A grading system of lung adenocarcinomas based on histologic pattern is predictive of disease recurrence in stage I tumors

Prognostic and clinicopathological significance of the new grading system for invasive pulmonary adenocarcinoma: A systematic review and meta-analysis

In 2020, the International Association for the Study of Lung Cancer (IASLC) introduced a new grading system for invasive pulmonary adenocarcinoma (IPA). This meta-analysis aimed to validate the prognostic utility of this grading system and identify relevant clinicopathological features. The PubMed, Embase, Web of Science, and Cochrane Library databases were searched for relevant studies published between January 1, 2020 and March 5, 2024. Hazard ratios (HRs) with corresponding 95 % confidence intervals (CIs) were pooled to evaluate the effect of IASLC grading on prognosis. Odds ratios with corresponding 95 % CIs were pooled to assess relevant clinicopathological features. Twenty-two studies comprising 12,515 patients with IPA were included. Regarding overall survival, grade 3 adenocarcinomas had a worse prognosis compared with grades 1-2 (HR: 2.26, 95 % CI: 1.79-2.85, P<0.001), grade 1 (HR: 4.75, 95 % CI: 2.61-8.66, P<0.001), or grade 2 (HR: 1.71, 95 % CI: 1.28-2.29, P<0.001). Considering recurrence-free survival, grade 3 tumors had a higher recurrence risk than grades 1-2 (HR: 1.92, 95 % CI: 1.53-2.41, P<0.001), grade 1 (HR: 4.43, 95 % CI: 2.91-6.73, P<0.001), or grade 2 (HR: 1.67, 95 % CI: 1.33-2.10, P<0.001). In the subgroup analysis of stage I patients, grade 3 tumors exhibited a similarly poor prognosis. In addition, grade 3 adenocarcinomas were associated with aggressive clinicopathological features. This study demonstrated that the IASLC grading system is a robust predictor of prognostic stratification in patients with IPA, and warrants further promotion and worldwide implementation.

Digital image analysis of tumour pattern and histological models for prognostic evaluation of invasive non-mucinous adenocarcinoma of the lung

The 2021 World Health Organisation classification of lung adenocarcinoma is based on the predominance and percentage of high-grade histological patterns, e.g. solid and micropapillary patterns, determined by semiquantitative estimation. Digital pathology can be used to evaluate the area of each pattern and calculate the exact percentage. To evaluate the prognostic predictive ability of a histological model for invasive non-mucinous adenocarcinoma using digital pathology. This retrospective cohort study included 76 patients with invasive non-mucinous lung adenocarcinoma who underwent lung resection at Songklanagarind Hospital between January 2010 and December 2016. The histological pattern area was measured on a digital slide using the QuPath Open software version 0.3.2. Clinical and pathological data, including the presence of tumour spread through airspaces, tumour necrosis, tumour-infiltrating lymphocytes, and lymphovascular invasion, were collected. The primary outcome was 5-year overall survival. The best model was provided by the Akaike information criterion, and the prognostic discrimination ability was compared with that of other models from previous studies by identifying the area under the curve (AUC) in the receiver operating characteristic analysis. The best model was validated using bootstrapping. The best model was a combination of stage and an 82 % cut-off high-grade pattern (AUC = 0.776). Tumours with ≥82 % high-grade pattern resulted in significantly worse prognoses (p = 0.001) than those with <82 % high-grade pattern. Our model had the highest AUC among all models from previous studies. This was validated using bootstrapping, with an AUC of 0.708. The best model for survival prediction was a combination of stage and an 82 % cut-off high-grade pattern.

Combination of grade and spread through air spaces (STAS) predicts recurrence in early stage lung adenocarcinoma: a retrospective cohort study

Adenocarcinomas, a common subtype of lung cancer, exhibit diverse histological patterns. In 2020, The International Association for the Study of Lung Cancer (IASLC) introduced a grading system emphasizing high-grade components, which has shown prognostic value. Spread through air spaces (STAS) is recognized as a prognostic feature increasing the risk of recurrence in lung cancer. This study evaluates the combination of STAS status and the IASLC-grading system in surgically resected Stage I lung adenocarcinomas. This study is a retrospective analysis of 123 patients with Stage I lung adenocarcinoma who underwent lobectomy between 2011 and 2019. Histological patterns were assessed according to the IASLC criteria, and STAS status was documented. Patients were categorized based on their IASLC Grade and STAS status. Statistical analyses included Kaplan-Meier survival estimates, Cox proportional hazards models, and comparisons using Chi-square and t-tests. The cohort comprised 43 females and 80 males with a mean age of 61.8 ± 7.6 years. STAS positivity was noted in 52.8% of patients. STAS positivity correlated significantly with Grade 3 tumors (p < 0.001). The 5-year recurrence-free survival was significantly lower in STAS-positive patients (70.7% vs. 88.7%, p = 0.026). Patients with Grade 3 and STAS positivity had significantly lower recurrence-free survival compared to other groups (p = 0.002). Grade 3 and STAS positivity were independent predictors of poor recurrence-free survival in multivariate analysis. IASLC Grade 3 tumors and STAS positivity are independent prognostic factors for poor recurrence-free survival in Stage I lung adenocarcinomas. Adjuvant treatment strategies should be considered for patients with these characteristics to improve outcomes.

Pathological features of the differentiation landscape in esophageal squamous cell cancer and their correlations with prognosis

Background

For esophageal squamous cell carcinoma (ESCC), universally accepted pathological criteria for classification by differentiation degree are lacking. Tumor budding, single-cell invasion, and nuclear grade, recognized as prognostic factors in other carcinomas, have rarely been investigated for their correlation with differentiation and prognosis in ESCC. This study aims to determine if pathological findings can predict differentiation degree and prognosis in ESCC.

Patients and methods

This study reviewed tumor slides from 326 patients who underwent surgery for ESCC between 2007 and 2012. Tumors were evaluated for subtypes, tumor nest size, tumor stroma, and nuclear grade (nuclear diameter and mitosis) across different differentiation groups. Overall survival (OS) and disease-free survival (DFS) were estimated using the Kaplan-Meier method, with group differences assessed using the stratified log-rank test and Cox proportional hazards model.

Results

The mean values of tumor budding invasion margins in well, moderately, and poorly differentiated groups were 25.3%, 30.7%, and 36.3%, respectively. Mean tumor budding/10HPFs were 8.0, 10.3, and 13.0, respectively. Well-differentiated tumors showed more keratinizing subtypes, smaller tumor budding invasion margins, more Grade 1 tumor budding (0-4 cells), absence of single-cell invasion, larger nuclear diameter (≥5 lymphocytes), higher mitotic counts, more submucosal invasion, and less lymphovascular invasion. Conversely, poorly differentiated tumors exhibited opposite characteristics. Multivariate analyses identified the nuclear diameter as independent prognostic factors for OS and DFS.

Conclusions

Pathological features can stratify the differentiation landscape in ESCC patients. The nuclear diameter (4 lymphocytes) can help predict prognosis in ESCC than other pathological features.

Implications for practice

We first time report the mean values of tumor budding invasion margins and tumor budding/10HPF in well, moderately, and poorly differentiated groups for esophageal squamous cell carcinoma. The landscape of well differentiation was depicted with more keratinizing subtypes, smaller tumor budding invasion margins, more Grade 1 tumor budding (0-4 cells), absence of single-cell invasion, larger nuclear diameter (≥5 lymphocytes), higher mitotic counts, and less lymphovascular invasion. The nuclear diameter as independent prognostic factors for prognosis. The findings indicate that pathological features can stratify the differentiation landscape in ESCC patients and offer novel insight into definition of well or moderately differentiation.

Prognostic impact of the newly revised IASLC proposed grading system for invasive lung adenocarcinoma: a systematic review and meta-analysis

BACKGROUND

This study aimed to evaluate the prognostic value of the newly revised International Association for the Study of Lung Cancer (IASLC) grading system (2020) on the 5-year overall survival (OS) and recurrence-free survival (RFS) in patients with lung adenocarcinoma (LADC).

METHODS

Clinical studies that investigated the prognostic value of revised IASLC staging system in patients with LADC were retrieved from the PubMed, Web of Science, ScienceDirect, and Cochrane Library databases. This study was conducted in accordance to the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and checklists.

RESULTS

Based on inclusion and exclusion criteria, we included 12 studies for analysis. The grade of LADC was assessed by revised IASLC system, which included three grades. Compared to Grade 3 LADC, grade 1 (total [95% CI]: 1.38 [1.19, 1.60]) and grade 2 (total [95% CI]: 1.29 [1.15, 1.44]) LADC had higher 5-year OS rates. Similarly, Grade 1 (total [95% CI]: 1.76 [1.42, 2.18]) and Grade 2 (total [95% CI]: 1.51 [1.28, 1.77]) had higher 5-year RFS rates Grade 3 LADC. However, 5-year OS and RFS had no significant difference between Grade 1 and Grade 2 patients.

CONCLUSION

This systematic review and meta-analysis provides evidence that the newly revised IASLC grading system is significantly associated with the prognosis of patients with LADC, where Grade 3 indicated unfavorable prognosis.

