Clinical significance of visceral pleural and lymphovascular invasion in surgically resected adenosquamous lung cancer

Integrating machine learning and multi-omics analysis to develop an asparagine metabolism immunity index for improving clinical outcome and drug sensitivity in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a malignancy affecting the respiratory system. Most patients are diagnosed with advanced or metastatic lung cancer due to the fact that most of their clinical symptoms are insidious, resulting in a bleak prognosis. Given that abnormal reprogramming of asparagine metabolism (AM) has emerged as an emerging therapeutic target for anti-tumor therapy. However, the clinical significance of abnormal reprogramming of AM in LUAD patients is unclear. In this study, we collected 864 asparagine metabolism-related genes (AMGs) and used a machine-learning computational framework to develop an asparagine metabolism immunity index (AMII) for LUAD patients. Through the utilization of median AMII scores, LUAD patients were segregated into either a low-AMII group or a high-AMII group. We observed outstanding performance of AMII in predicting survival prognosis in LUAD patients in the TCGA-LUAD cohort and in three externally independently validated GEO cohorts (GSE72094, GSE37745, and GSE30219), and poorer prognosis for LUAD patients in the high-AMII group. The results of univariate and multivariate analyses showed that AMII can be used as an independent risk factor for LUAD patients. In addition, the results of C-index analysis and decision analysis showed that AMII-based nomograms had a robust performance in terms of accuracy of prognostic prediction and net clinical benefit in patients with LUAD. Excitingly, LUAD patients in the low-AMII group were more sensitive to commonly used chemotherapeutic drugs. Consequently, AMII is expected to be a novel diagnostic tool for clinical classification, providing valuable insights for clinical decision-making and personalized management of LUAD patients.

Machine Learning Models to Predict Bone Metastasis Risk in Patients With Lung Cancer

INTRODUCTION

The aim of this study was to find the most appropriate variables to input into machine learning algorithms to identify those patients with primary lung malignancy with high risk for metastasis to the bone.

PATIENT INCLUSION

Patients with either histological or radiological diagnoses of lung cancer were included in this study.

RESULTS

The patient cohort comprised 1864 patients diagnosed from 2016 to 2021. A total of 25 variables were considered as potential risk factors. These variables have been identified in previous studies as independent risk factors for bone metastasis. Treatment methods for lung cancer were taken into account during model development. The outcome variable was binary, (presence or absence of bone metastasis) with follow-up until death or 12-month survival, whichever is the sooner. Results showed that American Joint Committee on Cancer staging, the use of EGFR inhibitor, age, T-staging, and lymphovascular invasion were the five input features contributing the most to the model algorithm. High AJCC staging (OR 1.98; p < 0.05), the use of EGFR inhibitor (OR 6.14; p < 0.05), high T-staging (OR 1.47; p < 0.05), and the presence of lymphovascular invasion (OR 4.92; p < 0.05) increase predicted risk of bone metastasis. Conversely, older age reduces predicted bone metastasis risk (OR 0.98; p < 0.05).

CONCLUSION

The machine learning model developed in this study can be easily incorporated into the hospital's Clinical Management System so that input variables can be immediately utilized to give an accurate prediction of bone metastatic risk, therefore informing clinicians on the best treatment strategy for that individual patient.

The location of visceral pleural invasion in stage IB patients with non-small cell lung cancer: Comparison and prognosis

OBJECTIVES

Recently, early-stage lung cancer has been drawing more attention, especially in screening and treatment. Visceral pleural invasion in stage IB cancer is considered as risk factor for poor prognosis. Herein, we aimed to study the distinction between the different locations of visceral pleural invasion.

METHODS

In this retrospective cohort study, we summarized 58,242 patient cases that underwent surgery from 2015 to 2018 at Shanghai Chest Hospital. Of those patients, 389 met the inclusion criteria. Patients with PL3 pleural invasion were excluded. The patients were dichotomized into the interlobar pleural and peripheral pleural groups. The outcomes measured were overall survival (OS) and recurrence-free survival (RFS) rates.

RESULTS

According to the initial analysis, the baseline characteristics of the two groups were largely balanced. In multivariate Cox analyses, we found that the location of visceral pleural invasion was not a risk factor for prognosis in the overall population (RFS: P = 0.726, OS: P = 0.599). However, we discovered that relative to patients with peripheral pleura invasion, those with interlobar pleura invasion, PL1 invasion, lesions with greater than 3 cm solid components, and those who underwent segmentectomy had a compromised prognosis. Additionally, tumors larger than 3 cm in size with interlobar pleura invasion showed poor prognosis in patients who underwent postoperative chemotherapy.

CONCLUSIONS

In most cases, the location of tumor invasion did not worsen the postoperative prognosis of stage IB non-small cell lung cancer patients with visceral pleural invasion. However, interlobar pleural invasion still had some potential risks compared to that of peripheral pleural invasion.

