma (LUAD). The objective of this study was to examine the impact of the maximum standardized uptake value (SUVmax) as measured by 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) on the efficacy of ACT in patients diagnosed with stage I LUAD.

Methods

We scrutinized the medical records of 928 consecutive patients who underwent complete surgical resection for pathological stage I LUAD at our institution. The ideal cut-off value for primary tumor SUVmax in terms of disease-free survival (DFS) and overall survival (OS) was determined using the X-tile software. The Kaplan-Meier method and Cox regression analysis were used for survival analysis.

Results

Based on the SUVmax algorithm, the ideal cutoff values were determined to be 4.9 for DFS and 5.0 for OS. We selected 5.0 as the threshold because OS is the more widely accepted predictive endpoint. In a multivariate Cox regression analysis, SUVmax ≥ 5.0, problematic IB stage, and sublobectomy were identified as independent risk factors for poor DFS and OS. It is noteworthy that patients who were administered ACT had significantly longer DFS and OS than what was observed in the subgroup of patients with pathological stage IB LUAD and SUVmax ≥ 5.0 (p < 0.035 and p ≤ 0.046, respectively). However, there was no observed survival advantage for patients in stages IA or IB who had an SUVmax < 5.0.

Conclusion

The preoperative SUVmax of tumors served as an indicator of the impact of ACT in the context of completely resected pathological stage I LUAD. Notably, patients within the Stage IB category exhibiting elevated SUVmax levels emerged as a subgroup experiencing substantial benefits from postoperative ACT.

A novel neoadjuvant therapy for early-stage non-small cell lung cancer in a mouse model

Background

Lung cancer is the common malignancy with high mortality rate in the world. Even with curative resection for early-stage lung cancer patients, the rate of postoperative recurrence and metastasis is still high. Neoadjuvant nivolumab combined with chemotherapy leads to improved pathological complete response rate and event-free survival in resectable non-small cell lung cancer (NSCLC) patients. However, the neoadjuvant therapy is not only accompanied by grade 3 or above adverse events which resulting in the potential missing out on the window for curative surgery for the patients, but also has low efficacy especially in patients with low programmed death ligand 1 (PD-L1) expression. Hence, it is particularly important to explore innovative ways to inhibit tumour recurrence and metastasis.

Methods

In the present study, we investigated whether neoadjuvant therapy with intralesional Rose Bengal (RB) elicited specific immune responses compared with control group, and then the lung cancer mouse model was used to evaluated the immunological mechanism.

Results

The secondary Lewis lung cancer cells (LLCs) tumour growth was significantly suppressed by RB intralesional injection into subcutaneous tumour; the formation rate of secondary tumours induced by the B16 melanoma cell injection was 100%. Intralesional RB neoadjuvant therapy before surgical resection exhibited effectively enhanced T central memory cells (Tcm) and T memory stem cells (Tscm) + naïve T cells (Tn) infiltration, elicited stronger cytotoxic T lymphocyte (CTL) responses against LLCs, and displayed markedly higher proportions of splenic lymphocytes that produce tumour necrosis factor-alpha (TNF-α) and interferon-gamma (IFN-γ) upon restimulation in a lung cancer mouse model.

Conclusions

Based on our preclinical data, neoadjuvant therapy with intralesional RB injection generated immune memory and prevented the recurrence and metastasis of tumour in a lung cancer mouse model, which provides a new strategy for neoadjuvant treatment of early-stage NSCLC.

IL6-STAT3-C/EBPβ-IL6 positive feedback loop in tumor-associated macrophages promotes the EMT and metastasis of lung adenocarcinoma

BACKGROUND

Lung cancer is one of the most common tumors in the world, and metastasis is one of the major causes of tumor-related death in lung cancer patients. Tumor-associated macrophages (TAMs) are a major component of the tumor microenvironment (TME) and are frequently associated with tumor metastasis in human cancers. However, the regulatory mechanisms of TAMs in lung cancer metastasis remain unclear.

METHODS

Single-cell sequencing analysis of lung cancer and normal tissues from public databases and from 14 patients who underwent surgery at Zhongshan Hospital was performed. In vitro co-culture experiments were performed to evaluate the effects of TAMs on lung cancer migration and invasion. Changes in the expression of IL-6, STAT3, C/EBPΒ, and EMT pathway were verified using RT-qPCR, western blotting, and immunofluorescence. Dual luciferase reporter assays and ChIP were used to reveal potential regulatory sites on the transcription factor sets. In addition, the effects of TAMs on lung cancer progression and metastasis were confirmed by in vivo models.

RESULTS

TAM infiltration is associated with tumor progression and poor prognosis. IL-6 secreted by TAMs can activate the JAK2/STAT3 pathway through autocrine secretion, and STAT3 acts as a transcription factor to activate the expression of C/EBPβ, which further promotes the transcription and expression of IL-6, forming positive feedback loops for IL6-STAT3-C/EBPβ-IL6 in TAMs. IL-6 secreted by TAMs promotes lung cancer progression and metastasis in vivo and in vitro by activating the EMT pathway, which can be attenuated by the use of JAK2/STAT3 pathway inhibitors or IL-6 monoclonal antibodies.

CONCLUSIONS

Our data suggest that TAMs promote IL-6 expression by forming an IL6-STAT3-C/EBPβ-IL6 positive feedback loop. Released IL-6 can induce the EMT pathway in lung cancer to enhance migration, invasion, and metastasis. The use of IL-6-neutralizing antibody can partially counteract the promotion of LUAD by TAMs. A novel mechanism of macrophage-promoted tumor progression was revealed, and the IL6-STAT3-C/EBPβ-IL6 signaling cascade may be a potential therapeutic target against lung cancer.

Molecular alterations and clinical prognostic factors in resectable non-small cell lung cancer

BACKGROUND

EGFR inhibitor and immunotherapy have been approved for adjuvant treatment in resectable non-small cell lung cancer (NSCLC). Limited reports of molecular and clinical characteristics as prognostic factors in NSCLC have been published.

METHODS

Medical records of patients with resectable NSCLC stage I-III diagnosed during 2015-2020 were reviewed. Real time-PCR (RT-PCR) was performed for EGFR mutations (EGFRm). Immunohistochemistry staining was conducted for ALK and PD-L1 expression. Categorical variables were compared using chi-square test and Fisher's exact test. Survival analysis was done by cox-regression method.

RESULTS

Total 441 patients were included. The prevalence of EGFRm, ALK fusion, and PD-L1 expression were 57.8%, 1.9%, and 20.5% (SP263), respectively. The most common EGFRm were Del19 (43%) and L858R (41%). There was no significant difference of recurrence free survival (RFS) by EGFRm status whereas patients with PD-L1 expression (PD-L1 positive patients) had lower RFS compared to without PD-L1 expression (PD-L1 negative patients) (HR = 1.75, P = 0.036). Patients with both EGFRm and PD-L1 expression had worse RFS compared with EGFRm and PD-L1 negative patients (HR = 3.38, P = 0.001). Multivariable analysis showed higher CEA at cut-off 3.8 ng/ml, pT4, pN2, pStage II, and margin were significant poor prognostic factors for RFS in the overall population, which was similar to EGFRm population (exception of pT and pStage). Only pStage was a significant poor prognostic factor for PD-L1 positive patients. The predictive score for predicting of recurrence were 6 for all population (63% sensitivity and 86% specificity) and 5 for EGFRm population (62% sensitivity and 93% specificity).