A novel histopathological feature of spatial tumor-stroma distribution predicts lung squamous cell carcinoma prognosis

We used a mathematical approach to investigate the quantitative spatial profile of cancer cells and stroma in lung squamous cell carcinoma tissues and its clinical relevance. The study enrolled 132 patients with 3-5 cm peripheral lung squamous cell carcinoma, resected at the National Cancer Center Hospital East. We utilized machine learning to segment cancer cells and stroma on cytokeratin AE1/3 immunohistochemistry images. Subsequently, a spatial form of Shannon's entropy was employed to precisely quantify the spatial distribution of cancer cells and stroma. This quantification index was defined as the spatial tumor-stroma distribution index (STSDI). The patients were classified as STSDI-low and -high groups for clinicopathological comparison. The STSDI showed no significant association with baseline clinicopathological features, including sex, age, pathological stage, and lymphovascular invasion. However, the STSDI-low group had significantly shorter recurrence-free survival (5-years RFS: 49.5% vs. 76.2%, p < 0.001) and disease-specific survival (5-years DSS: 53.6% vs. 81.5%, p < 0.001) than the STSDI-high group. In contrast, the application of Shannon's entropy without spatial consideration showed no correlation with patient outcomes. Moreover, low STSDI was an independent unfavorable predictor of tumor recurrence and disease-specific death (RFS; HR = 2.668, p < 0.005; DSS; HR = 3.057, p < 0.005), alongside the pathological stage. Further analysis showed a correlation between low STSDI and destructive growth patterns of cancer cells within tumors, potentially explaining the aggressive nature of STSDI-low tumors. In this study, we presented a novel approach for histological analysis of cancer tissues that revealed the prognostic significance of spatial tumor-stroma distribution in lung squamous cell carcinoma.

Predicting pathological grade of stage I pulmonary adenocarcinoma: a CT radiomics approach

Objectives

To investigate the value of CT radiomics combined with radiological features in predicting pathological grade of stage I invasive pulmonary adenocarcinoma (IPA) based on the International Association for the Study of Lung Cancer (IASLC) new grading system.

Methods

The preoperative CT images and clinical information of 294 patients with stage I IPA were retrospectively analyzed (159 training set; 69 validation set; 66 test set). Referring to the IASLC new grading system, patients were divided into a low/intermediate-grade group and a high-grade group. Radiomic features were selected by using the least absolute shrinkage and selection operator (LASSO), the logistic regression (LR) classifier was used to establish radiomics model (RM), clinical-radiological features model (CRM) and combined rad-score with radiological features model (CRRM), and visualized CRRM by nomogram. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the performance and fitness of models.

Results

In the training set, RM, CRM, and CRRM achieved AUCs of 0.825 [95% CI (0.735-0.916)], 0.849 [95% CI (0.772-0.925)], and 0.888 [95% CI (0.819-0.957)], respectively. For the validation set, the AUCs were 0.879 [95% CI (0.734-1.000)], 0.888 [95% CI (0.794-0.982)], and 0.922 [95% CI (0.835-1.000)], and for the test set, the AUCs were 0.814 [95% CI (0.674-0.954)], 0.849 [95% CI (0.750-0.948)], and 0.860 [95% CI (0.755-0.964)] for RM, CRM, and CRRM, respectively.

Conclusion

All three models performed well in predicting pathological grade, especially the combined model, showing CT radiomics combined with radiological features had the potential to distinguish the pathological grade of early-stage IPA.

The Grading System for Lung Adenocarcinoma: Brief Review of its Prognostic Performance and Future Directions

Histologic grading of tumors is associated with prognosis in many organs. In the lung, the most recent grading system proposed by International association for the Study of Lung Cancer (IASLC) and adopted by the World Health Organization (WHO) incorporates the predominant histologic pattern, as well as the presence of high-grade architectural patterns (solid, micropapillary, and complex glandular pattern) in proportions >20% of the tumor surface. This system has shown improved prognostic ability when compared with the prior grading system based on the predominant pattern alone, across different patient populations. Interobserver agreement is moderate to excellent, depending on the study. IASLC/WHO grading system has been shown to correlate with molecular alterations and PD-L1 expression in tumor cells. Recent studies interrogating gene expression has shown correlation with tumor grade and molecular alterations in the tumor microenvironment that can further stratify risk of recurrence. The use of machine learning algorithms to grade nonmucinous adenocarcinoma under this system has shown accuracy comparable to that of expert pulmonary pathologists. Future directions include evaluation of tumor grade in the context of adjuvant and neoadjuvant therapies, as well as the development of better prognostic indicators for mucinous adenocarcinoma.

Novel Insights Into the International Association for the Study of Lung Cancer Grading System for Lung Adenocarcinoma

The new grading system for lung adenocarcinoma proposed by the International Association for the Study of Lung Cancer (IASLC) defines prognostic subgroups on the basis of histologic patterns observed on surgical specimens. This study sought to provide novel insights into the IASLC grading system, with particular focus on recurrence-specific survival (RSS) and lung cancer-specific survival among patients with stage I adenocarcinoma. Under the IASLC grading system, tumors were classified as grade 1 (lepidic predominant with <20% high-grade patterns [micropapillary, solid, and complex glandular]), grade 2 (acinar or papillary predominant with <20% high-grade patterns), or grade 3 (≥20% high-grade patterns). Kaplan-Meier survival estimates, pathologic features, and genomic profiles were investigated for patients whose disease was reclassified into a higher grade under the IASLC grading system on the basis of the hypothesis that they would strongly resemble patients with predominant high-grade tumors. Overall, 423 (29%) of 1443 patients with grade 1 or 2 tumors classified based on the predominant pattern-based grading system had their tumors upgraded to grade 3 based on the IASLC grading system. The RSS curves for patients with upgraded tumors were significantly different from those for patients with grade 1 or 2 tumors (log-rank P < .001) but not from those for patients with predominant high-grade patterns (P = .3). Patients with upgraded tumors had a similar incidence of visceral pleural invasion and spread of tumor through air spaces as patients with predominant high-grade patterns. In multivariable models, the IASLC grading system remained significantly associated with RSS and lung cancer-specific survival after adjustment for aggressive pathologic features such as visceral pleural invasion and spread of tumor through air spaces. The IASLC grading system outperforms the predominant pattern-based grading system and appropriately reclassifies tumors into higher grades with worse prognosis, even after other pathologic features of aggressiveness are considered.

Prognostic impact of the IASLC grading system of lung adenocarcinoma: a systematic review and meta-analysis

AIMS

Tumour grading is an essential part of the pathologic assessment that promotes patient management. The International Association for the Study of Lung Cancer (IASLC) proposed a grading system for non-mucinous lung adenocarcinoma in 2020. We aimed to validate the prognostic impact of this novel grading system on overall survival (OS) and recurrence-free survival (RFS) based on literature data.

METHODS AND RESULTS

The review protocol was registered in PROSPERO (CRD42023396059). We aimed to identify randomized or non-randomized controlled trials published after 2020 comparing different IASLC grade categories in Medline, Embase, and CENTRAL. Hazard ratios (HRs) with 95% confidence intervals (CIs) of OS and RFS were pooled and the Quality In Prognosis Studies (QUIPS) tool was used to assess the risk of bias in the included studies. Ten articles were eligible for this review. Regarding OS estimates, grade 1 lung adenocarcinomas were better than grade 3 both in univariate and multivariate analyses (HROSuni = 0.19, 95% CI: 0.05-0.66, p = 0.009; HROSmulti = 0.21, 95% CI: 0.12-0.38, p < 0.001). Regarding RFS estimates, grade 3 adenocarcinomas had a worse prognosis than grade 1 in multivariate analysis (HRRFSmulti: 0.22, 95% CI: 0.14-0.35, p < 0.001).

CONCLUSION

The literature data and the result of our meta-analysis demonstrate the prognostic relevance of the IASLC grading system. This supports the inclusion of this prognostic parameter in daily routine worldwide.

Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unannotated pathology slides

Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human bias. Supervised deep learning approaches have proven powerful, but are inherently limited by the cost and quality of annotations used for training. Therefore, we present Histomorphological Phenotype Learning, a self-supervised methodology requiring no labels and operating via the automatic discovery of discriminatory features in image tiles. Tiles are grouped into morphologically similar clusters which constitute an atlas of histomorphological phenotypes (HP-Atlas), revealing trajectories from benign to malignant tissue via inflammatory and reactive phenotypes. These clusters have distinct features which can be identified using orthogonal methods, linking histologic, molecular and clinical phenotypes. Applied to lung cancer, we show that they align closely with patient survival, with histopathologically recognised tumor types and growth patterns, and with transcriptomic measures of immunophenotype. These properties are maintained in a multi-cancer study.

Invasion and Grading of Pulmonary Non-Mucinous Adenocarcinoma

Lung adenocarcinoma staging and grading were recently updated to reflect the link between histologic growth patterns and outcomes. The lepidic growth pattern is regarded as "in-situ," whereas all other patterns are regarded as invasive, though with stratification. Solid, micropapillary, and complex glandular patterns are associated with worse prognosis than papillary and acinar patterns. These recent changes have improved prognostic stratification. However, multiple pitfalls exist in measuring invasive size and in classifying lung adenocarcinoma growth patterns. Awareness of these limitations and recommended practices will help the pathology community achieve consistent prognostic performance and potentially contribute to improved patient management.

