Prognostic prediction and comparison of three staging programs for patients with advanced (T2-T4) esophageal squamous carcinoma after radical resection.

Purpose: Lymph node-based staging protocols are frequently employed to evaluate the prognosis of esophageal cancer, yet their accuracy remains contentious. The present study was conducted to assess the prognostic significance of three lymph node staging systems, namely N stage, lymph node rate (LNR), and log odds of positive lymph nodes (LODDS), in patients diagnosed with advanced (T2-T4) esophageal squamous cell carcinoma (ESCC). Methods: This cohort comprised 319 eligible patients, with an additional 409 individuals retrieved from the Surveillance, Epidemiology, and End Results (SEER) database, forming the validation cohort. Differences in overall survival (OS) of patients between groups were assessed using the log-rank test. Prognostic independent risk variables were identified, and lymph nodes (LN) prognostic models were built using multivariate Cox regression analysis. Besides, the predictive accuracy of each model was evaluated utilizing the (-2) log-likelihood ratio (-2LLR), the likelihood ratio χ2 score (LRχ2), the Akaike information criterion (AIC), and Harrell's concordance index (C-index). To further evaluate the potential superiority of the model, a nomogram was constructed for comparison with the conventional Tumor Node Metastasis (TNM) staging approach. Results: Independent prognostic factors for advanced ESCC include the N stage, LNR, and LODDS. Herein, LODDS presented higher values for C-index and LRχ2, and lower values for AIC and -2LLR in OS compared to the others. Consequently, a nomogram was constructed based on LODDS. Calibration curves exhibited strong agreement, and assessment through C-index, receiver operating characteristic (ROC) curves, and clinical decision curve analysis (DCA) demonstrated promising clinical applicability. Conclusion: LODDS emerges as a promising future prognostic indicator. After surgery, the proposed model holds the potential to provide valuable treatment recommendations for patients with advanced ESCC.

Immune-tumor interaction dictates spatially directed evolution of esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a poor-prognostic cancer type with extensive intra- and inter-patient heterogeneity in both genomic variations and tumor microenvironment (TME). However, the patterns and drivers of spatial genomic and microenvironmental heterogeneity of ESCC remain largely unknown. Here, we generated a spatial multi-omic atlas by whole-exome, transcriptome, and methylome sequencing of 507 tumor samples from 103 patients. We identified a novel tumor suppressor PREX2, accounting for 22% of ESCCs with frequent somatic mutations or hyper-methylation, which promoted migration and invasion of ESCC cells in vitro. Analysis of the TME and quantification of subclonal expansion indicated that ESCCs undergo spatially directed evolution, where subclones mostly originated from the tumor center but had a biased clonal expansion to the upper direction of the esophagus. Interestingly, we found upper regions of ESCCs often underwent stronger immunoediting with increased selective fitness, suggesting more stringent immune selection. In addition, distinct TMEs were associated with variable genomic and clinical outcomes. Among them, hot TME was associated with high immune evasion and subclonal heterogeneity. We also found that immunoediting, instead of CD8+ T cell abundance, acts as an independent prognostic factor of ESCCs. Importantly, we found significant heterogeneity in previously considered potential therapeutic targets, as well as BRCAness characteristics in a subset of patients, emphasizing the importance of focusing on heterogeneity in ESCC targeted therapy. Collectively, these findings provide novel insights into the mechanisms of the spatial evolution of ESCC and inform precision therapeutic strategies.

Effectiveness of neoadjuvant immunochemotherapy compared to neoadjuvant chemotherapy in non-small cell lung cancer patients: Real-world data of a retrospective, dual-center study.