CONCLUSION

The prevalence and types of EGFRm were similar between early stage and advanced stage NSCLC. While lower prevalence of PD-L1 expression was found in early stage disease. Patients with both EGFRm and PD-L1 expression had poorer outcome. Thus PD-L1 expression would be one of the prognostic factor in EGFRm patients. Validation of the predictive score should be performed in a larger cohort.

Identification of potential regulatory mechanisms and therapeutic targets for lung cancer

Lung cancer poses a significant health threat globally, especially in regions like India, with 5-year survival rates remain alarmingly low. Our study aimed to uncover key markers for effective treatment and early detection. We identified specific genes related to lung cancer using the BioXpress database and delved into their roles through DAVID enrichment analysis. By employing network theory, we explored the intricate interactions within lung cancer networks, identifying ASPM and MKI67 as crucial regulator genes. Predictions of microRNA and transcription factor interactions provided additional insights. Examining gene expression patterns using GEPIA and KM Plotter revealed the clinical relevance of these key genes. In our pursuit of targeted therapies, Drug Bank pointed to methotrexate as a potential drug for the identified key regulator genes. Confirming this, molecular docking studies through Swiss Dock showed promising binding interactions. To ensure stability, we conducted molecular dynamics simulations using the AMBER 16 suite. In summary, our study pinpoints ASPM and MKI67 as vital regulators in lung cancer networks. The identification of hub genes and functional pathways enhances our understanding of molecular processes, offering potential therapeutic targets. Importantly, methotrexate emerged as a promising drug candidate, supported by robust docking and simulation studies. These findings lay a solid foundation for further experimental validations and hold promise for advancing personalized therapeutic strategies in lung cancer.Communicated by Ramaswamy H. Sarma.

Evaluating clinical and radiomic features for predicting lung cancer recurrence pre- and post-tumor resection

Among patients with early-stage non-small cell lung cancer (NSCLC) undergoing surgical resection, identifying who is at high-risk of recurrence can inform clinical guidelines with respect to more aggressive follow-up and/or adjuvant therapy. While predicting recurrence based on pre-surgical resection data is ideal, clinically important pathological features are only evaluated postoperatively. Therefore, we developed two supervised classification models to assess the importance of pre- and post-surgical features for predicting 5-year recurrence. An integrated dataset was generated by combining clinical covariates and radiomic features calculated from pre-surgical computed tomography images. After removing correlated radiomic features, the SHapley Additive exPlanations (SHAP) method was used to measure feature importance and select relevant features. Binary classification was performed using a Support Vector Machine, followed by a feature ablation study assessing the impact of radiomic and clinical features. We demonstrate that the post-surgical model significantly outperforms the pre-surgical model in predicting lung cancer recurrence, with tumor pathological features and peritumoral radiomic features contributing significantly to the model's performance.

Neoadjuvant nivolumab plus chemotherapy in resectable non-small-cell lung cancer in Japanese patients from CheckMate 816

In the open-label, phase III CheckMate 816 study (NCT02998528), neoadjuvant nivolumab plus chemotherapy demonstrated statistically significant improvements in event-free survival (EFS) and pathological complete response (pCR) versus chemotherapy alone in patients with resectable non-small-cell lung cancer (NSCLC). Here we report efficacy and safety outcomes in the Japanese subpopulation. Patients with stage IB-IIIA, resectable NSCLC were randomized 1:1 to nivolumab plus chemotherapy or chemotherapy alone for three cycles before undergoing definitive surgery within 6 weeks of completing neoadjuvant treatment. The primary end-points (EFS and pCR) and safety were assessed in patients enrolled at 16 centers in Japan. Of the Japanese patients randomized, 93.9% (31/33) in the nivolumab plus chemotherapy arm and 82.9% (29/35) in the chemotherapy arm underwent surgery. At 21.5 months' minimum follow-up, median EFS was 30.6 months (95% confidence interval [CI], 16.8-not reached [NR]) with nivolumab plus chemotherapy versus 19.6 months (95% CI, 8.5-NR) with chemotherapy; hazard ratio, 0.60 (95% CI, 0.30-1.24). The pCR rate was 30.3% (95% CI, 15.6-48.7) versus 5.7% (95% CI, 0.7-19.2), respectively; odds ratio, 7.17 (95% CI, 1.44-35.85). Grade 3/4 treatment-related adverse events were reported in 59.4% versus 42.9% of patients, respectively, with no new safety signals identified. Neoadjuvant nivolumab plus chemotherapy resulted in longer EFS and a higher pCR rate versus chemotherapy alone in Japanese patients, consistent with findings in the global population. These data support nivolumab plus chemotherapy as a neoadjuvant treatment option in Japanese patients with resectable NSCLC.

iCluF: an unsupervised iterative cluster-fusion method for patient stratification using multiomics data

Motivation

Patient stratification is crucial for the effective treatment or management of heterogeneous diseases, including cancers. Multiomic technologies facilitate molecular characterization of human diseases; however, the complexity of data warrants the need for the development of robust data integration tools for patient stratification using machine-learning approaches.

Results

iCluF iteratively integrates three types of multiomic data (mRNA, miRNA, and DNA methylation) using pairwise patient similarity matrices built from each omic data. The intermediate omic-specific neighborhood matrices implement iterative matrix fusion and message passing among the similarity matrices to derive a final integrated matrix representing all the omics profiles of a patient, which is used to further cluster patients into subtypes. iCluF outperforms other methods with significant differences in the survival profiles of 8581 patients belonging to 30 different cancers in TCGA. iCluF also predicted the four intrinsic subtypes of Breast Invasive Carcinomas with adjusted rand index and Fowlkes-Mallows scores of 0.72 and 0.83, respectively. The Gini importance score showed that methylation features were the primary decisive players, followed by mRNA and miRNA to identify disease subtypes. iCluF can be applied to stratify patients with any disease containing multiomic datasets.

Availability and implementation

Source code and datasets are available at https://github.com/GudaLab/iCluF_core.

Impact of chronic obstructive pulmonary disease on the efficacy and safety of neoadjuvant immune checkpoint inhibitors combined with chemotherapy for resectable non-small cell lung cancer: a retrospective cohort study

BACKGROUND

Neoadjuvant immune checkpoint inhibitors(ICIs) combined with chemotherapy can improve non-small cell lung cancer(NSCLC) patients' pathological responses and show promising improvements in survival. Chronic obstructive pulmonary disease (COPD) is a systemic inflammatory disease, and its associated abnormal inflammatory response affects not only the immunotherapy efficacy but also immune-related adverse events. It remains unclear whether NSCLC patients with COPD can benefit from neoadjuvant ICIs combined with chemotherapy.

METHODS

A retrospective observational clinical study was conducted on 105 consecutive NSCLC patients receiving neoadjuvant ICIs combined with chemotherapy at the Department of Thoracic Surgery of Tianjin Chest Hospital between April 2020 and April 2023.