Proposed novel grading system for stage I invasive lung adenocarcinoma and a comparison with the 2020 IASLC grading system

BACKGROUND

Several studies have proposed grading systems for risk stratification of early-stage lung adenocarcinoma based on histological patterns. However, the reproducibility of these systems is poor in clinical practice, indicating the need to develop a new grading system which is easy to apply and has high accuracy in prognostic stratification of patients.

METHODS

Patients with stage I invasive nonmucinous lung adenocarcinoma were retrospectively collected from pathology archives between 2009 and 2016. The patients were divided into a training and validation set at a 6:4 ratio. Histological features associated with patient outcomes (overall survival [OS] and progression-free survival [PFS]) identified in the training set were used to construct a new grading system. The newly proposed system was validated using the validation set. Survival differences between subgroups were assessed using the log-rank test. The prognostic performance of the novel grading system was compared with two previously proposed systems using the concordance index.

RESULTS

A total of 539 patients were included in this study. Using a multioutcome decision tree model, four pathological factors, including the presence of tumor spread through air space (STAS) and the percentage of lepidic, micropapillary and solid subtype components, were selected for the proposed grading system. Patients were accordingly classified into three groups: low, medium, and high risk. The high-risk group showed a 5-year OS of 52.4% compared to 89.9% and 97.5% in the medium and low-risk groups, respectively. The 5-year PFS of patients in the high-risk group was 38.1% compared to 61.7% and 90.9% in the medium and low-risk groups, respectively. Similar results were observed in the subgroup analysis. Additionally, our proposed grading system provided superior prognostic stratification compared to the other two systems with a higher concordance index.

CONCLUSION

The newly proposed grading system based on four pathological factors (presence of STAS, and percentage of lepidic, micropapillary, and solid subtypes) exhibits high accuracy and good reproducibility in the prognostic stratification of stage I lung adenocarcinoma patients.

Survival benefit of adjuvant chemotherapy after resection of Stage I lung adenocarcinoma containing micropapillary components

BACKGROUND

The usefulness of postoperative adjuvant chemotherapy (ACT) for patients with stage I lung adenocarcinoma with micropapillary (MIP) components remains unclear. We analyzed whether postoperative ACT could reduce recurrence in patients with stage I lung adenocarcinoma with MIP components, thereby improving their overall survival (OS) and disease-free survival (DFS).

METHODS

Data for patients with pathologically confirmed stage I lung adenocarcinoma with MIP components from January 2012 to December 2018 were retrospectively analyzed. OS and DFS were analyzed in groups and subgroups.

RESULTS

Overall, 259 patients were enrolled. Patients who received ACT in stage IA showed significantly better survival than did those with no-adjuvant chemotherapy (NACT); (5-year OS 89.4% vs. 73.6%, p < 0.001; 5-year DFS 87.2% vs. 66.0%, p = 0.008). A difference was also observed for in-stage IB patients (5-year OS 82.0% vs. 51.8%, p = 0.001; 5-year DFS 76.0% vs. 41.11 %, p = 0.004). In subgroup analysis based on the proportion of MIP components, patients with 1%-5% MIP components had a significantly better prognosis in the ACT group than in the NACT group (5-year OS 82.4% vs. 66.0%, p = 0.005; 5-year DFS 76.5% vs. 49.1%, p = 0.032). A similar difference was observed for patients with MIP ≥5% (5-year OS 80.7% vs. 47.8%, p = 0.009; 5-year DFS 73.11% vs. 43.5%, p = 0.007).

CONCLUSION

Among patients with stage I lung adenocarcinoma with MIP components, those who received ACT showed significant survival benefits compared to those without ACT. Patients with lung adenocarcinoma with MIP components could benefit from ACT when the MIP was ≥1%.

Updates on lung adenocarcinoma: invasive size, grading and STAS

Advancements in the classification of lung adenocarcinoma have resulted in significant changes in pathological reporting. The eighth edition of the tumour-node-metastasis (TNM) staging guidelines calls for the use of invasive size in staging in place of total tumour size. This shift improves prognostic stratification and requires a more nuanced approach to tumour measurements in challenging situations. Similarly, the adoption of new grading criteria based on the predominant and highest-grade pattern proposed by the International Association for the Study of Lung Cancer (IASLC) shows improved prognostication, and therefore clinical utility, relative to previous grading systems. Spread through airspaces (STAS) is a form of tumour invasion involving tumour cells spreading through the airspaces, which has been highly researched in recent years. This review discusses updates in pathological T staging, adenocarcinoma grading and STAS and illustrates the utility and limitations of current concepts in lung adenocarcinoma.

TTF-1 status in early-stage lung adenocarcinoma is an independent predictor of relapse and survival superior to tumor grading

OBJECTIVES

Thyroid transcription factor 1 (TTF-1) is a well-established independent prognostic factor in lung adenocarcinoma (LUAD), irrespective of stage. This study aims to determine if TTF-1's prognostic impact is solely based on histomorphological differentiation (tumor grading) or if it independently relates to a biologically more aggressive phenotype. We analyzed a large bi-centric LUAD cohort to accurately assess TTF-1's prognostic value in relation to tumor grade.

PATIENTS AND METHODS

We studied 447 patients with resected LUAD from major German lung cancer centers (Berlin and Cologne), correlating TTF-1 status and grading with clinical, pathologic, and molecular data, alongside patient outcomes. TTF-1's impact was evaluated through univariate and multivariate Cox regression. Causal graph analysis was used to identify and account for potential confounders, improving the statistical estimation of TTF-1's predictive power for clinical outcomes.

RESULTS

Univariate analysis revealed TTF-1 positivity associated with significantly longer disease-free survival (DFS) (median log HR -0.83; p = 0.018). Higher tumor grade showed a non-significant association with shorter DFS (median log HR 0.30; p = 0,62 for G1 to G2 and 0.68; p = 0,34 for G2 to G3). In multivariate analysis, TTF-1 positivity resulted in a significantly longer DFS (median log HR -0.65; p = 0.05) independent of all other parameters, including grading. Adjusting for potential confounders as indicated by the causal graph confirmed the superiority of TTF-1 over tumor grading in prognostics power.

CONCLUSIONS

TTF-1 status predicts relapse and survival in LUAD independently of tumor grading. The prognostic power of tumor grading is limited to TTF-1-positive patients, and the effect size of TTF-1 surpasses that of tumor grading. We recommend including TTF1 status as a prognostic factor in the diagnostic guidelines of LUAD.

High-risk histological subtype-related FAM83A hijacked FOXM1 transcriptional regulation to promote malignant progression in lung adenocarcinoma

Background

According to the histopathology, lung adenocarcinoma (LUAD) could be divided into five distinct pathological subtypes, categorized as high-risk (micropapillary and solid) group, intermediate-risk (acinar and papillary) group, and low-risk (lepidic) group. Despite this classification, there is limited knowledge regarding the role of transcription factors (TFs) in the molecular regulation of LUAD histology patterns.

Methods

Publish data was mined to explore the candidate TFs associated with high-risk histopathology in LUAD, which was validated in tissue samples. Colony formation, CCK8, EdU, transwell, and matrigel assays were performed to determine the biological function of FAM83A in vitro. Subcutaneous tumor-bearing in BALB/c nude mice and xenograft perivitelline injection in zebrafish were utilized to unreal the function of FAM83A in vivo. We also performed chromatin immunoprecipitation (ChIP), dual-luciferase reporter, and rescue assays to uncover the underline mechanism of FAM83A. Immunohistochemistry (IHC) was performed to confirm the oncogenic role of FAM83A in clinical LUAD tissues.

Results

Screening the transcriptional expression data from TCGA-LUAD, we focus on the differentially expressed TFs across the divergent pathological subtypes, and identified that the expression of FAM83A is higher in patients with high-risk groups compared with those with intermediate or low-risk groups. The FAM83A expression is positively correlated with worse overall survival, progression-free survival, and advanced stages. Gain- and loss-of-function assays revealed that FAM83A promoted cell proliferation, invasion, and migration of tumor cell lines both in vivo and in vitro. Pathway enrichment analysis shows that FAM83A expression is significantly enriched in cell cycle-related pathways. The ChIP and luciferase reporter assays revealed that FAM83A hijacks the promoter of FOXM1 to progress the malignant LUAD, and the rescue assay uncovered that the function of FAM83A is partly dependent on FOXM1 regulation. Additionally, patients with high FAM83A expression positively correlated with higher IHC scores of Ki-67 and FOXM1, and patients with active FAM83A/FOXM1 axis had poor prognoses in LUAD.

Conclusions

Taken together, our study revealed that the high-risk histological subtype-related FAM83A hijacks FOXM1 transcriptional regulation to promote malignant progression in lung adenocarcinoma, which implies targeting FAM83A/FOXM1 is the therapeutic vulnerability.

