Vascular invasion is an adverse prognostic factor in resected non-small-cell lung cancer

Analysis of postoperative recurrence-free survival in non-small cell lung cancer patients based on consensus clustering

AIMS

This study aims to assess whether consensus clustering, based on computed tomography (CT) radiomics from both intratumoral and peritumoral regions, can effectively stratify the risk of non-small cell lung cancer (NSCLC) patients and predict their postoperative recurrence-free survival (RFS).

MATERIALS AND METHODS

A retrospective analysis was conducted on the data of surgical patients diagnosed with NSCLC between December 2014 and April 2020. After preprocessing CT images, radiomic features were extracted from a 9-mm region encompassing both the tumor and its peritumoral area. Consensus clustering was utilized to analyze the radiomics features and categorize patients into distinct clusters. A comparison of the differences in clinical pathological characteristics was conducted among the clusters. Kaplan-Meier survival analysis was employed to investigate differences in survival among the clusters.

RESULTS

A total of 266 patients were included in this study, and consensus clustering identified three clusters (Cluster 1: n=111, Cluster 2: n=61, Cluster 3: n=94). Multiple clinical risk factors, including pathological TNM staging, programmed cell death ligand 1 (PD-L1), and epidermal growth factor receptor (EGFR) expression status exhibit significant differences among the three clusters. Kaplan-Meier survival analysis demonstrated significant variations in RFS across the clusters (P<0.001). The 3-year cumulative recurrence-free survival rates were 76.5% (95% CI: 68.6-84.4) for Cluster 1, 45.9% (95% CI: 33.4-58.4) for Cluster 2, and 41.5% (95% CI: 31.6-51.5) for Cluster 3.

CONCLUSIONS

Consensus clustering of CT radiomics based on intratumoral and peritumoral regions can stratify the risk of postoperative recurrence in patients with NSCLC.

Development and Validation of a Deep Learning Radiomics Model to Predict High-Risk Pathologic Pulmonary Nodules Using Preoperative Computed Tomography

RATIONALE AND OBJECTIVES

To accurately identify the high-risk pathological factors of pulmonary nodules, our study constructed a model combined with clinical features, radiomics features, and deep transfer learning features to predict high-risk pathological pulmonary nodules.

MATERIALS AND METHODS

The study cohort consisted of 469 cases of lung adenocarcinoma patients, divided into a training cohort (n = 400) and an external validation cohort (n = 69). We obtained computed tomography (CT) semantic features and clinical characteristics, as well as extracted radiomics and deep transfer learning (DTL) features from the CT images. Selected features were used for constructing prediction models using the logistic regression (LR) algorithm. The performance of the models was evaluated through metrics including the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, calibration curve, and decision curve analysis.

RESULTS

The clinical model achieved an AUC of 0.774 (95% CI: 0.728-0.821) in the training cohort and 0.762 (95% confidence interval [CI]: 0.650-0.873) in the external validation cohort. The radiomics model demonstrated an AUC of 0.847 (95% CI: 0.810-0.884) in the training cohort and 0.800 (95% CI: 0.693-0.907) in the external validation cohort. The radiomics-DTL (Rad-DTL) model showed an AUC of 0.871 (95% CI: 0.838-0.905) in the training cohort and 0.806 (95% CI: 0.698-0.914) in the external validation cohort. The proposed combined model yielded AUC values of 0.872 and 0.814 in the training and external validation cohorts, respectively. The combined model demonstrated superiority over both the clinical model and the Rad-DTL model. There were no statistically significant differences observed in the comparison between the combined model incorporating clinical features and the Rad-DTL model. Decision curve analysis (DCA) indicated that the models provided a net benefit in predicting high-risk pathologic pulmonary nodules.

CONCLUSION

Rad-DTL signature is a potential biomarker for predicting high-risk pathologic pulmonary nodules using preoperative CT, determining the appropriate surgical strategy, and guiding the extent of resection.

Intratumoral and peritumoral radiomics nomograms for the preoperative prediction of lymphovascular invasion and overall survival in non-small cell lung cancer

OBJECTIVES

To evaluate the predictive value of intratumoral and peritumoral radiomics and radiomics nomogram for preoperative lymphovascular invasion (LVI) status and overall survival (OS) in patients with non-small cell lung cancer (NSCLC).