RESULTS

A total of 74 NSCLC patients were included in the study, including 30 patients with COPD and 44 patients without COPD. The percentage of patients with a pathological complete response (PCR) was higher in the COPD group than in the non-COPD group (43.3% vs. 20.5%, P = 0.042). Multivariate logistic regression analysis of factors associated with PCR showed that the adjusted odds ratio (OR) was statistically significant for presence of COPD (OR = 3.020, 95%CI: 1.042-8.757; P = 0.042). Major pathological response (66.7% vs. 50%, P = 0.155), R0 resection rate (96.7% vs.93.2%, P = 0.642), N2 lymph node downstaging(92.3% vs. 66.7%, P = 0.182) and objective response rate (70% vs. 63.6%, P = 0.57) were not significantly different between the groups. Progression-free survival(PFS) was not reached in the COPD group and 17 months (95%CI: 12.1-21.9) in the non-COPD group, with statistically significance (χ2 = 6.247, P = 0.012). Multivariate Cox's regression analysis showed that the adjusted hazard ratio (HRadj) was statistically significant for presence of COPD (HRadj = 0.321, 95%CI: 0.111-0.930; P = 0.036). The grade 3 and grade 4 adverse events in the COPD group were leukopenia (3.3%, 6.7%), neutropenia (3.3%, 6.7%), fatigue (6.7%, 0%), gastrointestinal reactions (3.3%, 0%), and hypothyroidism (3.3%, 0%). In the non-COPD group, the corresponding adverse events were leukopenia (6.8%, 6.8%), neutropenia (3.3%, 6.8%), fatigue (2.3%, 0%), gastrointestinal reactions (2.3%, 0%), and hypothyroidism (2.3%, 0%), respectively.

CONCLUSIONS

The present study indicates that the presence of COPD may improve PCR, prolong PFS, and have an acceptable safety profile in NSCLC patients receiving neoadjuvant ICIs combined with chemotherapy.

Targeting HER3 to overcome EGFR TKI resistance in NSCLC

Receptor tyrosine kinases (RTKs) play a crucial role in cellular signaling and oncogenic progression. Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR TKIs) have become the standard treatment for advanced non-small cell lung cancer (NSCLC) patients with EGFR-sensitizing mutations, but resistance frequently emerges between 10 to 14 months. A significant factor in this resistance is the role of human EGFR 3 (HER3), an EGFR family member. Despite its significance, effective targeting of HER3 is still developing. This review aims to bridge this gap by deeply examining HER3's pivotal contribution to EGFR TKI resistance and spotlighting emerging HER3-centered therapeutic avenues, including monoclonal antibodies (mAbs), TKIs, and antibody-drug conjugates (ADCs). Preliminary results indicate combining HER3-specific treatments with EGFR TKIs enhances antitumor effects, leading to an increased objective response rate (ORR) and prolonged overall survival (OS) in resistant cases. Embracing HER3-targeting therapies represents a transformative approach against EGFR TKI resistance and emphasizes the importance of further research to optimize patient stratification and understand resistance mechanisms.

Cancer cell cycle heterogeneity as a critical determinant of therapeutic resistance

Intra-tumor heterogeneity is now arguably one of the most-studied topics in tumor biology, as it represents a major obstacle to effective cancer treatment. Since tumor cells are highly diverse at genetic, epigenetic, and phenotypic levels, intra-tumor heterogeneity can be assumed as an important contributing factor to the nullification of chemotherapeutic effects, and recurrence of the tumor. Based on the role of heterogeneous subpopulations of cancer cells with varying cell-cycle dynamics and behavior during cancer progression and treatment; herein, we aim to establish a comprehensive definition for adaptation of neoplastic cells against therapy. We discuss two parallel and yet distinct subpopulations of tumor cells that play pivotal roles in reducing the effects of chemotherapy: "resistant" and "tolerant" populations. Furthermore, this review also highlights the impact of the quiescent phase of the cell cycle as a survival mechanism for cancer cells. Beyond understanding the mechanisms underlying the quiescence, it provides an insightful perspective on cancer stem cells (CSCs) and their dual and intertwined functions based on their cell cycle state in response to treatment. Moreover, CSCs, epithelial-mesenchymal transformed cells, circulating tumor cells (CTCs), and disseminated tumor cells (DTCs), which are mostly in a quiescent state of the cell cycle are proved to have multiple biological links and can be implicated in our viewpoint of cell cycle heterogeneity in tumors. Overall, increasing our knowledge of cell cycle heterogeneity is a key to identifying new therapeutic solutions, and this emerging concept may provide us with new opportunities to prevent the dreadful cancer recurrence.

Tumor Organoids: The Era of Personalized Medicine

The strategies of future medicine are aimed to modernize and integrate quality approaches including early molecular-genetic profiling, identification of new therapeutic targets and adapting design for clinical trials, personalized drug screening (PDS) to help predict and individualize patient treatment regimens. In the past decade, organoid models have emerged as an innovative in vitro platform with the potential to realize the concept of patient-centered medicine. Organoids are spatially restricted three-dimensional clusters of cells ex vivo that self-organize into complex functional structures through genetically programmed determination, which is crucial for reconstructing the architecture of the primary tissue and organs. Currently, there are several strategies to create three-dimensional (3D) tumor systems using (i) surgically resected patient tissue (PDTOs, patient-derived tumor organoids) or (ii) single tumor cells circulating in the patient's blood. Successful application of 3D tumor models obtained by co-culturing autologous tumor organoids (PDTOs) and peripheral blood lymphocytes have been demonstrated in a number of studies. Such models simulate a 3D tumor architecture in vivo and contain all cell types characteristic of this tissue, including immune system cells and stem cells. Components of the tumor microenvironment, such as fibroblasts and immune system cells, affect tumor growth and its drug resistance. In this review, we analyzed the evolution of tumor models from two-dimensional (2D) cell cultures and laboratory animals to 3D tissue-specific tumor organoids, their significance in identifying mechanisms of antitumor response and drug resistance, and use of these models in drug screening and development of precision methods in cancer treatment.

Overcoming challenges in cancer treatment: Nano-enabled photodynamic therapy as a viable solution

Cancer presents a formidable challenge, necessitating innovative therapies that maximize effectiveness while minimizing harm to healthy tissues. Nanotechnology has emerged as a transformative force in cancer treatment, particularly through nano-enabled photodynamic therapy (NE-PDT), which leverages precise and targeted interventions. NE-PDT capitalizes on photosensitizers activated by light to generate reactive oxygen species (ROS) that initiate apoptotic pathways in cancer cells. Nanoparticle enhancements optimize this process, improving drug delivery, selectivity, and ROS production within tumors. This review dissects NE-PDT's mechanistic framework, showcasing its potential to harness apoptosis as a potent tool in cancer therapy. Furthermore, the review explores the synergy between NE-PDT and complementary treatments like chemotherapy, immunotherapy, and targeted therapies, highlighting the potential to amplify apoptotic responses, enhance immune recognition of cancer cells, and inhibit resistance mechanisms. Preclinical and clinical advancements in NE-PDT demonstrate its efficacy across various cancer types. Challenges in translating NE-PDT into clinical practice are also addressed, emphasizing the need for optimizing nanoparticle design, refining dosimetry, and ensuring long-term safety. Ultimately, NE-PDT represents a promising approach in cancer therapy, utilizing the intricate mechanisms of apoptosis to address therapeutic hurdles. The review underscores the importance of understanding the interplay between nanoparticles, ROS generation, and apoptotic pathways, contributing to a deeper comprehension of cancer biology and novel therapeutic strategies. As interdisciplinary collaborations continue to thrive, NE-PDT offers hope for effective and targeted cancer interventions, where apoptosis manipulation becomes central to conquering cancer. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