A pretreatment prediction model of grade 3 tumors classed by the IASLC grading system in lung adenocarcinoma

PURPOSE

The new grading system for invasive nonmucinous lung adenocarcinoma (LUAD) in the 2021 World Health Organization Classification of Thoracic Tumors was based on a combination of histologically predominant subtypes and high-grade components. In this study, a model for the pretreatment prediction of grade 3 tumors was established according to new grading standards.

METHODS

We retrospectively collected 399 cases of clinical stage I (cStage-I) LUAD surgically treated in Tianjin Chest Hospital from 2015 to 2018 as the training cohort. Besides, the validation cohort consists of 216 patients who were collected from 2019 to 2020. These patients were also diagnosed with clinical cStage-I LUAD and underwent surgical treatment at Tianjin Chest Hospital. Univariable and multivariable logistic regression analyses were used to select independent risk factors for grade 3 adenocarcinomas in the training cohort. The nomogram prediction model of grade 3 tumors was established by R software.

RESULTS

In the training cohort, there were 155 grade 3 tumors (38.85%), the recurrence-free survival of which in the lobectomy subgroup was better than that in the sublobectomy subgroup (P = 0.034). After univariable and multivariable analysis, four predictors including consolidation-to-tumor ratio, CEA level, lobulation, and smoking history were incorporated into the model. A nomogram was established and internally validated by bootstrapping. The Hosmer-Lemeshow test result was χ2 = 7.052 (P = 0.531). The C-index and area under the receiver operating characteristic curve were 0.708 (95% CI: 0.6563-0.7586) for the training cohort and 0.713 (95% CI: 0.6426-0.7839) for the external validation cohort.

CONCLUSIONS

The nomogram prediction model of grade 3 LUAD was well fitted and can be used to assist in surgical or adjuvant treatment decision-making.

Spatial transcriptomics delineates molecular features and cellular plasticity in lung adenocarcinoma progression

Indolent (lepidic) and aggressive (micropapillary, solid, and poorly differentiated acinar) histologic subtypes often coexist within a tumor tissue of lung adenocarcinoma (LUAD), but the molecular features associated with different subtypes and their transitions remain elusive. Here, we combine spatial transcriptomics and multiplex immunohistochemistry to elucidate molecular characteristics and cellular plasticity of distinct histologic subtypes of LUAD. We delineate transcriptional reprogramming and dynamic cell signaling that determine subtype progression, especially hypoxia-induced regulatory network. Different histologic subtypes exhibit heterogeneity in dedifferentiation states. Additionally, our results show that macrophages are the most abundant cell type in LUAD, and identify different tumor-associated macrophage subpopulations that are unique to each histologic subtype, which might contribute to an immunosuppressive microenvironment. Our results provide a systematic landscape of molecular profiles that drive LUAD subtype progression, and demonstrate potentially novel therapeutic strategies and targets for invasive lung adenocarcinoma.

Correlation of Programmed Death-Ligand 1 Expression With Lung Adenocarcinoma Histologic and Molecular Subgroups in Primary and Metastatic Sites

Programmed death-ligand 1 (PD-L1) expression in terms of the tumor proportion score (TPS) is the main predictive biomarker approved for immunotherapy against lung nonsmall cell carcinoma. Although some studies have explored the associations between histology and PD-L1 expression in pulmonary adenocarcinoma, they have been limited in sample size and/or extent of examined histologic variables, which may have resulted in conflicting information. In this observational retrospective study, we identified primary and metastatic lung adenocarcinoma cases in the span of 5 years and tabulated the detailed histopathologic features, including pathological stage, tumor growth pattern, tumor grade, lymphovascular and pleural invasion, molecular alterations, and the associated PD-L1 expression for each case. Statistical analyses were performed to detect associations between PD-L1 and these features. Among 1658 cases, 643 were primary tumor resections, 751 were primary tumor biopsies, and 264 were metastatic site biopsies or resections. Higher TPS significantly correlated with high-grade growth patterns, grade 3 tumors, higher T and N stage, presence of lymphovascular invasion, and presence of MET and TP53 alterations, whereas lower TPS correlated with lower-grade tumors and presence of EGFR alterations. There was no difference in PD-L1 expression in matched primary and metastases, although higher TPS was observed in metastatic tumors due to the presence of high-grade patterns in these specimens. TPS showed a strong association with a histologic pattern. Higher-grade tumors had higher TPS, which is also associated with more aggressive histologic features. Tumor grade should be kept in mind when selecting cases and blocks for PD-L1 testing.

Advances in diagnosis and prediction for aggression of pure solid T1 lung cancer

A growing number of early-stage lung cancers presenting as malignant pulmonary nodules have been diagnosed because of the increased adoption of low-dose spiral computed tomography. But pure solid T1 lung cancer with ≤3 cm in the greatest dimension is not always at an early stage, despite its small size. This type of cancer can be highly aggressive and is associated with pathological involvement, metastasis, postoperative relapse, and even death. However, it is easily misdiagnosed or delay diagnosed in clinics and thus poses a serious threat to human health. The percentage of nodal or extrathoracic metastases has been reported to be >20% in T1 lung cancer. As such, understanding and identifying the aggressive characteristics of pure solid T1 lung cancer is crucial for prevention, diagnosis, and therapeutic strategies, and beneficial to improving the prognosis. With the widespread of lung cancer screening, these highly invasive pure solid T1 lung cancer will become the main advanced lung cancer in future. However, there is limited information regarding precision medicine on how to identify these "early-stage" aggressive lung cancers. To provide clinicians with new insights into early recognition and intervention of the highly invasive pure solid T1 lung cancer, this review summarizes its clinical characteristics, imaging, pathology, gene alterations, immune microenvironment, multi-omics, and current techniques for diagnosis and prediction.

A CT-Based Radiomics Nomogram Combined with Clinic-Radiological Characteristics for Preoperative Prediction of the Novel IASLC Grading of Invasive Pulmonary Adenocarcinoma

RATIONALE AND OBJECTIVES

The novel International Association for the Study of Lung Cancer (IASLC) grading system of invasive lung adenocarcinoma (ADC) demonstrated a remarkable prognostic effect and enabled numerous patients to benefit from adjuvant chemotherapy. We sought to build a CT-based nomogram for preoperative prediction of the IASLC grading.

MATERIALS AND METHODS

This work retrospectively analyzed the CT images and clinical data of 303 patients with pathologically confirmed invasive ADC. The histological subtypes and radiological characteristics of the patients were re-evaluated. Radiomics features were extracted, and the optimal subset of features was established by ANOVA, spearman correlation analysis, and the least absolute shrinkage and selection operator (LASSO). Univariate and multivariate analyses identified the independent clinical and radiological variables. Finally, multivariate logistic regression analysis incorporated clinical, radiological, and optimal radiomics features into the nomogram. Receiver operating characteristic (ROC) curve, and accuracy were applied to assess the model's performance. Decision curve analysis (DCA), and calibration curve were applied to assess the clinical usefulness.

RESULTS

Nine selected CT image features were used to develop the radiomics model. The accuracy, precision, sensitivity, and specificity of the radiomics model outperformed the clinic-radiological model in the training and testing sets. Integrating Radscore with independent radiological characteristics showed higher prediction performance than clinic-radiological characteristics alone in the training (AUC, 0.915 vs. 0.882; DeLong, p < 0.05) and testing (AUC, 0.838 vs. 0.782; DeLong, p < 0.05) sets. Good calibration and decision curve analysis demonstrated the clinical usefulness of the nomogram.

CONCLUSION

Radiomics features effectively predict high-grade ADC. The combined nomogram may facilitate selecting patients who benefit from adjuvant treatment.

Overcoming the Interobserver Variability in Lung Adenocarcinoma Subtyping: A Clustering Approach to Establish a Ground Truth for Downstream Applications

CONTEXT.—

The accurate identification of different lung adenocarcinoma histologic subtypes is important for determining prognosis but can be challenging because of overlaps in the diagnostic features, leading to considerable interobserver variability.

OBJECTIVE.—

To provide an overview of the diagnostic agreement for lung adenocarcinoma subtypes among pathologists and to create a ground truth using the clustering approach for downstream computational applications.

DESIGN.—

Three sets of lung adenocarcinoma histologic images with different evaluation levels (small patches, areas with relatively uniform histology, and whole slide images) were reviewed by 17 international expert lung pathologists and 1 pathologist in training. Each image was classified into one or several lung adenocarcinoma subtypes.

RESULTS.—

Among the 4702 patches of the first set, 1742 (37%) had an overall consensus among all pathologists. The overall Fleiss κ score for the agreement of all subtypes was 0.58. Using cluster analysis, pathologists were hierarchically grouped into 2 clusters, with κ scores of 0.588 and 0.563 in clusters 1 and 2, respectively. Similar results were obtained for the second and third sets, with fair-to-moderate agreements. Patches from the first 2 sets that obtained the consensus of the 18 pathologists were retrieved to form consensus patches and were regarded as the ground truth of lung adenocarcinoma subtypes.