Background: Studying the application of neoadjuvant immunochemotherapy (NICT) in the real world and evaluating its effectiveness and safety in comparison with neoadjuvant chemotherapy (NCT) are critically important. Methods: This study included the II-IIIB stage non-small cell lung cancer (NSCLC) patients receiving NCT with or without PD-1 inhibitors and undergoing surgery after neoadjuvant treatments between January 2019 to August 2022. The clinical characteristics and treatment outcomes were retrospectively reviewed and analyzed. Results: A total of 66 patients receiving NICT and 101 patients receiving NCT were included in this study. As compared to NCT, NICT showed similar safety while not increasing the surgical difficulty. The ORR in the NICT and NCT groups was 74.2% and 53.5%, respectively, P = 0.009. A total of 44 patients (66.7%) in the NICT group and 21 patients (20.8%) in the NCT group showed major pathology response (MPR) (P <0.001). The pathology complete response (pCR) rate was also significantly higher in NICT group than that in NCT group (45.5% vs. 10.9%, P <0.001). After Propensity Score Matching (PSM), 42 pairs of patients were included in the analysis. The results showed no significant difference in the ORR between the two groups (52.3% vs. 43.2%, P = 0.118), and the proportions of MPR (76.2%) and pCR (50.0%) in NICT group were significantly higher than those of MPR (11.9%) and pCR (4.7%) in the NCT group (P <0.001). The patients with driver mutations might also benefit from NICT. Conclusions: As compared to NCT, the NICT could significantly increase the proportions of patients with pCR and MPR without increasing the operation-related bleeding and operation time.

CT imaging indications correlate with the degree of lung adenocarcinoma infiltration.

Background: Ground glass nodules (GGN) of the lung may be a precursor of lung cancer and have received increasing attention in recent years with the popularity of low-dose high-resolution computed tomography (CT). Many studies have discussed imaging features that suggest the benignity or malignancy of GGN, but the extent of its postoperative pathological infiltration is poorly understood. In this study, we identified CT imaging features that indicate the extent of GGN pathological infiltration. Methods: A retrospective analysis of 189 patients with pulmonary GGN from January 2020 to December 2021 at Shanxi Cancer Hospital was performed. Patients were classified according to their pathological type into non-invasive adenocarcinoma [atypical adenomatous hyperplasia (AAH) and adenocarcinoma in situ (AIS) in a total of 34 cases], micro-invasive adenocarcinoma (MIA) in 80 cases, and invasive adenocarcinoma (IAC) in a total of 75 cases. The general demographic data, nodule size, nodule area, solid component, CT indications and pathological findings of the three groups of patients were analyzed to predict the correlation between GGN and the degree of lung adenocarcinoma infiltration. Results: No statistically significant differences were found among the three groups in general information, vascular signs, and vacuolar signs (P > 0.05). Statistically significant differences among the three groups were found in nodule size, nodule area, lobar signs, pleural traction, burr signs, bronchial signs, and solid components (P < 0.05). Logistic regression equation tests based on the statistically significant indicators showed that nodal area, lobar sign, pleural pull, burr sign, bronchial sign, and solid component were independent predictors of lung adenocarcinoma infiltration. The subject operating characteristic (ROC) curve analysis showed that nodal area is valuable in predicting GGN infiltration. Conclusion: CT-based imaging indications are useful predictors of infiltrative adenocarcinoma manifested as pulmonary ground glass nodules.

Integrated multi-omics profiling yields a clinically relevant molecular classification for esophageal squamous cell carcinoma.

Integrated molecular analysis of human cancer has yielded molecular classification for precise management of cancer patients. Here, we analyzed the whole genomic, epigenomic, transcriptomic, and proteomic data of 155 esophageal squamous cell carcinomas (ESCCs). Multi-omics analysis led to the classification of ESCCs into four subtypes: cell cycle pathway activation, NRF2 oncogenic activation, immune suppression (IS), and immune modulation (IM). IS and IM cases were highly immune infiltrated but differed in the type and distribution of immune cells. IM cases showed better response to immune checkpoint blockade therapy than other subtypes in a clinical trial. We further developed a classifier with 28 features to identify the IM subtype, which predicted anti-PD-1 therapy response with 85.7% sensitivity and 90% specificity. These results emphasize the clinical value of unbiased molecular classification based on multi-omics data and have the potential to further improve the understanding and treatment of ESCC.

Identifying the EMT-related signature to stratify prognosis and evaluate the tumor microenvironment in lung adenocarcinoma.