METHODS

In total, 240 NSCLC patients from our institution were randomly divided into the training cohort (n = 145) and internal validation cohort (n = 95) with a ratio of 6:4, and 65 patients from the Cancer Imaging Archive were enrolled as the external validation cohort. We extracted 1217 CT-based radiomics features from the gross tumor volume (GTV) and gross tumor volume incorporating peritumoral 3, 6, and 9 mm regions (GPTV₃, GPTV₆, GPTV₉). A radiomics nomogram based on clinical independent predictors and radiomics score (Radscore) of the best radiomics model was constructed. The correlation between factors and OS was evaluated with the Kaplan-Meier survival analysis and Cox proportional hazards regression analysis.

RESULTS

Compared with GTV, GPTV₃, and GPTV₆ radiomics models, GPTV₉ radiomics model exhibited better prediction performance with the AUCs of 0.82, 0.75, and 0.67 in the training, internal validation, and external validation cohorts, respectively. In the clinical model, smoking and clinical stage were independent predictors. The nomogram incorporating independent predictors and GPTV₉-Radscore was clinically useful, with the AUCs of 0.89, 0.83, and 0.66 in three cohorts. Pathological LVI, GPTV₉-Radscore-predicted, and Nomoscore-predicted LVI were associated with poor OS (p < 0.05).

CONCLUSIONS

CT-based radiomics nomogram can predict LVI and OS in patients with NSCLC and may help in making personalized treatment strategies before surgery.

KEY POINTS

• Compared with GTV, GPTV₃, and GPTV₆ radiomics models, GPTV₉ radiomics model showed better prediction performance for LVI status in NSCLC. • The radiomics nomogram based on GPTV₉ radiomics features and clinical independent predictors could effectively predict LVI status and OS in NSCLC and outperformed the clinical model. • The radiomics nomogram had a wider scope of clinical application.

Pathological high malignant grade is higher risk of recurrence in pN0M0 invasive lung adenocarcinoma, even with small invasive size

Introduction

Tumor size is an absolute recurrence risk in lung cancer. Although morphological features also reflect recurrence risk, its significance among lower‐risk cases characterized by small size is unknown. We aimed to evaluate the relationship between pathological invasive tumor size and morphological features, and their prognostic impact by considering them simultaneously in lung adenocarcinoma.

Patients and methods

We retrospectively reviewed 563 pN0M0 patients with pathological invasive size of ≤40 mm. The patients were classified by pathological invasive size and pathological malignant grading using the proportion of subhistological components. The prognostic impact was evaluated using recurrence‐free survival (RFS) and overall survival (OS). The impact on prognosis was evaluated using uni‐ and multivariate analyses.

Results

The proportion of histological grade changed according to invasive tumor size. Patients with high malignant grade (G3) showed worse RFS than those with low and intermediate malignant grade (G1+2) with invasive size ≤20 mm. The 5‐year RFS (G1+2 vs. G3) in 5–10 mm was 96.0% vs. 83.3% (HR = 5.505, 95% CI = 7.156–1850, p < 0.001) and in 10–20 mm was 87.8% vs. 67.1% (HR = 2.829, 95% CI = 4.160–43.14, p < 0.001). G3 patients were significantly bigger in invasive size and included more pleural/lymphatic/vascular invasion and recurrence. Multivariate analysis indicated pathological G3 status was significantly associated with worse RFS (HR = 2.097, 95% CI = 1.320–3.333, p = 0.002).

Conclusions

Invasive tumor size and pathological malignant grade overlap in invasive adenocarcinoma. G3 patients are more likely to have pleural/lymphatic/vascular invasion and significantly worse RFS compared to G1/G2 cases, even with a small invasive size of ≤20 mm.

Risk stratification of postoperative recurrence in hypopharyngeal squamous-cell carcinoma patients with nodal metastasis

PURPOSE

To explore lymph node-related risk factors and investigate the benefit of different adjuvant therapy strategies in hypopharyngeal squamous-cell carcinoma (HPSCC) patients with nodal metastasis (N +).

METHODS

We conducted a retrospective review covering 266 HPSCC patients with nodal metastasis. Kaplan-Meier curves and Cox proportional hazard models were utilized to evaluate recurrence-free survival (RFS) and independent risk factors.

RESULTS

pT3-T4, extranodal extension, lymphovascular invasion, and lower lymph node involvement were high-risk factors leading to poorer RFS in N + HPSCC patients. Patients were classified into three groups based on the recursive-partitioning analysis (RPA). Postoperative chemoradiation significantly improved RFS in patients in the high-risk group (p < 0.001). For patients in the low- and intermediate-risk groups, the application of adjuvant therapies showed no significant benefit on RFS (p = 0.74 and 0.53, respectively).

CONCLUSIONS

The novel risk stratification for N + HPSCC patients can predict the risk of postoperative recurrence effectively. Adjuvant chemoradiation is preferred for patients in the high-risk group as it lowers risk of recurrence. Conversely, for patients in the low- and intermediate-risk groups, regular observation and follow-up strategies are a valid form of treatment.