CONCLUSIONS.—

Our observations highlight discrepancies among experts when assessing lung adenocarcinoma subtypes. However, a subsequent number of consensus patches could be retrieved from each cluster, which can be used as ground truth for the downstream computational pathology applications, with minimal influence from interobserver variability.

A Simplified Version of the IASLC Grading System for Invasive Pulmonary Adenocarcinomas With Improved Prognosis Discrimination

Tumor grading enables better management of patients and treatment options. The International Association for the Study of Lung Cancer (IASLC) Pathology Committee has recently released a 3-tier grading system for invasive pulmonary adenocarcinoma consisting of predominant histologic patterns plus a cutoff of 20% of high-grade components including solid, micropapillary, and complex glandular patterns. The goal of this study was to validate the prognostic value of the new IASLC grading system and to compare its discriminatory performance to the predominant pattern-based grading system and a simplified version of the IASLC grading system without complex glandular patterns. This was a single-site retrospective study based on a 20-year data collection of patients that underwent lung cancer surgery. All invasive pulmonary adenocarcinomas confirmed by the histologic review were evaluated in a discovery cohort (n=676) and a validation cohort (n=717). The median duration of follow-up in the combined dataset (n=1393) was 7.5 years. The primary outcome was overall survival after surgery. The 3 grading systems had strong and relatively similar predictive performance, but the best parsimonious model was the simplified IASLC grading system (log-rank P =1.39E-13). The latter was strongly associated with survival in the validation set ( P =1.1E-18) and the combined set ( P =5.01E-35). We observed a large proportion of patients upgraded to the poor prognosis group using the IASLC grading system, which was attenuated when using the simplified IASLC grading system. In conclusion, we identified a histologic simpler classification for invasive pulmonary adenocarcinomas that outperformed the recently proposed IASLC grading system. A simplified grading system is clinically convenient and will facilitate widespread implementation.

Establishment and validation of nomograms for predicting survival of lung invasive adenocarcinoma based on the level of pathological differentiation: a SEER cohort-based analysis

BACKGROUND

The pathological differentiation of invasive adenocarcinoma (IAC) has been linked closely with epidemiological characteristics and clinical prognosis. However, the current models cannot accurately predict IAC outcomes and the role of pathological differentiation is confused. This study aimed to establish differentiation-specific nomograms to explore the effect of IAC pathological differentiation on overall survival (OS) and cancer-specific survival (CSS).

METHODS

The data of eligible IAC patients between 1975 and 2019 were collected from the Surveillance, Epidemiology, and End Results (SEER) database, and randomly divided in a ratio of 7:3 into a training cohort and a validation cohort. The associations between pathological differentiation and other clinical characteristics were evaluated using chi-squared test. The OS and CSS analyses were performed using the Kaplan-Meier estimator, and the log-rank test was used for nonparametric group comparisons. Multivariate survival analysis was performed using a Cox proportional hazards regression model. The discrimination, calibration, and clinical performance of nomograms were assessed by area under receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA).

RESULTS

A total of 4,418 IAC patients (1,001 high-differentiation, 1,866 moderate-differentiation, and 1,551 low-differentiation) were identified. Seven risk factors [age, sex, race, tumor-node-metastasis (TNM) stage, tumor size, marital status, and surgery] were screened to construct differentiation-specific nomograms. Subgroup analyses showed that disparate pathological differentiation played distinct roles in prognosis, especially in patients with older age, white race, and higher TNM stage. The AUC of nomograms for OS and CSS in the training cohort were 0.817 and 0.835, while in the validation cohort were 0.784 and 0.813. The calibration curves showed good conformity between the prediction of the nomograms and the actual observations. DCA results indicated that these nomogram models could be used as a supplement to the prediction of the TNM stage.

CONCLUSIONS

Pathological differentiation should be considered as an independent risk factor for OS and CSS of IAC. Differentiation-specific nomogram models with good discrimination and calibration capacity were developed in the study to predict the OS and CSS in 1-, 3- and 5-year, which could be used predict prognosis and select appropriate treatment options.

Heterogeneous expression of predictive biomarkers PD-L1 and TIGIT in non-mucinous lung adenocarcinoma and corresponding lymph node metastasis: A challenge for clinical biomarker testing

The use of immune checkpoint inhibitors (ICI) targeting the PD-L1:PD1 interaction revolutionized tumor treatment by re-activating the anti-tumoral capacity of the immune system. Assessment of tumor mutational burden, microsatellite instability, or expression of the surface marker PD-L1 have been used to predict individual response to ICI therapy. However, the predicted response does not always correspond to the actual therapy outcome. We hypothesize that tumor heterogeneity might be a major cause of this inconsistency. In this respect we recently demonstrated that PD-L1 shows heterogenous expression in the different growth patterns of non-small cell lung cancer (NSCLC) - lepidic, acinar, papillary, micropapillary and solid. Furthermore, additional inhibitory receptors, like T cell immunoglobulin and ITIM domain (TIGIT), appear to be heterogeneously expressed and affect the outcome of anti-PD-L1 treatment. Given this heterogeneity in the primary tumor, we set out to analyze the situation in corresponding lymph node metastases, since these are often used to obtain biopsy material for tumor diagnosis, staging and molecular analysis. Again, we observed heterogeneous expression of PD-1, PD-L1, TIGIT, Nectin-2 and PVR in relation to different regions and growth pattern distribution that varied between the primary tumor and their metastases. Together, our study underscores the complex situation regarding the heterogeneity of NSCLC samples and suggest that the analysis of a small biopsy from lymph node metastases may not be sufficient to ensure a reliable prediction of ICI therapy success.

Relationship Between the Diffusing Capacity of the Lung for Carbon Monoxide (DLCO) and Lung Adenocarcinoma Patterns: New Possible Insights

INTRODUCTION

This study aimed to evaluate a potential relationship between the diffusing capacity of the lung for carbon monoxide (DLCO) and the aggressiveness of lung adenocarcinoma (ADC).

METHODS

Patients who underwent radical surgery for lung ADC between 2001 and 2018 were retrospectively reviewed. DLCO values were dichotomized into DLCO_low (<80% of predicted) and DLCO_normal (≥80%). Relationships between DLCO and ADC histopathological features, clinical features, as well as with overall survival (OS), were evaluated.

RESULTS

Four-hundred and sixty patients were enrolled, of which 193 (42%) were included in the DLCO_low group. DLCO_low was associated with smoking status, low FEV₁, micropapillary and solid ADC, tumour grade 3, high tumour lymphoid infiltrate and presence of tumour desmoplasia. In addition, DLCO values were higher in low-grade ADC and progressively decreased in intermediate and high-grade ADC (p=0.024). After adjusting for clinical variables, at multivariable logistic regression analysis, DLCO_low still showed a significant correlation with high lymphoid infiltrate (p=0.017), presence of desmoplasia (p=0.065), tumour grade 3 (p=0.062), micropapillary and solid ADC subtypes (p=0.008). To exclude the association between non-smokers and well-differentiated ADC, the relationship between DLCO and histopathological ADC patterns was confirmed in the subset of 377 former and current smokers (p=0.021). At univariate analysis, gender, DLCO, FEV₁, ADC histotype, tumour grade, stage, pleural invasion, tumour necrosis, tumour desmoplasia, lymphatic and blood invasion were significantly related with OS. At multivariate analysis, only gender (p<0.001), tumour stage (p<0.001) and DLCO (p=0.050) were significantly related with the OS.

CONCLUSIONS

We found a relationship between DLCO and ADC patterns as well as with tumour grade, tumour lymphoid infiltrate and desmoplasia, suggesting that lung damage may be associated with tumour aggressiveness.

The prognostic value of histopathology in invasive lung adenocarcinoma: a comparative review of the main proposed grading systems

INTRODUCTION

An accurate histological evaluation of invasive lung adenocarcinoma is essential for a correct clinical and pathological definition of the tumour. Different grading systems have been proposed to predict the prognosis of invasive lung adenocarcinoma.

AREAS COVERED

Invasive non mucinous lung adenocarcinoma is often morphologically heterogeneous, consisting of complex combinations of architectural patterns with different proportions. Several grading systems for non-mucinous lung adenocarcinoma have been proposed, being the main based on architectural differentiation and the predominant growth pattern. Herein we perform a thorough review of the literature using PubMed, Scopus and Web of Science and we highlight the peculiarities and the differences between the main grading systems and compare the data about their prognostic value. In addition, we carried out an evaluation of the proposed grading systems for less common histological variants of lung adenocarcinoma, such as fetal adenocarcinoma and invasive mucinous adenocarcinoma.

EXPERT OPINION

The current IASLC grading system, based on the combined score of predominant growth pattern plus high-grade histological pattern, shows the stronger prognostic significance than the previous grading systems in invasive non mucinous lung adenocarcinoma.

Comparison of small biopsy and cytology specimens: Subtyping of pulmonary adenocarcinoma

Objectives

The aims of this study was to investigate the use of cytologic samples for subclassification of lung adenocarcinoma and the cytologic-histologic correlation in lung adenocarcinoma subtypes using small samples.