Predictive Value of 18 F-FDG PET/MRI for Pleural Invasion in Solid and Subsolid Lung Adenocarcinomas Smaller Than 3 cm

BACKGROUND

Positron emission tomography (PET)/MRI combines the characteristics of metabolism imaging and high soft tissue resolution, and could provide high diagnostic efficacy for assessment of pleural invasion (PI) of lung cancer.

PURPOSE

To investigate the application of ¹⁸ F-fluorodeoxyglucose (FDG) PET/MRI for predicting PI of lung cancer with the maximum diameter ≤3 cm.

STUDY TYPE

Prospective.

POPULATION

A total of 44 patients with non-small cell lung cancer (NSCLC), age from 39 to 79 years old, including 19 (56.82%) females.

FIELD STRENGTH/SEQUENCE

A 3-T, hybrid PET/MRI including axial fast spin echo respiratory-triggered T2 fat-suppressed imaging (T2FS) and echo planar imaging diffusion-weighted imaging (DWI).

ASSESSMENT

The maximum standardized uptake value (SUVmax) of all lesions was measured on PET images. Localized effusion outside the contact between the nodules and the pleura on T2FS and signal at the contact between the nodules and the pleura on DWI were evaluated by experienced physicians through visual assessment of the MRI sequences.

STATISTICAL TESTS

Three models (models 1-3) were developed, incorporating CT, CT and PET, PET and MRI features, and Lasso regression was used in feature selection. The receiver operating characteristic (ROC) curve for PI diagnosis was visualized for each model, and the area under the curve (AUC) was calculated. The DeLong test was used to compare the different AUCs. A P value < 0.05 was considered statistically significant.

RESULTS

The AUC of models 1-3 was 0.762, 0.829, and 0.915, respectively. The DeLong test showed a statistically significant difference between the AUCs of model 1 vs. model 3, while the differences between the AUCs of model 1 vs. model 2 (P = 0.253) and model 2 vs. model 3 (P = 0.075) were not statistically significant.

DATA CONCLUSION

¹⁸ F-FDG PET/MRI might show high predictive value for lung adenocarcinoma smaller than 3 cm with PI.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Clinicopathological characteristics and prognosis of resectable lung adenosquamous carcinoma: a population-based study of the SEER database

OBJECTIVE

Adenosquamous carcinoma is a rare subtype of non-small cell lung cancer characterized by aggressive behavior, with combination of adenocarcinoma and squamous cell carcinoma components. The clinicopathological characteristics and prognosis of resectable adenosquamous carcinoma are incompletely understood and this study aimed to depict those in a large population.

METHODS

A total of 805 adenosquamous carcinoma, 7875 squamous cell carcinoma and 23 957 adenocarcinoma patients who underwent lobectomy or sublobectomy were queried from the Surveillance, Epidemiology, and End Results database (2010-17). Clinicopathological characteristics of adenosquamous carcinoma patients were compared with those of squamous cell carcinoma and adenocarcinoma patients. Prognostic factors were identified by univariable and multivariable Cox regression analyses. Propensity score matching was applied to reduce confounding effects.

RESULTS

Adenosquamous carcinoma was associated with higher pleural invasion incidence and poorer differentiation compared with squamous cell carcinoma or adenocarcinoma (P values < 0.001). The independent risk factors of cancer-specific survival of adenosquamous carcinoma patients were increasing age, male sex, invading through visceral pleura, poor differentiation and higher stage. Stage IB adenosquamous carcinoma patients whose tumor invaded through visceral pleura had significantly worse survival than those not (P = 0.003). Adenosquamous carcinoma patients had worse survival compared with squamous cell carcinoma (5-year-survival: 64.55 vs. 69.09%, P = 0.003) and adenocarcinoma (5-year-survival: 64.55 vs. 76.79%, P < 0.001) patients before match. And this difference persisted after match.

CONCLUSIONS

Resectable adenosquamous carcinoma patients had higher pleural invasion incidence, poorer differentiation and worse survival compared with squamous cell carcinoma and adenocarcinoma patients. Visceral pleural invasion status and differentiation grade were vital prognostic factors of adenosquamous carcinoma patients on the basis of stage.

The Effect of Examined Lymph Nodes and Lymph Node Ratio on Pathological Nodal Classification in the Lung Adenosquamous Carcinoma After Lobectomy

Objective

The effects of examined lymph nodes (LNs) and lymph node ratio (LNR) on pN classification and the prognosis are unclear in lung adenosquamous carcinoma (ASC) patients. Thus, this study aimed to investigate the significance of LNs and LNR in the prognosis of ASC and the impact of the abovementioned factors on the pN classification.