Multi-omics identification of GPCR gene features in lung adenocarcinoma based on multiple machine learning combinations

Background: Lung adenocarcinoma is a common malignant tumor that ranks second in the world and has a high mortality rate. G protein-coupled receptors (GPCRs) have been reported to play an important role in cancer; however, G protein-coupled receptor-associated features have not been adequately investigated. Methods: In this study, GPCR-related genes were screened at single-cell and bulk transcriptome levels based on AUcell, single-sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network (WGCNA) analysis. And a new machine learning framework containing 10 machine learning algorithms and their multiple combinations was used to construct a consensus G protein-coupled receptor-related signature (GPCRRS). GPCRRS was validated in the training set and external validation set. We constructed GPCRRS-integrated nomogram clinical prognosis prediction tools. Multi-omics analyses included genomics, single-cell transcriptomics, and bulk transcriptomics to gain a more comprehensive understanding of prognostic features. We assessed the response of risk subgroups to immunotherapy and screened for personalized drugs targeting specific risk subgroups. Finally, the expression of key GPCRRS genes was verified by RT-qPCR. Results: In this study, we identified 10 GPCR-associated genes that were significantly associated with the prognosis of lung adenocarcinoma by single-cell transcriptome and bulk transcriptome. Univariate and multivariate showed that the survival rate was higher in low risk than in high risk, which also suggested that the model was an independent prognostic factor for LUAD. In addition, we observed significant differences in biological function, mutational landscape, and immune cell infiltration in the tumor microenvironment between high and low risk groups. Notably, immunotherapy was also relevant in the high and low risk groups. In addition, potential drugs targeting specific risk subgroups were identified. Conclusion: In this study, we constructed and validated a lung adenocarcinoma G protein-coupled receptor-related signature, which has an important role in predicting the prognosis of lung adenocarcinoma and the effect of immunotherapy. It is hypothesized that LDHA, GPX3 and DOCK4 are new potential targets for lung adenocarcinoma, which can achieve breakthroughs in prognosis prediction, targeted prevention and treatment of lung adenocarcinoma and provide important guidance for anti-tumor.

Dual peptides-modified cationic liposomes for enhanced Lung cancer gene therapy by a gap junction regulating strategy

BACKGROUND

Gene therapy for lung cancer has emerged as a novel tumor-combating strategy for its superior tumor specificity, low systematical toxicity and huge clinical translation potential. Especially, the applications of microRNA shed led on effective tumor ablation by directly interfering with the crucial gene expression, making it one of the most promising gene therapy agents. However, for lung cancer therapy, the microRNA treatment confronted three bottlenecks, the poor tumor tissue penetration effect, the insufficient lung drug accumulation and unsatisfied gene transfection efficiency. To address these issues, an inhalable RGD-TAT dual peptides-modified cationic liposomes loaded with microRNA miR-34a and gap junction (GJ) regulation agent all-trans retinoic acid (ATRA) was proposed, which was further engineered into dry powder inhalers (DPIs).

RESULTS

Equipped with a rough particle surface and appropriate aerodynamic size, the proposed RGD-TAT-CLPs/ARTA@miR-34a DPIs were expected to deposit into the deep lung and reach lung tumor lesions guided by targeting peptide RGD. Assisted by cellular transmembrane peptides TAT, the RGD-TAT-CLPs/ARTA@miR-34a was proven to be effectively internalized by cancer cells, enhancing gene transfection efficiency. Then, the GJ between tumor cells was upregulated by ARTA, facilitating the intercellular transport of miR-34a and boosting the gene expression in the deep tumor.

CONCLUSION

Overall, the proposed RGD-TAT-CLPs/ARTA@miR-34a DPIs could enhance tumor tissue penetration, elevate lung drug accumulation and boost gene transfection efficiency, breaking the three bottlenecks to enhancing tumor elimination in vitro and in vivo. We believe that the proposed RGD-TAT-CLPs/ARTA@miR-34a DPIs could serve as a promising pulmonary gene delivery platform for multiple lung local disease treatments.

Conditional survival analysis of patients with resected non-small cell lung cancer

Background

Conditional survival (CS) analyses provide an estimate of survival accounting for years already survived after treatment. We aim to evaluate the difference between actuarial and conditional survival in patients following lung resection for non-small cell lung cancer (NSCLC). In addition, CS analyses are used to examine whether prognosticators of survival change over time following surgery.

Methods

Patients who underwent anatomic lung resection at a single institution for pathologic stage I-IIIA NSCLC between 2010 and 2021 were identified; those who underwent wedge resection for node-negative tumors ≤2 cm were also included. CS estimates were calculated as the probability of remaining disease-free after x years of nonrecurrence (CSx). Kaplan-Meier, log-rank, and Cox proportional hazard methods for examining CS were used for subgroup comparisons and assessing associations with baseline covariates.

Results

Overall, 863 patients met the study inclusion criteria, with a median follow-up of 44.1 months. Conditional overall survival (OS) and disease-free survival (DFS) were greater than actuarial rates at all time points after surgery. At the time of resection, male sex (hazard ratio [HR], 1.33; 95% confidence interval [CI], 1.03 to 1.72; P = .032), tumor size >3 cm (HR, 1.17; 95% CI, 1.11-1.23; P < .001), node positivity (HR, 3.31; 95% CI, 2.52-4.33; P < .001), and American Joint Committee on Cancer stage (P < .001) were associated with DFS. However, if a patient lived 3 years without recurrence (CS3), these factors were no longer prognostic of DFS.

Conclusions

Conditional survival analyses provide dynamic assessments of OS and DFS after NSCLC resection. After 3 years without recurrence, certain characteristics associated with DFS at the time of surgery no longer prognosticate recurrence.

Peripheral blood inflammatory biomarkers dynamics reflect treatment response and predict prognosis in non-small cell lung cancer patients with neoadjuvant immunotherapy

Neoadjuvant immunotherapy has significantly changed the therapeutic approach for treating patients with surgically resectable non-small cell lung cancer (NSCLC). Here, peripheral blood inflammation-based biomarkers as well as previously less focused eosinophil fraction, modified Glasgow prognostic score (mGPS), and prognostic nutritional index (PNI) were systematically included to comprehensively analyze their potential in predicting neoadjuvant immunotherapy efficacy and prognosis. We enrolled 189 patients (94 in training and 95 in validation cohorts) with stage I-III B surgically resectable NSCLC treated with neoadjuvant immunotherapy from the National Cancer Center of China. Baseline and post-treatment eosinophils fraction, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), monocyte-to-lymphocyte ratio (MLR), PNI, mGPS, and their changes were calculated and analyzed for correlation with neoadjuvant immunotherapy efficacy and prognosis. In patients in the major pathological response (MPR) group, the post-treatment eosinophil fraction was significantly high, and NLR, PLR, SII, and MLR were significantly lower compared to the non-MPR group in both the training and validation cohorts. The receiver operating characteristic curve showed that post-treatment, eosinophil fraction and SII and their changing were two of the most important factors. Univariate and multivariate logistic regression analyses showed that post-treatment eosinophil fraction, SII, mGPS, and ΔSII could independently predict MPR in patients treated with neoadjuvant immunotherapy. Survival analysis showed a significant correlation between high post-treatment NLR, PLR, SII, mGPS, and their changes in ΔNLR and ΔSII elevation with poor overall survival and event-free survival of patients. Our results suggest that inflammatory biomarkers could predict the patient's response to neoadjuvant immunotherapy and prognosis.