Methods and Methods

Cytological characteristics of lung adenocarcinoma subtypes were summarized by a literature review. Cytology samples from 115 patients with lung adenocarcinoma confirmed by small biopsies were classified by subtype. The diagnostic concordance of subtypes between biopsy and cytology samples was assessed.

Results

Among the 115 cases, 62 (53.9%) had acinar predominant pattern, 16 (13.9%) were papillary predominant pattern, 29 (25.2%) had solid predominant pattern, 3 (2.6%) had lepidic predominant pattern, and 5 (4.3%) had micropapillary predominant pattern. All corresponding cytologic samples were classified into five subtypes based on cytomorphology features, with concordance rates of 74.2% (46 patients) in c-acinar subtype, 56.3% (nine patients) in c-papillary subtype, 24.1% (seven patients) in c-solid subtype, 66.7% (two patients) in c-lepidic subtype, and 40% (two patients) in c-micropapillary subtype. Collectively, the cytology and small biopsy concordance rate was approximately 57.4%.

Conclusion

Subtyping of lung adenocarcinoma using cytologic specimens is challenging and the consistency rate varies with the subtype. Acinar predominant tumors have an excellent cytologic-histologic correlation compared to tumors with predominant solid or micropapillary pattern. Evaluating cytomorphologic features of different lung adenocarcinoma subtypes can reduce the false-negative rate of lung adenocarcinoma, particularly for the mild, atypical micropapillary subtype, and improve diagnostic accuracy.

Proposal of a revised International Association for the Study of Lung Cancer grading system in pulmonary non-mucinous adenocarcinoma: The importance of the lepidic proportion

OBJECTIVES

We aimed to measure the validity of the International Association for the Study of Lung Cancer (IASLC) grading system in Korean patients and propose a modification for an increase of its predictability, especially in grade 2 patients.

MATERIALS AND METHODS

From 2012 to 2017, histopathologic characteristics of 1358 patients with invasive pulmonary adenocarcinoma (stage I-III) from two institutions were retrospectively reviewed and re-classified according to the IASLC grading system. Considering the amount of the lepidic proportion, the validity of the revised model (Lepidic-10), derived from the training cohort (hospital A), was measured using the validation cohort (hospital B). Its predictability was compared to that of the IASLC system.

RESULTS

Of the 1358 patients, 259 had a recurrence, and 189 died during follow-up. The Harrell's concordance index and area under the curve of the IASLC system were 0.685 and 0.699 for recurrence-free survival (RFS) and 0.669 and 0.679 for death, respectively. From the training cohort, the IASLC grade 2 patients were divided into grades 2a and 2b (Lepidic-10 model) with a 10 % lepidic pattern. This new model further distinguished patients in both institutions that had better performance than the IASLC grading (Hospital A, p < 0.001 for RFS and death; Hospital B, p = 0.0215 for RFS, p = 0.0429 for death).

CONCLUSION

The IASLC grading system was easily applicable; its clinical use in predicting the prognosis of Korean patients with pulmonary adenocarcinoma was validated. Furthermore, the introduction of the lepidic proportion as an additional criterion to differentiate grade 2 patients improved its predictability.

Validation of the novel International Association for the Study of Lung Cancer grading system and prognostic value of filigree micropapillary and discohesive growth pattern in invasive pulmonary adenocarcinoma

INTRODUCTION

The Pathology Committee of the International Association for the Study of Lung Cancer (IASLC) proposed a new histological grading system based on the combination of predominant and high-grade patterns in 2020.

MATERIALS AND METHODS

Pathological sections from 631 patients with stage I-III invasive lung adenocarcinoma were reviewed. We then determined the histological grade according to the new grading system and confirmed the pathological features that included the filigree micropapillary and discohesive growth pattern. Applying of the novel IASLC grading system in prognosis stratification was verified and the clinical significance of the pathological characteristics was explored.

RESULTS

Cox multivariable analysis revealed that in the stage I-III invasive lung adenocarcinoma, the IASLC grading system was significantly associated with disease-free survival (DFS) [hazard ratio (HR) = 1.419; 95 % confidence interval (CI): 1.040-1.937; P = 0.027] and overall survival (OS) (HR = 1.899; 95 % CI: 1.168-3.087; P = 0.010). In patients with IASLC Grades 1 and 2, the simultaneous presence of filigree micropapillary and discohesive growth pattern was significantly correlated with DFS (HR = 1.899; 95 % CI:1.168-3.087; P = 0.010). However, the filigree micropapillary and discohesive growth pattern did not affect the OS (HR = 2.786; P = 0.317). The competitive risk model revealed that in the stage I cohort, the simultaneous presence of filigree micropapillary and discohesive growth pattern was a risk factor for recurrence and metastasis [sub- distribution HR (SHR) = 1.987; 95 %CI: 1.122-3.518; P = 0.019].

CONCLUSION

Our study verified that the new prognostic stratification system was an effective stratification tool. Filigree micropapillary and discohesive growth pattern may also be risk factors for DFS, postoperative recurrence and metastasis.

Prognosis of resected invasive mucinous adenocarcinoma compared with the IASLC histologic grading system for invasive nonmucinous adenocarcinoma: Surgical database study in the TKIs era in Korea

BACKGROUND

The prognosis of invasive mucinous adenocarcinoma (IMA) remains controversial and should be clarified by comparison with the International Association for the Study of Lung Cancer (IASLC) histologic grading system for invasive nonmucinous adenocarcinoma (INMA).

METHODS

This study included patients with IMA who underwent curative resection. Their clinicopathological outcomes were compared with those of patients with INMA. Propensity score matching was performed to compare the prognosis of IMA with IASLC grade 2 or 3. Kaplan-Meier survival curves and log-rank tests were used to analyze recurrence-free survival (RFS) and overall survival (OS).

RESULTS

The prognoses of IMA and IASLC grade 2 were similar in terms of RFS and OS. Although patients with IMA had better RFS than patients with IASLC grade 3, the OS was not significantly different. After propensity score matching, IMA demonstrated similar RFS to IASLC grade 2 but superior to IASLC grade 3; there was no difference in the OS compared with grades 2/3. Multivariate analysis revealed that tumor size (hazard ratio [HR] = 1.20, p = 0.028), lymphovascular invasion (HR = 127.5, p = 0.003), and maximum standardized uptake value (HR = 1.24, p = 0.005) were poor prognostic predictors for RFS. Patients with IMA demonstrated RFS similar to and significantly better than that of patients with IASLC grades 2 and 3, respectively. For OS, IMA prognosis was between that of IASLC grades 2 and 3.

CONCLUSIONS

Since the prognosis of IMA among lung adenocarcinomas appears to be relatively worse, further clinical studies investigating IMA-specific treatment and follow-up plans are necessary to draw more inferences.

Associations of IFT20 and GM130 protein expressions with clinicopathological features and survival of patients with lung adenocarcinoma

Background

Lung cancer is the leading cause of malignancy-related mortality and lung adenocarcinoma accounts for about 40% of lung malignancies. The aim of this study was to investigate the associations of intraflagellar transport protein 20 (IFT20) and Golgi matrix protein 130 (GM130) expression with clinicopathological features and survival in patients with lung adenocarcinoma.

Methods

The expressions of IFT20 and GM130 protein in cancerous and matched adjacent lung tissues of 235 patients with lung adenocarcinoma were assessed by tissue microarray and immunohistochemistry, which were indicated by the mean optical density (IOD/area), the rate of positive staining cells and staining intensity score. The correlation between IFT20 and GM130 protein was assessed by Spearman’s rank correlation. Associations of IFT20 and GM130 protein expression with clinicopathological features of patients were analyzed by multivariate logistic regression models. The survival analysis of patients was performed by Cox proportional hazard regression models.

Results

With adjustment for multiple potential confounders, each one-point increase in IFT20 protein staining intensity score was significantly associated with 32% and 29% reduced risk for TNM stage in II ~ IV and lymphatic metastasis of patients, respectively (P < 0.05). And each one-point increase in GM130 protein staining intensity score was associated with a significant reduction in the risk of poor differentiation and tumors size > 7 cm by 29% and 38% for lung adenocarcinoma patients, respectively (P < 0.05). In stratified Cox model analysis, enhanced IFT20 staining intensity score was significantly decreased the risk of death by 16% for patients without distant metastasis. And elevated the IOD/area of GM130 expression significantly decreased the death risk of lung adenocarcinoma patients with tumor size > 7 cm or distant metastasis by 54% and 65%, respectively (P < 0.05).

Conclusion

IFT20 and GM130 protein expressions were negatively associated with tumor differentiated types, size, TNM stage and lymphatic metastasis of lung adenocarcinoma. Both IFT20 and GM130 proteins have some protective effects on the survival of lung adenocarcinoma patients with specific clinicopathological features.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09905-6.