Background: Epithelial-mesenchymal transition (EMT) is a critical process in tumor invasion and metastasis. EMT has been shown to significantly influence the invasion, metastasis, and poor prognosis in lung adenocarcinoma (LUAD). This study aimed to develop a novel EMT-related prognostic model capable of predicting overall survival (OS) in patients with LUAD. Methods: A total of 283 LUAD patients from TCGA RNA-seq dataset were assigned to a training cohort for model building, and 310 LUAD patients from GEO RNA-seq dataset were assigned to a validation cohort. EMT genes were acquired from MsigDB database and then prognosis-related EMT genes were identified by univariate Cox regression. Lasso regression was then performed to determine the genes and the corresponding variables to construct a prognosis risk model from the training cohort. Furthermore, characteristics of the tumor microenvironment (TME), mutation status and chemotherapy responses were analyzed to assess the differences between the two risk groups based on the prognostic model. In addition, RT-qPCR was employed to validate the expression patterns of the 6 genes derived from the risk model. Results: A six-gene EMT signature (PMEPA1, LOXL2, PLOD2, MMP14, SPOCK1 and DCN) was successfully constructed and validated. The signature assigned the LUAD patients into high-risk and low-risk groups. In comparison with the low-risk group, patients in the high-risk group had a significantly lower survival rate. ROC curves and calibration curves for the risk model demonstrated reliable stratification and predictive ability. The risk model was robustly correlated with multiple TME characteristics. Besides, the data showed that patients in the low-risk group had more immune activities, higher stemness scores and cytolytic activity scores and higher TMB. In addition, RT-qPCR results revealed that PMEPA1, LOXL2, PLOD2, MMP14, and SPOCK1 were notably upregulated in LUAD tissues, while DCN was downregulated. Conclusion: Our study successfully developed a novel EMT-related signature to predict prognosis of LUAD patients and guide treatment strategies. The six genes derived from the prediction signature might play a potential role in antitumor immunity and serve as promising therapeutic targets in LUAD.

A Radiomics Nomogram for Non-Invasive Prediction of Progression-Free Survival in Esophageal Squamous Cell Carcinoma.

To construct a prognostic model for preoperative prediction on computed tomography (CT) images of esophageal squamous cell carcinoma (ESCC), we created radiomics signature with high throughput radiomics features extracted from CT images of 272 patients (204 in training and 68 in validation cohort). Multivariable logistic regression was applied to build the radiomics signature and the predictive nomogram model, which was composed of radiomics signature, traditional TNM stage, and clinical features. A total of 21 radiomics features were selected from 954 to build a radiomics signature which was significantly associated with progression-free survival (p < 0.001). The area under the curve of performance was 0.878 (95% CI: 0.831-0.924) for the training cohort and 0.857 (95% CI: 0.767-0.947) for the validation cohort. The radscore of signatures' combination showed significant discrimination for survival status. Radiomics nomogram combined radscore with TNM staging and showed considerable improvement over TNM staging alone in the training cohort (C-index, 0.770 vs. 0.603; p < 0.05), and it is the same with clinical data (C-index, 0.792 vs. 0.680; p < 0.05), which were confirmed in the validation cohort. Decision curve analysis showed that the model would receive a benefit when the threshold probability was between 0 and 0.9. Collectively, multiparametric CT-based radiomics nomograms provided improved prognostic ability in ESCC.

MiR-421 promotes lipid metabolism by targeting PTEN via activating PI3K/AKT/mTOR pathway in non-small cell lung cancer.

Aims: We aim to investigate the effects of miR-421 on lipid metabolism in non-small cell lung cancer (NSCLC). Methods: The miR-421 expression and PTEN mRNA level in tumor tissues, adjacent normal tissues, human lung epithelial cells and NSCLC cell lines were detected with reverse transcription quantitative real-time PCR. Results: MiR-421 was increased, and PTEN was reduced remarkably in tumor tissues and NSCLC cell lines. Down-regulated miR-421 suppressed lipid accumulation, cell proliferation, migration and invasion, whereas overexpression of miR-421 had the opposite effects. MiR-421 directly targeted PTEN and negatively regulated PTEN expression. MiR-421 activated PI3K/AKT/mTOR pathway through regulating PTEN. Conclusion: MiR-421 promotes lipid metabolism through targeting PTEN via PI3K/AKT/mTOR pathway activation in NSCLC, indicating that miR-421 can be a latent therapeutic target for NSCLC.

Lay abstract Numerous miRNAs are dysregulated in lung cancer, which play vital roles in tumor progression. Currently, the alteration of lipid metabolism has been recognized as a critical hallmark of cancer. In the present study, we found that miR-421 targeted PTEN to promote lipid metabolism via activation of PI3K/AKT/mTOR signaling pathway in NSCLC. This study might provide a deeper insight into the prognostics strategies for lung cancer by understanding the specific mechanism of miR-421 in lipid metabolism.