Efficacy, safety, and survival of neoadjuvant immunochemotherapy in operable non-small cell lung cancer: a systematic review and meta-analysis

Background

Neoadjuvant immunochemotherapy may benefit patients with non-small cell lung cancer (NSCLC), but its impact requires further investigation.

Methods

A meta-analysis was conducted. PubMed, Embase, Web of Science, and the Cochrane Library were searched. The study was registered in PROSPERO (registration no. CRD42022360893).

Results

60 studies of 3,632 patients were included. Comparing with neoadjuvant chemotherapy, neoadjuvant immunochemotherapy showed higher pCR (RR: 4.71, 95% CI: 3.69, 6.02), MPR (RR, 3.20, 95% CI: 2.75, 3.74), and ORR (RR, 1.46, 95% CI: 1.21, 1.77), fewer surgical complications (RR: 0.67, 95%CI: 0.48, 0.94), higher R0 resection rate (RR: 1.06, 95%CI: 1.03, 1.10, I2 = 52%), and longer 1-year and 2-year OS, without affecting TRAEs. For neoadjuvant immunochemotherapy in NSCLC, the pooled pCR rate was 0.35 (95% CI: 0.31, 0.39), MPR was 0.59 (95% CI: 0.54, 0.63), and ORR was 0.71 (95% CI: 0.66, 0.76). The pooled incidence of all grade TRAEs was 0.70 (95% CI: 0.60, 0.81), and that of >= grade 3 TRAEs was 0.24 (95% CI: 0.16, 0.32). The surgical complications rate was 0.13 (95% CI: 0.07, 0.18) and R0 resection rate was 0.98 (95% CI: 0.96, 0.99). The pooled 1-year OS was 0.97 (95%CI: 0.96, 0.99), and 2-year OS was 0.89 (95%CI: 0.83, 0.94). Patients with squamous cell carcinoma, stage III or higher PD-L1 performed better. Notably, no significant differences were observed in pCR, MPR, and ORR between 2 or more treatment cycles. Pembrolizumab-, or toripalimab-based neoadjuvant immunochemotherapy demonstrated superior efficacy and tolerable toxicity.

Conclusion

According to our analysis, reliable efficacy, safety, and survival of neoadjuvant immunochemotherapy for operable NSCLC were demonstrated.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022360893, identifier CRD42022360893.

Comparative Efficacy and Safety of Neoadjuvant Immunotherapy with Chemotherapy versus Chemotherapy Alone in Non-Small Cell Lung Cancer: A Propensity Score and Inverse Probability Treatment Weighting Analysis

Purpose

This study aimed to compare the efficacy and safety of neoadjuvant chemotherapy (NCT) and neoadjuvant immunotherapy combined with chemotherapy (NICT) combined with radical lung cancer resection for the treatment of patients with resectable non-small cell lung cancer (NSCLC). To adjust for confounding factors, we innovatively adopted two matching methods: propensity score (PS) and inverse probability of treatment weighting (IPTW).

Patients and Methods

We conducted a retrospective analysis of the clinicopathological features and prognosis of patients with resectable NSCLC treated with NCT or NICT combined with radical lung cancer resection using propensity score matching (PSM) at a ratio of 1:1 and IPTW to balance potential bias.

Results

After PSM, 116 pairs of patients who had undergone NCT or NICT were selected for the final analysis. The pathological complete remission (pCR) and major pathological remission (MPR) rates were significantly better in the NICT group than in the NCT group (pCR rate of 44.8% vs 2.6%, P< 0.001; MPR rate of 66.4% vs 20.7%, P< 0.001). No significant difference was seen between the NICT and NCT groups in terms of postoperative complications (12.1% vs 9.5%, P=0.182). Patients in the NICT group had significantly better disease-free survival (DFS) and overall survival(OS) than those in the NCT group ([3-year DFS: 75.2% vs 43.3%, P< 0.001] and [3-year OS: 91.5% vs 58.0%, P< 0.001]). Among all patients, those with postoperative pathology of pCR had better DFS (P< 0.001) and OS (P= 0.009). Patients with postoperative pathology of MPR had better DFS (P< 0.001) and OS (P< 0.001). The IPTW method yielded similar pathologic and prognostic results.

Conclusion

Patients with resectable NSCLC treated with NICT had better pathological responses and prognosis, than those treated with NCT, and the safety profiles of NICT and NCT were similar.

Frailty, Illness Perception and Lung Functional Exercise Adherence in Lung Cancer Patients After Thoracoscopic Surgery

Background

Lung cancer patients will have lung damage after surgery, need rehabilitation exercise. Common-sense model has shown the impact of patients' perception of illness on health behaviors. However, for patients with lung cancer after thoracoscopic surgery, there has been no relevant exploration of disease perception.

Objective

The purpose of this study was to investigate the clinical status of patients with lung cancer patients who have undergone thoracoscopic surgery, and to explore the correlation between frailty, disease perception, and lung functional exercise compliance.

Methods

The cross-sectional study included 218 patients with lung cancer after thoracoscopic surgery. We collected participants' frailty, disease perception, exercise adherence, and relevant clinical information. T-test, Chi-square, Linear regression, Pearson's correlation, and mediation analysis were used for statistical analysis of patient data.

Results

We analyzed the data by disease perception with high and low median scores and found significant differences in lymphatic dissection, stool within three days, pain, thoracic drainage tube placement time. Linear regression results show that, after controlling for confounding factors, frailty and disease perception were significantly associated with pulmonary function exercise compliance. The higher the frailty score, the worse the compliance, and the higher the disease perception negative score, the less exercise. Illness perception played a partially mediating role in the association between frailty and lung functional exercise adherence.

Conclusion

Frailty and disease perception have an impact on exercise adherence, therefore, we need to consider these factors in the intervention to improve exercise compliance after thoracoscopic surgery for lung cancer.