The IASLC Proposed Grading System Accurately Predicts Prognosis and Mediastinal Nodal Metastasis in Patients With Clinical Stage I Lung Adenocarcinoma

The International Association for the Study of Lung Cancer (IASLC) recently proposed a new grading system for lung adenocarcinoma (LUAD). We aimed to validate the prognostic performance of the grading system and explore its role in guiding the strategy of lymph node (LN) dissection. We retrospectively reviewed 1029 patients with clinical stage I LUAD who underwent surgery between 2011 and 2013. The association between mediastinal nodal metastasis and grading system was evaluated. To investigate the value of the grading system in guiding LN dissection strategies, 3 pathologists evaluated the feasibility of identifying the grading system using frozen section (FS). The differences in prognosis between all neighboring grades were highly significant based on the grading system ( P <0.001). Notably, almost no grade 1 LUAD (1.4%) had pN2 disease, whereas higher rates were found in grade 2 LUAD (9.6%) and grade 3 LUAD (18.3%) ( P <0.001). Multivariate logistic regression analysis revealed that higher tumor grade was an independent predictor of mediastinal nodal metastasis ( P =0.002). Moreover, limited mediastinal LN dissection had equivalent prognosis in grade 1 LUAD, but significantly worse prognosis in grade 2 and grade 3 LUAD than systematic mediastinal LN dissection. The overall accuracy of using intraoperative FS to identify the IASLC grading system was 85.4% (κ=0.765) with substantial agreement. The IASLC grading system could accurately stratify prognosis and predict mediastinal nodal metastasis in patients with clinical stage I LUAD. FS was feasible for identifying the IASLC grading system.

Proteogenomic analysis of lung adenocarcinoma reveals tumor heterogeneity, survival determinants, and therapeutically relevant pathways

We present a deep proteogenomic profiling study of 87 lung adenocarcinoma (LUAD) tumors from the United States, integrating whole-genome sequencing, transcriptome sequencing, proteomics and phosphoproteomics by mass spectrometry, and reverse-phase protein arrays. We identify three subtypes from somatic genome signature analysis, including a transition-high subtype enriched with never smokers, a transversion-high subtype enriched with current smokers, and a structurally altered subtype enriched with former smokers, TP53 alterations, and genome-wide structural alterations. We show that within-tumor correlations of RNA and protein expression associate with tumor purity and immune cell profiles. We detect and independently validate expression signatures of RNA and protein that predict patient survival. Additionally, among co-measured genes, we found that protein expression is more often associated with patient survival than RNA. Finally, integrative analysis characterizes three expression subtypes with divergent mutations, proteomic regulatory networks, and therapeutic vulnerabilities. This proteogenomic characterization provides a foundation for molecularly informed medicine in LUAD.

Validation Study of New IASLC Histology Grading System in Stage I Non-Mucinous Adenocarcinoma Comparing With Minimally Invasive Adenocarcinoma

BACKGROUND

A new histologic grading system for pulmonary non-mucinous invasive adenocarcinoma was proposed by the International Association for the Study of Lung Cancer (IASLC). We evaluated its clinical impact on prognosis in stage I patients, including minimally invasive adenocarcinoma (MIA).

PATIENTS AND METHODS

919 patients underwent surgery for lung adenocarcinoma between 2012 and 2019. Stage I patients (n = 500) were retrospectively reviewed. They were divided into 4 categories: MIA and 3 new IASLC grades (grades 1-3). Cox proportional hazards analysis was performed to identify risk factors associated with recurrence and mortality. Furthermore, we compared the predictability of the IASLC grading system with different models that are based on the clinicopathologic characteristics (baseline model), TNM staging, and predominant histologic pattern. The area under the receiver operating characteristic curve (AUC) was calculated for comparison.

RESULTS

Recurrence-free survival (RFS) and overall survival (OS) were significantly stratified by the IASLC grading system in patients with stage I adenocarcinoma (P < .001 and P = .003, respectively). In multivariate analyses, IASLC grade 3 was a significant factor for RFS (hazard ratio [HR] 3.18, P < .001) and OS (HR 2.31, P = .013). The AUCs of the new IASLC model were 0.781 for recurrence and 0.770 for mortality, compared with those of the predominant pattern (0.769 for recurrence, 0.747 for death) and TNM staging (0.762 for recurrence, 0.747 for death).

CONCLUSION

The IASLC grading system effectively predicted the prognosis of early-stage adenocarcinoma compared with previous models. The IASLC classification appears to improve the current system; therefore, precise pathologic examination for early-stage adenocarcinoma is warranted.

Prognostic role of standard uptake value according to pathologic features of lung adenocarcinoma

OBJECTIVE

To evaluate the influence of lung adenocarcinoma second predominant pattern on the maximal standard uptake value (SUVmax) and its prognostic effect in different histologic groups.

METHODS

We retrospectively collected surgically resected pathologic stage I and II lung adenocarcinoma from nine European institutions. Only patients who underwent preoperative PET-CT and with available information regarding SUVmax of T (SUVmaxT) and N1 (SUVmaxN1) component were included.

RESULTS

We enrolled 344 patients with lung adenocarcinoma. SUVmaxT did not show any significant relation according to the second predominant pattern (p = 0.139); this relationship remained nonsignificant in patients with similar predominant pattern. SUVmaxT influenced the disease-free survival in the whole cohort (p = 0.002) and in low- and intermediate-grade predominant pattern groups (p = 0.040 and p = 0.008, respectively). In the high-grade predominant pattern cohort and in the pathologic N1 cases, SUVmaxT lost its prognostic power. SUVmaxN1 did not show any significant correlation with predominant and second predominant patterns and did not have any prognostic impact on DFS.

CONCLUSIONS

SUVmaxT is influenced only by the adenocarcinoma predominant pattern, but not by second predominant pattern. Concurrently, in high-grade predominant pattern and pN1 group the prognostic power of SUVmaxT becomes nonsignificant.

Impact of High-Grade Patterns in Early-Stage Lung Adenocarcinoma: A Multicentric Analysis

OBJECTIVE

The presence of micropapillary and solid adenocarcinoma patterns leads to a worse survival and a significantly higher tendency to recur. This study aims to assess the impact of pT descriptor combined with the presence of high-grade components on long-term outcomes in early-stage lung adenocarcinomas.

METHODS

We retrospectively collected data of consecutive resected pT1-T3N0 lung adenocarcinoma from nine European Thoracic Centers. All patients who underwent a radical resection with lymph-node dissection between 2014 and 2017 were included. Differences in Overall Survival (OS) and Disease-Free Survival (DFS) and possible prognostic factors associated with outcomes were evaluated also after performing a propensity score matching to compare tumors containing non-high-grade and high-grade patterns.

RESULTS

Among 607 patients, the majority were male and received a lobectomy. At least one high-grade histological pattern was seen in 230 cases (37.9%), of which 169 solid and 75 micropapillary. T1a-b-c without high-grade pattern had a significant better prognosis compared to T1a-b-c with high-grade pattern (p = 0.020), but the latter had similar OS compared to T2a (p = 0.277). Concurrently, T1a-b-c without micropapillary or solid patterns had a significantly better DFS compared to those with high-grade patterns (p = 0.034), and it was similar to T2a (p = 0.839). Multivariable analysis confirms the role of T descriptor according to high-grade pattern both for OS (p = 0.024; HR 1.285 95% CI 1.033-1.599) and DFS (p = 0.003; HR 1.196, 95% CI 1.054-1.344, respectively). These results were confirmed after the propensity score matching analysis.

CONCLUSIONS

pT1 lung adenocarcinomas with a high-grade component have similar prognosis of pT2a tumors.

The new IASLC grading system for invasive non-mucinous lung adenocarcinoma is a more useful indicator of patient survival compared with previous grading systems

BACKGROUND

The International Association for the Study of Lung Cancer (IASLC) Pathology Committee recently proposed a new histological grading system for invasive lung adenocarcinoma (ADC). This study evaluated the usefulness of this grading system.

METHODS

A total of 395 patients with ADC were examined. ADCs were reclassified based on comprehensive histological subtyping according to the IASLC grading system. We evaluated the following histological grading systems for invasive ADC: the architectural (Arch), Sica's grading, and IASLC grading systems. Multivariate analyses of overall and recurrence-free survival (RFS) based on these three grading systems were performed using Cox proportional hazards models.

RESULTS

Multivariate analysis showed that all three grading systems were useful for predicting the outcomes of patients at all stages. However, the IASLC grading system was superior to the Arch and Sica's grading systems in differentiating grade 3 from grade 1 ADCs in terms of both overall survivals (IASLC vs. Arch vs. Sica's grading systems: hazard ratio [HR] = 3.77 vs. 3.03 vs. 2.63) and RFS (HR = 4.25 vs. 2.69 vs. 2.4).

CONCLUSION

The newly proposed IASLC grading system was useful for predicting patient outcomes and was superior to the other grading systems in detecting high-grade malignancy.

Clinicopathologic and genomic features of high-grade pattern and their subclasses in lung adenocarcinoma

INTRODUCTION

Recent lung adenocarcinoma (LUAD) grading system proposed by the International Association for the Study of Lung Cancer (IASLC) has emphasized the proportion of high-grade patterns (HGPs). We aimed to evaluate the clinicopathologic and genomic characteristics associated with HGP which has not yet been fully investigated.