[Prognostic Factors of N2 Stage Non-small Cell Lung Cancer after Surgery]

背景与目的

N2期非小细胞肺癌患者预后异质性很强，本研究旨在探索其预后相关因素。

方法

纳入四川大学华西医院胸外科2007年1月-2016年12月间行根治性切除的N2期患者，使用Cox模型比较临床病理学特征与总体生存率之间的关系，使用Kaplan-Meier法绘制生存曲线，并且根据淋巴结转移情况进行亚组分析。

结果

总共纳入773例N2期患者，中位随访时间57.2个月，5年总体生存率为34.8%。肿瘤原发灶-淋巴结-远处转移（tumor-node-metastasis, TNM）分期、多站淋巴结转移、跳跃性转移、脉管侵犯、辅助化疗为预后相关的独立风险因素。T1-3期患者具有相似的预后，T4期患者预后明显更差。单站跳跃性转移的患者预后最好，5年生存率达48.9%。

结论

N2患者中T4期预后差。在将来的分期中应结合淋巴结转移站数和跳跃性转移进行更精细的N分期划分。

A 5-microRNA signature identified from serum microRNA profiling predicts survival in patients with advanced stage non-small cell lung cancer

Circulating microRNAs (miRNAs) are potential biomarkers for cancer diagnosis, screening and prognosis. This study aimed to identify serum miRNAs as predictors of survival in patients with advanced non-small cell lung cancer (NSCLC). We profiled serum miRNAs in a pilot set of four patients with good survival (>24 months) and four patients with poor survival (<6 months). We selected 140 stably detectable miRNAs and 42 miRNAs reported in literature for further analysis. Expression of these 182 miRNAs was measured using high-throughput polymerase chain reaction assay, and their association with 3-year survival in the discovery (n = 345) and validation (n = 177) cohorts was assessed. Five serum miRNAs (miR-191, miR-28-3p, miR-145, miR-328 and miR-18a) were significantly associated with 3-year overall survival in both cohorts. A combined 5-miRNA risk score was created to assess the cumulative impact of these miRNAs on risk of death. Quartile analysis of the risk score showed significant association with 3-year death risk, with a 4.6-, 6.8- and 9.3-month reduction in median survival time for the second, third and fourth quartiles, respectively. Survival tree analysis also identified distinct risk groups with different 3-year survival durations. Data from The Cancer Genome Atlas revealed all five miRNAs were differentially expressed (P < 0.0001) in paired tumor and normal tissues. Pathway analysis indicated that target genes of these five miRNAs were mainly enriched in inflammatory/immune response pathways and pathways implicated in resistance to chemoradiotherapy and/or targeted therapy. Our results suggested that the 5-miRNA signature could serve as a prognostic predictor in patients with advanced NSCLC.

Influential factors and prognostic analysis of blood vessel invasion in advanced gastric cancer

The purpose of this study was to analyze the influencing factors of BVI in advanced gastric cancer and explore the factors affecting the prognosis of advanced gastric cancer, so as to accurately evaluate the disease status and enable patients to receive effective treatment. We retrospectively analyzed 622 cases with complete data and successful follow-up. BVI was found in 144 of the 622 patients with advanced gastric cancer, with a detection rate of 23.15%. BVI was closely related to the differentiation degree, infiltration depth and lymph node metastasis of advanced gastric cancer, (P <  0.05). Gender, age, tumor location, tumor size, Lauren classification, tumor M stage, and clinical TNM stage were not the influencing factors of BVI in patients with advanced gastric cancer (P >  0.05). The 5-year survival rate of patients in the positive group of BVI was 34.72%. The 5-year survival rate of patients with advanced gastric cancer was correlated with BVI, Lauren classification, depth of invasion, lymph node metastasis, and clinical TNM staging, (P <  0.05). The 5-year survival rate was independent of gender, age, tumor location, tumor size, tumor tissue differentiation, and M stage (P >  0.05). The results of multi-factor analysis showed that BVI, N stage and clinical TNM stage were independent predictors of prognosis in patients with advanced radical gastric cancer. By analyzing the stage and related prognostic factors of resectable advanced gastric cancer, we found that BVI was not only closely related to lymph node metastasis, but also an independent predictor of prognosis of advanced gastric cancer. As this study was only a single-center retrospective study, there may be a selective bias in clinical data. So large-scale and multi-center collaboration is needed to further explore the influencing factors of BVI in the progression of gastric cancer.