Regulation and therapeutic potentials of microRNAs to non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, accounting for 80%-85% of total cases and leading to millions of deaths worldwide. Drug resistance is the primary cause of treatment failure in NSCLC, which urges scientists to develop advanced approaches for NSCLC treatment. Among novel approaches, the miRNA-based method has emerged as a potential approach as it allows researchers to modulate target gene expression. Subsequently, cell behaviors are altered, which leads to the death and the depletion of cancer cells. It has been reported that miRNAs possess the capacity to regulate multiple genes that are involved in various signaling pathways, including the phosphoinositide 3-kinase, receptor tyrosine kinase/rat sarcoma virus/mitogen-activated protein kinase, wingless/integrated, retinoblastoma, p53, transforming growth factor β, and nuclear factor-kappa B pathways. Dysregulation of these signaling pathways in NSCLC results in abnormal cell proliferation, tissue invasion, and drug resistance while inhibiting apoptosis. Thus, understanding the roles of miRNAs in regulating these signaling pathways may enable the development of novel NSCLC treatment therapies. However, a comprehensive review of potential miRNAs in NSCLC treatment has been lacking. Therefore, this review aims to fill the gap by summarizing the up-to-date information on miRNAs regarding their targets, impact on cancer-associated pathways, and prospective outcomes in treating NSCLC. We also discuss current technologies for delivering miRNAs to the target cells, including virus-based, non-viral, and emerging extracellular vesicle-based delivery systems. This knowledge will support future studies to develop an innovative miRNA-based therapy and select a suitable carrier to treat NSCLC effectively.

Recurrence prediction of lung adenocarcinoma using an immune gene expression and clinical data trained and validated support vector machine classifier

Background

Immune microenvironment plays a critical role in cancer from onset to relapse. Machine learning (ML) algorithm can facilitate the analysis of lab and clinical data to predict lung cancer recurrence. Prompt detection and intervention are crucial for long-term survival in lung cancer relapse. Our study aimed to evaluate the clinical and genomic prognosticators for lung cancer recurrence by comparing the predictive accuracy of four ML models.

Methods

A total of 41 early-stage lung cancer patients who underwent surgery between June 2007 and October 2014 at New York University Langone Medical Center were included (with recurrence, n=16; without recurrence, n=25). All patients had tumor tissue and buffy coat collected at the time of resection. The CIBERSORT algorithm quantified tumor-infiltrating immune cells (TIICs). Protein-protein interaction (PPI) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to unearth potential molecular drivers of tumor progression. The data was split into training (75%) and validation sets (25%). Ensemble linear kernel support vector machine (SVM) ML models were developed using optimized clinical and genomic features to predict tumor recurrence.

Results

Activated natural killer (NK) cells, M0 macrophages, and M1 macrophages showed a positive correlation with progression. Conversely, T CD4+ memory resting cells were negatively correlated. In the PPI network, TNF and IL6 emerged as prominent hub genes. Prediction models integrating clinicopathological prognostic factors, tumor gene expression (45 genes), and buffy coat gene expression (47 genes) yielded varying receiver operating characteristic (ROC)-area under the curves (AUCs): 62.7%, 65.4%, and 59.7% in the training set, 58.3%, 83.3%, and 75.0% in the validation set, respectively. Notably, merging gene expression with clinical data in a linear SVM model led to a significant accuracy boost, with an AUC of 92.0% in training and 91.7% in validation.

Conclusions

Using ML algorithm, immune gene expression data from tumor tissue and buffy coat may enhance the precision of lung cancer recurrence prediction.

Real-world outcomes of immunotherapy-based neoadjuvant therapy in resectable non-small cell lung cancer

Objectives

Recent clinical studies have demonstrated that immunotherapy-based neoadjuvant therapy have promising effectiveness for patients with resectable non-small cell lung cancer (NSCLC) in terms of pathologic response. Therefore, we performed this study to investigate whether immunotherapy-based neoadjuvant therapy is effective and safe for patients with resectable NSCLC.

Materials and methods

This open-label observational two-arm clinical study was performed at Shanghai Chest Hospital in China with patients who had resectable NSCLC and received two to three cycles of immunotherapy-based neoadjuvant therapy or neoadjuvant chemotherapy alone, followed by surgical resection. The primary endpoint was a major pathologic response (MPR). The secondary endpoints include a complete pathological response (pCR), a radiologic response to neoadjuvant therapy (TRR), event-free survival (EFS), and overall survival (OS).

Results

A total of 51 patients was included in this clinical study, of which 31 patients received immunotherapy-based neoadjuvant therapy and 20 patients received neoadjuvant chemotherapy alone. The percentage of patients achieving a major pathologic response was 41.9% with immunotherapy-based neoadjuvant therapy and 15.0% (95% CI, 0.008 to 0.468; P = 0.043) with neoadjuvant chemotherapy alone. The percentage of patients with pathologic complete response was 19.4% in the immunotherapy-based group and 5% (95% CI, -0.069 to 0.318; P = 0.223) in the chemotherapy group. The radiographic response rate was 71% after immunotherapy-based neoadjuvant therapy and 60% (95% CI, -0.143 to 0.359; P = 0.417) after neoadjuvant chemotherapy. At a median follow-up of 28 months, the median EFS and OS endpoints were not reached.

Conclusions

Neoadjuvant immunotherapy offers a considerable advantage over chemotherapy alone for resectable NSCLC in terms of the major pathologic response. Moreover, it did not enhance the risk of adverse events or hinder surgical resection.

A comparison of mutation and amplification-driven resistance mechanisms and their impacts on tumor recurrence

Tumor recurrence, driven by the evolution of drug resistance is a major barrier to therapeutic success in cancer. Tumor drug resistance is often caused by genetic alterations such as point mutation, which refers to the modification of a single genomic base pair, or gene amplification, which refers to the duplication of a region of DNA that contains a gene. These mechanisms typically confer varying degrees of resistance, and they tend to occur at vastly different frequencies. Here we investigate the dependence of tumor recurrence dynamics on these mechanisms of resistance, using stochastic multi-type branching process models. We derive tumor extinction probabilities and deterministic estimates for the tumor recurrence time, defined as the time when an initially drug sensitive tumor surpasses its original size after developing resistance. For models of amplification-driven and mutation-driven resistance, we prove law of large numbers results regarding the convergence of the stochastic recurrence times to their mean. Additionally, we prove sufficient and necessary conditions for a tumor to escape extinction under the gene amplification model, discuss behavior under biologically relevant parameters, and compare the recurrence time and tumor composition in the mutation and amplification models both analytically and using simulations. In comparing these mechanisms, we find that the ratio between recurrence times driven by amplification versus mutation depends linearly on the number of amplification events required to acquire the same degree of resistance as a mutation event, and we find that the relative frequency of amplification and mutation events plays a key role in determining the mechanism under which recurrence is more rapid for any specific system. In the amplification-driven resistance model, we also observe that increasing drug concentration leads to a stronger initial reduction in tumor burden, but that the eventual recurrent tumor population is less heterogeneous, more aggressive and harbors higher levels of drug-resistance.

Characterization of chemoresistant human non-small cell lung cancer cells by metabolic and lipidomic profiling

INTRODUCTION

Lung cancer is one of the most malignant cancers and the leading cause of cancer-related deaths worldwide, while acquired chemoresistance would represent a major problem in the treatment of non-small cell lung cancer (NSCLC) because of the reduced treatment effect and increased rates of recurrence.