Methods

Patients diagnosed with pathological stage T1-4N0-2M0 ASC from the Surveillance Epidemiology and End Results database were included in the study. The primary clinical endpoint was cancer-specific survival (CSS). The optimal cutoff values of the LNs and LNR were determined. An LN indicator, including pN0 #LNs ≤9, pN0 #LNs >9, pN⁺ #LNR ≤0.53, and pN⁺ #LNR > 0.53, was developed. Concordance index (C-index) was used to compare the prognostic predictive ability between N classification and LN indicator. The univariable and multivariable Cox regression analyses were used in this study.

Results

The cohort of 1,416 patients were included in the study. The level of LNs stratified the patients without metastasis of lymph nodes (pN0 #LNs ≤9 vs. pN0 #LNs >9, unadjusted hazard ratio [HR] = 1.255, P = 0.037). Two groups based on the cutoff value of LNR differentiated prognosis of patients with metastasis of lymph nodes (pN⁺ #LNR >0.53 vs. pN⁺ #LNR ≤0.53, unadjusted HR = 1.703, P = 0.001). The LN indicator had a much better predictive ability over N classification in this cohort (LN indicator: C-index = 0.615; N classification: C-index = 0.602, P = 0.001).

Conclusions

We explored clinicopathological factors affecting prognosis in resected lung ASC patients. Besides, the LN indicator was confirmed to be played an essential role in affecting the survival rate in ASC patients. The high-level LNs or low-level LNR might be corelated to improved survival outcomes.

Preoperative risk factors of lymph node metastasis in clinical N0 lung adenocarcinoma of 3 cm or less in diameter

BACKGROUND

Lung adenocarcinoma is the most common subtype of non-small cell lung cancer. The surgical strategy of lymph node dissection is controversial because many more patients are diagnosed at an early stage in clinical practice.

METHODS

We retrospectively reviewed 622 clinical N0 lung adenocarcinoma patients with 3 cm or less in tumor size who underwent lobectomy or segmentectomy combined with lymph node dissection in our hospital from January 2017 to December 2019. We performed univariate and multivariate analyses to identify preoperative risk factors of lymph node metastasis.

RESULTS

Lymph node metastasis was found in 60 out of 622 patients. On univariate analysis, lymph node metastasis was linked to smoking history, preoperative CEA level, tumor size, tumor location (peripheral or central), consolidation/tumor ratio, pleural invasion, and pathologic type. However, only the preoperative CEA level, tumor size, and consolidation/tumor ratio were independent risk factors in multivariate analysis. The ROC curve showed that the cutoff value of tumor size was 1.7 cm. There was no lymph node metastasis in patients without risk factors.

CONCLUSIONS

The preoperative CEA level, tumor size, and consolidation/tumor ratio were independent risk factors of lymph node metastasis in clinical N0 lung adenocarcinoma with tumor size ≤ 3 cm. The lymph node metastasis rate was extremely low in clinical N0 lung adenocarcinoma patients without risk factors and lymph node dissection should be avoided in these patients to reduce surgical trauma.

Prognostic significance of visceral pleural invasion in patients with surgically resected small-cell lung cancer: a population-based study

OBJECTIVE

Visceral pleural invasion is an adverse prognostic factor in non-small-cell lung cancer, but its value in small-cell lung cancer remains unclear. Thus, we investigated the prognostic impact of visceral pleural invasion in patients with surgically resected small-cell lung cancer.

METHODS

We queried the Surveillance, Epidemiology and End Results Program database for patients diagnosed with stages I-III (excluding N3 and nodal metastasis cannot be evaluated (NX)) small-cell lung cancer from 2004 to 2016, who underwent surgery. To minimize unbalanced baseline characteristics between the visceral pleural invasion and non-visceral pleural invasion groups, one-to-one propensity score matching was employed. A Kaplan-Meier curve was used to compare the overall survival of the two cohorts. A Cox proportional hazards model was adopted to determine the impact of visceral pleural invasion on survival.

RESULTS

Of the 1416 patients included, 372 (26.27%) presented with visceral pleural invasion. Patients with visceral pleural invasion showed significantly worse overall survival (P < 0.001) both before and after propensity score matching. Multivariable analysis indicated that visceral pleural invasion was an independent adverse factor affecting survival. Patients with visceral pleural invasion showed poorer overall survival (hazard ratio: 1.44; 95% confidence interval: 1.17-1.76; P < 0.001). Subgroup analyses revealed that the non-visceral pleural invasion group was associated with favourable overall survival in N0 patients (P = 0.003) but not in N1 or N2 patients (P = 0.774 and 0.248, respectively). Patients diagnosed at younger ages, females, lower N stage, resection with a lobectomy and adjuvant chemotherapy were associated with improved overall survival in the visceral pleural invasion group.

CONCLUSIONS

Visceral pleural invasion was an indicator of a poor prognosis for small-cell lung cancer, especially in those with N0 disease. Adjuvant chemotherapy significantly improves patient outcomes for patients with visceral pleural invasion.