Magnetic resonance imaging evaluation of characteristics of vascular invasion in intermediate and advanced hepatic alveolar echinococcosis

The objective of the present study was to provide a basis for the personalized treatment of intermediate and advanced hepatic alveolar echinococcosis (HAE) by elucidating the characteristics of vascular invasion and lesion growth. A total of 160 patients with intermediate and advanced HAE who were subjected to plain as well as contrast-enhanced 3.0-T magnetic resonance imaging prior to surgery were analyzed. Pathological and intra-operative observations of the subjects were also considered. The size and location of HAE lesions, vascular invasion characteristics and growth patterns were assessed. A total of 78 patients (48.75%) had lesions involving the S5-8 segment/partial right liver lobe, 21 (13.13%) had involvement in the S2-4 segment/partial left liver lobe and 61 (38.13%) had lesions that transcended the left and right liver lobes. Pathological examination revealed that the vascular invasion rates of the hepatic portal veins, intrahepatic veins (left, central and right vein, and inferior vena cava) and hepatic arteries were 51.88, 43.28 and 26.87%, respectively. Liver hilum invasion was observed in 128 patients (80.00%), 71 of which (44.38%) presented with invasion of the primary porta hepatis, 11 (6.88%) with invasion of the secondary porta hepatis and 46 (28.75%) with invasion of the primary as well as the secondary porta hepatis. In conclusion, the growth pattern of intermediate and advanced HAE is determined by the site, blood supply and activity of the lesion. The current study demonstrated that lesions tend to invade the intrahepatic venous system and porta hepatis, and to target veins rather than arteries.

Low expression of SerpinB2 is associated with reduced survival in lung adenocarcinomas

Lung cancer is a leading cause of cancer deaths worldwide and new biomarkers are of utmost importance. Studies have indicated that the anti-plasminogen activators SerpinB2 and Neuroserpin, and the adhesion molecule L1CAM, have a coordinated impact on development of metastasis. Here, we examined whether expression of these markers was associated with clinico-pathologic characteristics and prognosis in resected non-small cell lung cancer (NSCLC).

Surgical specimens from 438 NSCLC patients treated at Haukeland University Hospital, Bergen, Norway (1993-2010) were included (median age 68 years; 213 adenocarcinomas, 135 squamous cell carcinomas, 90 others). Representative tumor sections were stained for SerpinB2, Neuroserpin, and L1CAM.

Low expression of SerpinB2 was associated with reduced lung cancer specific survival (LCSS) in adenocarcinomas (p = 0.017), also in stage I (p = 0.031). In contrast, high SerpinB2 was associated with reduced LCSS in stage I squamous cell carcinomas (p = 0.022). Although Neuroserpin and L1CAM showed some associations with clinico-pathologic phenotype, there were no associations with survival. In multivariate survival analysis of adenocarcinomas, low SerpinB2 demonstrated independent prognostic value (HR 1.8, p = 0.008).

In summary, low expression of SerpinB2 in lung adenocarcinomas was an independent prognostic factor. In contrast to findings by others, we found no impact of L1CAM on survival. Introduction

Microvascular proliferation is associated with aggressive tumour features and reduced survival in lung adenocarcinoma

Despite new treatment options in lung cancer, there is still a need for better biomarkers to assist in therapy decisions. Angiogenesis has been associated with tumour growth and dissemination, and the vascular proliferation index (VPI) is a valuable prognostic marker in other tumours. Nestin, a marker of immature endothelium, was previously applied in combination with Ki67 for proliferating endothelium as a novel marker (Nestin‐Ki67) of ongoing angiogenesis. Here, the prevalence and prognostic impact of vascular proliferation on lung cancer‐specific survival (LCSS) in lung adenocarcinomas was studied. Selected tumour slides from a cohort of 210 patients treated surgically for adenocarcinoma at Haukeland University Hospital (Norway) from 1993 to 2010 were stained for Nestin‐Ki67. VPI, the ratio between the density of proliferating vessels and the overall microvessel density were used, and the cut‐off value was set at 4.4% (upper quartile). High VPI was associated with the presence of blood vessel invasion (p = 0.007) and tumour necrosis (p = 0.007). Further, high VPI was significantly associated with reduced LCSS (p = 0.020). By multivariate analysis, VPI remained an independent prognostic factor for reduced LCSS (HR 1.7; 95% CI 1.04–2.68; p = 0.033) when adjusted for other prognostic clinico‐pathological features. In conclusion, microvessel proliferation assessed using the VPI was associated with aggressive tumour features such as blood vessel invasion and tumour necrosis and, independently, decreased LCSS. This marker should be further explored in separate cohorts, and in trials of anti‐angiogenesis therapy.