METHODS

To establish the chemoresistant NSCLC cells, doxorubicin was treated to A549 cells over 3 months at gradually increasing concentrations from 0.03 to 0.5 µM. Real-time PCR and Western blotting were employed for investigating mRNA and protein expression of the glutathione peroxidase (GPX) protein family and multidrug resistance protein 1 (MRP1) in A549 and A549/CR cells. We also employed gas chromatography mass-spectrometry and nano electrospray ionization mass-spectrometry coupled with multivariate statistical analysis to characterize the unique metabolic and lipidomic profiles of chemoresistant NSCLC cells in order to identify potential therapeutic targets.

RESULTS

Reactive oxygen species levels were decreased, and mRNA and protein levels of GPX2 and multidrug resistance protein 1 (MRP1) were increased in A549/CR. We identified 87 metabolites and intact lipid species in A549 and A549/CR. Among these metabolites, lactic acid, glutamic acid, glycine, proline, aspartic acid, succinic acid, and ceramide, alongside the PC to PE ratio, and arachidonic acid-containing phospholipids were suggested as characteristic features of chemoresistant NSCLC cells (A549/CR).

CONCLUSIONS

This study reveals characteristic feature differences between drug-resistance NSCLC cells and their parental cells. We suggest potential therapeutic targets in chemoresistant NSCLC. Our results provide new insight into metabolic and lipidomic alterations in chemoresistant NSCLC. This could be used as fundamental information to develop therapeutic strategies for the treatment of chemoresistant NSCLC patients.

Prognostic role of minute ventilation/carbon dioxide production slope for perioperative morbidity and long-term survival in resectable patients with nonsmall-cell lung cancer: a prospective study using propensity score overlap weighting

BACKGROUND

The role of minute ventilation/carbon dioxide production ( / CO 2 ) slope, a ventilation efficiency marker, in predicting short-term and long-term health outcomes for patients with nonsmall-cell lung cancer (NSCLC) undergoing lung resection has not been well investigated.

MATERIAL AND METHODS

This prospective cohort study consecutively enrolled NSCLC patients who underwent a presurgical cardiopulmonary exercise test from November 2014 to December 2019. The association of / CO 2 slope with relapse-free survival (RFS), overall survival (OS), and perioperative mortality was evaluated using the Cox proportional hazards and logistic models. Covariates were adjusted using propensity score overlap weighting. The optimal cut-off point of the E/ CO 2 slope was estimated using the receiver operating characteristics curve. Internal validation was completed through bootstrap resampling.

RESULTS

A cohort of 895 patients [median age (interquartile range), 59 (13) years; 62.5% male] was followed for a median of 40 (range, 1-85) months. Throughout the study, there were 247 relapses or deaths and 156 perioperative complications. The incidence rates per 1000 person-years for relapses or deaths were 108.8 and 79.6 among patients with high and low E/ CO 2 slopes, respectively [weighted incidence rate difference per 1000 person-years, 29.21 (95% CI, 7.30-51.12)]. A E/ CO 2 slope of greater than or equal to 31 was associated with shorter RFS [hazard ratio for relapse or death, 1.38 (95% CI, 1.02-1.88), P =0.04] and poorer OS [hazard ratio for death, 1.69 (1.15-2.48), P =0.02] compared to a lower / CO 2 slope. A high E/ CO 2 slope increased the risk of perioperative morbidity compared with a low E/ CO 2 slope [odds ratio, 2.32 (1.54-3.49), P <0.001].

CONCLUSIONS

In patients with operable NSCLC, a high E/ CO 2 slope was significantly associated with elevated risks of poorer RFS, OS, and perioperative morbidity.

Neoadjuvant immunochemotherapy with pembrolizumab plus chemotherapy in resectable non-small cell lung cancer

Background

Neoadjuvant immunotherapy, the focus of current research and treatment modality for long-term survival, has become one of the main options in supporting primary treatment interventions in early NSCLC.

Methods

This was a retrospective analysis of patients with locally resectable NSCLC who received the neoadjuvant drug pembrolizumab combined with chemotherapy and underwent surgical resection. Pathological responses, PFS and OS in the whole sample and subgroups were analyzed.

Results

Of the 61 patients included in this retrospective analysis, 31 (50.82%) achieved a pCR, and 38 (62.30%) obtained an MPR. Patients with a pCR had significantly higher OS than the non-pCR group (HR = 0.093, P = 0.0227); patients with an MPR also had significantly elevated OS compared with the non-MPR group (HR = 0.05357, P = 0.0169). Patients with lymph node metastasis after surgery had significantly reduced OS (HR = 0.01607, p = 0.0004) and PFS (HR = 0.08757, p = 0.0004) than those without lymph node metastasis. There was no significant difference in OS and PFS between squamous cell carcinomas (SCC) group and adenocarcinomas (AD) group. No significant differences in OS and PFS were found between patients administered 2 and 3 cycles of neoadjuvant therapy before surgery, between those administered ≤5 and > 5 cycles of adjuvant therapy post-surgery, and between patients with TPS <50% and ≥50% (all P > 0.05).

Conclusion

Neoadjuvant immunochemotherapy with pembrolizumab plus chemotherapy in non-small cell lung cancer is safe and tolerable. Both pCR and MPR were closely associated with OS and PFS, reflecting a good response of tumor tissues to drug therapy. Lymph node metastasis after surgery was a poor prognostic factor, reducing OS and PFS.

Role of the long non-coding RNAs in regulation of Gemcitabine response in tumor cells

Chemotherapy is widely used as one of the first line therapeutic methods in cancer patients. However, chemotherapeutic resistance is one of the most common problems in cancer patients, which leads to the therapeutic failure and tumor relapse. Considering the side effects of chemotherapy drugs in normal tissues, it is required to investigate the molecular mechanisms involved in drug resistance to improve the therapeutic strategies in cancer patients. Long non-coding RNAs (lncRNAs) have pivotal roles in regulation of cellular processes associated with drug resistance. LncRNAs deregulations have been frequently reported in a wide range of chemo-resistant tumors. Gemcitabine (GEM) as a nucleoside analog has a wide therapeutic application in different cancers. However, GEM resistance is considered as a therapeutic challenge. Considering the role of lncRNAs in the occurrence of GEM resistance, in the present review we discussed the molecular mechanisms of lncRNAs in regulation of GEM response among cancer patients. It has been reported that lncRNAs have mainly an oncogenic role as the inducers of GEM resistance through direct or indirect regulation of transcription factors, autophagy, polycomb complex, and signaling pathways such as PI3K/AKT, MAPK, WNT, JAK/STAT, and TGF-β. This review paves the way to present the lncRNAs as non-invasive markers to predict GEM response in cancer patients. Therefore, lncRNAs can be introduced as the efficient markers to reduce the possible chemotherapeutic side effects in GEM resistant cancer patients and define a suitable therapeutic strategy among these patients.

Pan-Immune-Inflammatory Value in Patients with Non-Small-Cell Lung Cancer Undergoing Neoadjuvant Immunochemotherapy

Background

We aimed to investigate the predictive value of a systematic serum inflammation index, pan-immune-inflammatory value (PIV), in pathological complete response (pCR) of patients treated with neoadjuvant immunotherapy to further promote ideal patients' selection.