Progress on neoadjuvant immunotherapy in resectable non-small cell lung cancer and potential biomarkers.

Immune checkpoint inhibitors (ICIs) are highly concerned in the treatment of non-small cell lung cancer (NSCLC), represented by inhibitors of programmed death protein 1 (PD-1) and its ligand (PD-L1), and inhibitors of cytotoxic T lymphocyte-associated antigen-4 (CTLA-4). The introduction of immunotherapy in the treatment of perioperative NSCLC has improved the prognosis to a great extent, as demonstrated by several phase II and III clinical trials. The target population for immunotherapy in early-stage NSCLC is still under discussion, and the biomarkers for neoadjuvant immunotherapy population selection are the next pending problem. The predictive efficacy of many potential makers is still being explored, including PD-L1 expression levels, tumor mutation burden, circulating tumor DNA, components of the tumor microenvironment, and several clinical factors. We summarize key findings on the utility of ICIs in clinical trials of preoperative NSCLC patients and conclude analyses of relevant biomarkers to provide a better understanding of potentially predictive biomarkers in neoadjuvant immunotherapy.

Genomic Landscape and Tumor Mutational Burden Determination of Circulating Tumor DNA in Over 5,000 Chinese Patients with Lung Cancer.

PURPOSE: Having emerged as a noninvasive and clinically applicable approach for molecular determination of lung cancer, a genomic overview of circulating tumor DNA (ctDNA) of large-scale cohort may be helpful in novel biomarker development and therapeutic innovation. EXPERIMENTAL DESIGN: Primary cohort encompasses 5,671 blood samples from 4,892 patients with lung cancer. Pair-wise tissue samples from 579 patients and additional 358 sample pairs were collected to evaluate the correlation between blood and tissue tumor mutational burden (TMB). Parallel sequencing with plasma/tissue and white blood cells was performed using a 1,021-gene panel. RESULTS: Histologic subtyping was the most relevant to ctDNA detectability independent of other demographic characteristics, with small cell lung cancer showing the highest detectability, ctDNA abundance, and blood TMB (bTMB). Mutational landscape demonstrated significant differences, and integrated clonality analysis highlighted distinct driver-pattern and functional pathway interaction among various subtypes. The clonality and concurrent genes of EGFR mutations could predict the therapeutic efficacy of tyrosine kinase inhibitors (TKI), and RB1 mutations in non-small cell lung cancer characterized a subset with high bTMB, elevated ctDNA level, and potential small cell transformation. Most importantly, we developed an adjusted algorithm for bTMB in samples with extremely low ctDNA level and validated its correlation with tissue TMB in an independent cohort. CONCLUSIONS: ctDNA could serve as a promising alternative in genomic profiling for lung cancer. The novel identification of ctDNA clonality and adjusted bTMB might improve therapeutic and prognostic evaluation. This dataset was also a valuable resource for the development of new therapeutic targets and new genomically guided clinical trials.

Author Correction: Multi-region sequencing unveils novel actionable targets and spatial heterogeneity in esophageal squamous cell carcinoma.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Multi-region sequencing unveils novel actionable targets and spatial heterogeneity in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) ranks fourth among cancer-related deaths in China due to the lack of actionable molecules. We performed whole-exome and T-cell receptor (TCR) repertoire sequencing on multi-regional tumors, normal tissues and blood samples from 39 ESCC patients. The data revealed 12.8% of ERBB4 mutations at patient level and functional study supported its oncogenic role. 18% of patients with early BRCA1/2 variants were associated with high-level contribution of signature 3, which was validated in an independent large cohort (n = 508). Furthermore, knockdown of BRCA1/2 dramatically increased sensitivity to cisplatin in ESCC cells. 5% of patients harbored focal high-level amplification of CD274 that led to massive expression of PD-L1, and might be more sensitive to immune checkpoint blockade. Finally, we found a tight correlation between genomic and TCR repertoire intra-tumor heterogeneity (ITH). Collectively, we reveal high-level ITH in ESCC, identify several potential actionable targets and may provide novel insight into ESCC treatment.