Methods

The clinicopathological and baseline laboratory information of 128 NSCLC patients receiving neoadjuvant immunochemotherapy between October 2019 and April 2022 were retrospectively reviewed. We performed least absolute shrinkage and selection operator (LASSO) algorithm to screen candidate serum biomarkers for predicting pCR, which further entered the multivariate logistic regression model to determine final biomarkers. Accordingly, a diagnostic model for predicting individual pCR was established. Kaplan-Meier method was utilized to estimate curves of disease-free survival (DFS), and the Log rank test was analyzed to compare DFS differences between patients with and without pCR.

Results

Patients with NSCLC heterogeneously responded to neoadjuvant immunotherapy, and those with pCR had a significant longer DFS than patients without pCR. Through LASSO and the multivariate logistic regression model, PIV was identified as a predictor for predicting pCR of patients. Subsequently, a diagnostic model integrating with PIV, differentiated degree and histological type was constructed to predict pCR, which presented a satisfactory predictive power (AUC, 0.736), significant agreement between actual and our nomogram-predicted pathological response.

Conclusion

Baseline PIV was an independent predictor of pCR for NSCLC patients receiving neoadjuvant immunochemotherapy. A significantly longer DFS was achieved in patients with pCR rather than those without pCR; thus, the PIV-based diagnostic model might serve as a practical tool to identify ideal patients for neoadjuvant immunotherapeutic guidance.

rWTC-MBTA: autologous vaccine prevents metastases via antitumor immune responses

BACKGROUND

Autologous tumor cell-based vaccines (ATVs) aim to prevent and treat tumor metastasis by activating patient-specific tumor antigens to induce immune memory. However, their clinical efficacy is limited. Mannan-BAM (MB), a pathogen-associated molecular pattern (PAMP), can coordinate an innate immune response that recognizes and eliminates mannan-BAM-labeled tumor cells. TLR agonists and anti-CD40 antibodies (TA) can enhance the immune response by activating antigen-presenting cells (APCs) to present tumor antigens to the adaptive immune system. In this study, we investigated the efficacy and mechanism of action of rWTC-MBTA, an autologous whole tumor cell vaccine consisting of irradiated tumor cells (rWTC) pulsed with mannan-BAM, TLR agonists, and anti-CD40 antibody (MBTA), in preventing tumor metastasis in multiple animal models.

METHODS

The efficacy of the rWTC-MBTA vaccine was evaluated in mice using breast (4T1) and melanoma (B16-F10) tumor models via subcutaneous and intravenous injection of tumor cells to induce metastasis. The vaccine's effect was also assessed in a postoperative breast tumor model (4T1) and tested in autologous and allogeneic syngeneic breast tumor models (4T1 and EMT6). Mechanistic investigations included immunohistochemistry, immunophenotyping analysis, ELISA, tumor-specific cytotoxicity testing, and T-cell depletion experiments. Biochemistry testing and histopathology of major tissues in vaccinated mice were also evaluated for potential systemic toxicity of the vaccine.

RESULTS

The rWTC-MBTA vaccine effectively prevented metastasis and inhibited tumor growth in breast tumor and melanoma metastatic animal models. It also prevented tumor metastasis and prolonged survival in the postoperative breast tumor animal model. Cross-vaccination experiments revealed that the rWTC-MBTA vaccine prevented autologous tumor growth, but not allogeneic tumor growth. Mechanistic data demonstrated that the vaccine increased the percentage of antigen-presenting cells, induced effector and central memory cells, and enhanced CD4⁺ and CD8⁺ T-cell responses. T-cells obtained from mice that were vaccinated displayed tumor-specific cytotoxicity, as shown by enhanced tumor cell killing in co-culture experiments, accompanied by increased levels of Granzyme B, TNF-α, IFN-γ, and CD107a in T-cells. T-cell depletion experiments showed that the vaccine's antitumor efficacy depended on T-cells, especially CD4⁺ T-cells. Biochemistry testing and histopathology of major tissues in vaccinated mice revealed negligible systemic toxicity of the vaccine.

CONCLUSION

The rWTC-MBTA vaccine demonstrated efficacy in multiple animal models through T-cell mediated cytotoxicity and has potential as a therapeutic option for preventing and treating tumor metastasis with minimal systemic toxicity.

A multi-kernel and multi-scale learning based deep ensemble model for predicting recurrence of non-small cell lung cancer

Predicting recurrence in patients with non-small cell lung cancer (NSCLC) before treatment is vital for guiding personalized medicine. Deep learning techniques have revolutionized the application of cancer informatics, including lung cancer time-to-event prediction. Most existing convolutional neural network (CNN) models are based on a single two-dimensional (2D) computational tomography (CT) image or three-dimensional (3D) CT volume. However, studies have shown that using multi-scale input and fusing multiple networks provide promising performance. This study proposes a deep learning-based ensemble network for recurrence prediction using a dataset of 530 patients with NSCLC. This network assembles 2D CNN models of various input slices, scales, and convolutional kernels, using a deep learning-based feature fusion model as an ensemble strategy. The proposed framework is uniquely designed to benefit from (i) multiple 2D in-plane slices to provide more information than a single central slice, (ii) multi-scale networks and multi-kernel networks to capture the local and peritumoral features, (iii) ensemble design to integrate features from various inputs and model architectures for final prediction. The ensemble of five 2D-CNN models, three slices, and two multi-kernel networks, using 5 × 5 and 6 × 6 convolutional kernels, achieved the best performance with an accuracy of 69.62%, area under the curve (AUC) of 72.5%, F1 score of 70.12%, and recall of 70.81%. Furthermore, the proposed method achieved competitive results compared with the 2D and 3D-CNN models for cancer outcome prediction in the benchmark studies. Our model is also a potential adjuvant treatment tool for identifying NSCLC patients with a high risk of recurrence.

Computational modeling of locoregional recurrence with spatial structure identifies tissue-specific carcinogenic profiles

Introduction

Local and regional recurrence after surgical intervention is a significant problem in cancer management. The multistage theory of carcinogenesis precisely places the presence of histologically normal but mutated premalignant lesions surrounding the tumor - field cancerization, as a significant cause of cancer recurrence. The relationship between tissue dynamics, cancer initiation and cancer recurrence in multistage carcinogenesis is not well known.

Methods

This study constructs a computational model for cancer initiation and recurrence by combining the Moran and branching processes in which cells requires 3 or more mutations to become malignant. In addition, a spatial structure-setting is included in the model to account for positional relativity in cell turnover towards malignant transformation. The model consists of a population of normal cells with no mutation; several populations of premalignant cells with varying number of mutations and a population of malignant cells. The model computes a stage of cancer detection and surgery to eliminate malignant cells but spares premalignant cells and then estimates the time for malignant cells to re-emerge.

Results

We report the cellular conditions that give rise to different patterns of cancer initiation and the conditions favoring a shorter cancer recurrence by analyzing premalignant cell types at the time of surgery. In addition, the model is fitted to disease-free clinical data of 8,957 patients in 27 different cancer types; From this fitting, we estimate the turnover rate per month, relative fitness of premalignant cells, growth rate and death rate of cancer cells in each cancer type.

Discussion

Our study provides insights into how to identify patients who are likely to have a shorter recurrence and where to target the therapeutic intervention.