METHODS

Tissue samples from 174 patients who underwent surgical resection of LUAD from January to December 2015 were histologically evaluated. Proportions of HGPs, including solid, micropapillary, cribriform, and complex glandular patterns, were individually quantified. Prognostic implications of HGP proportion, both as a continuous variable and as subclasses divided by cutoffs of 20%, 50%, and 90% (low-intermediate grade [LIG], HGP <20%; high grade 1 [HG1], 20-<50%, HG2, 50-<90%; HG3, ≥90%) were evaluated. Different clinicopathologic factors and genomic alterations according to the HGP subclasses were assessed.

RESULTS

Relative hazards of the HGP gradually elevated as its proportion increased over 20%, the cut-off value established by the IASLC grading system, and the cancer-specific overall survival (OS) of HG1 subclass was not significantly decreased compared to the LIG subclass on univariate analysis. However, further subgrouping showed significantly increased frequencies of male, advanced stage tumors, lymphovascular invasion, and spread through alveolar space in higher HGP subclasses. Also, common LUAD driver mutations, particularly EGFR mutations, were less frequent, whereas alterations in TP53 and cell cycle pathway-related genes were more frequent. Higher HGP subclasses and TP53 gene alteration were associated with shorter cancer-specific OS and RFS in multivariate survival analysis.

CONCLUSIONS

HGP subclasses of LUAD displayed distinct clinicopathological characteristics and genomic alterations, including TP53 and cell cycle pathway, emphasizing the clinical value of these subclasses in LUAD. Higher HGP subclass and alteration in TP53 may be markers of poor post-operative survival.

Prognostic and predictive value of the newly proposed grading system of invasive pulmonary adenocarcinoma in Chinese patients: a retrospective multicohort study

Our aim was to validate and analyze the prognostic impact of the novel International Association for the Study of Lung Cancer (IASLC) Pathology Committee grading system for invasive pulmonary adenocarcinomas (IPAs) in Chinese patients and to evaluate its utility in predicting a survival benefit from adjuvant chemotherapy (ACT). In this multicenter, retrospective, cohort study, we included 926 Chinese patients with completely resected stage I IPAs and classified them into three groups (Grade 1, n = 119; Grade 2, n = 431; Grade 3, n = 376) according to the new grading system proposed by the IASLC. Recurrence-free survival (RFS) and overall survival (OS) were estimated by the Kaplan-Meier method, and prognostic factors were assessed using univariable and multivariable Cox proportional hazards models. All included cohorts were well stratified in terms of RFS and OS by the novel grading system. Furthermore, the proposed grading system was found to be independently associated with recurrence and death in the multivariable analysis. Among patients with stage IB IPA (N = 490), the proposed grading system identified patients who could benefit from ACT but who were undergraded by the adenocarcinoma (ADC) classification. The novel grading system not only demonstrated prognostic significance in stage I IPA in a multicenter Chinese cohort but also offered clinical value for directing therapeutic decisions regarding adjuvant chemotherapy.

Relationships between SUVmax of lung adenocarcinoma and different T stages, histological grades and pathological subtypes: a retrospective cohort study in China

OBJECTIVES

Cancer cell has aberrant metabolism. The purpose of this study aimed to investigate relationships between maximum standard uptake value (SUVmax）of ¹⁸fluoro-2-deoxy-d-glucose and T stages, histological grades and pathological subtypes of lung adenocarcinoma.

DESIGN

Retrospective cohort study, employing the Kruskal-Wallis, Bonferroni-Dunn and Mann-Whitney tests to compare SUVmax of different T stages, histological grades and pathological subtypes of lung adenocarcinoma.

SETTING

The outpatients who had aberrant positron emission tomography/CT (PET/CT) images in chest were enrolled this study from August 2016 to November 2018 in Shanghai, China.

PARTICIPANT

Initial 11 270 patients with suspected lung cancer who underwent PET/CT examinations were surveyed. A total of 1454 patients who were diagnosed as lung adenocarcinoma by pathologist were included in this project.

PRIMARY OUTCOME MEASURES

SUVmax value at different tumour-node-metastasis stages of lung adenocarcinoma before surgery.

RESULTS

The mean SUVmax of patients with lung adenocarcinoma was significantly elevated with the increase in T stages. There were significant evident differences in SUVmax among T1a-T1c (p<0.05). However, after the staging of patients was more than T1 stage, SUVmax of T2a, T2b, T2 visceral pleural invasion, T3 and T4 had not dramatic changes. SUVmax value of lung adenocarcinoma in the same T stage group was the highest in patients with the high grade of malignancy and solid-predominant invasive adenocarcinoma.

CONCLUSIONS

SUVmax value was significantly associated with T stages, grades of malignancy and pathological subtypes of lung adenocarcinoma.

Percentage of Newly Proposed High-Grade Patterns Is Associated with Prognosis of Pathological T1-2N0M0 Lung Adenocarcinoma

OBJECTIVE

To evaluate the prognostic value of the percentage of high-grade patterns (micropapillary, solid, and complex glands) in early-stage lung adenocarcinoma (LUAD).

METHODS

A total of 1049 patients undergoing radical surgery with pathological T1-2N0M0 LUAD were screened retrospectively, and 191 patients were involved in the final analysis. Disease-free survival (DFS) was evaluated using the Kaplan-Meier curve and Cox regression analysis. The optimal cut-off value was determined using maximally selected rank statistics.

RESULTS

The entire cohort was divided into quartile groups based on the percentage of high-grade patterns: Group 1 (≤ 30%), Group 2 (31-55%), Group 3 (56-85%), and Group 4 (≥ 86%). There were significant differences in smoking history (P = 0.041), EGFR mutations (P < 0.001), and ALK rearrangement (P = 0.010) between the four groups, but no significant differences in other clinicopathological features. Kaplan-Meier analysis showed that a higher percentage of high-grade patterns predicted worse DFS (P = 0.001), and multivariate analysis indicated that the percentage of high-grade patterns was an independent predictor (Group 2 vs. Group 1, HR = 2.136, P = 0.228; Group 3 vs. Group 1, HR = 3.355, P = 0.035; Group 4 vs. Group 1, HR = 5.147, P = 0.003, respectively). A cut-off value of 20% (P = 0.048) and 50% (P <0.001) for high-grade patterns were tested, and both revealed a significant difference in distinguishing DFS between subgroups.

CONCLUSIONS

The percentage of high-grade patterns is associated with the prognosis of early-stage invasive LUAD. A higher percentage indicates a worse prognosis.

A narrative review of prognosis prediction models for non-small cell lung cancer: what kind of predictors should be selected and how to improve models?

Objective

To discover potential predictors and explore how to build better models by summarizing the existing prognostic prediction models of non-small cell lung cancer (NSCLC).

Background

Research on clinical prediction models of NSCLC has experienced explosive growth in recent years. As more predictors of prognosis are discovered, the choice of predictors to build models is particularly important, and in the background of more applications of next-generation sequencing technology, gene-related predictors are widely used. As it is more convenient to obtain samples and follow-up data, the prognostic model is preferred by researchers.

Methods

PubMed and the Cochrane Library were searched using the items “NSCLC”, “prognostic model”, “prognosis prediction”, and “survival prediction” from 1 January 1980 to 5 May 2021. Reference lists from articles were reviewed and relevant articles were identified.

Conclusions

The performance of gene-related models has not obviously improved. Relative to the innovation and diversity of predictors, it is more important to establish a highly stable model that is convenient for clinical application. Most of the prevalent models are highly biased and referring to PROBAST at the beginning of the study may be able to significantly control the bias. Existing models should be validated in a large external dataset to make a meaningful comparison.

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.

Utility of Newly Proposed Grading System From International Association for the Study of Lung Cancer for Invasive Lung Adenocarcinoma

Introduction

The International Association for the Study of Lung Cancer proposed a new grading criteria for invasive adenocarcinoma. However, its utility has not been validated.

Methods

Patients who underwent complete resection of lung adenocarcinoma were included in this study. Then, they were divided into the following three groups on the basis of the criteria recently proposed by the International Association for the Study of Lung Cancer: grade 1, lepidic predominant tumor, with less than 20% of high-grade patterns; grade 2, acinar or papillary predominant tumor, with less than 20% of high-grade patterns; and grade 3, any tumor with greater than or equal to 20% of high-grade patterns.

Results

Recurrence-free survival (RFS) was significantly different among the proposed grades (p < 0.001). The RFS of patients upgrading from current grade 2 (papillary or acinar predominant tumor) to proposed grade 3 (5-y RFS, 65.2%) was significantly worse than that of patients with proposed grade 2 (77.1%, hazard ratio = 1.882, 95% confidence interval: 1.236–2.866) but not significantly different from that of patients with grade 3 in both the current (micropapillary or solid predominant tumor) and proposed criteria (53.2%, hazard ratio = 0.761, 95% confidence interval: 0.456–1.269). Among patients with pathologic stage 0 or I, RFS was well stratified by the new grading system (p < 0.001) but not among patients with stage II or III (p = 0.334). In the multivariable analysis, the new grading was not a predictive factor of RFS.

Conclusions

Although the proposed grading system well stratified RFS in patients with pathologic stage 0 or I lung adenocarcinoma, there is room for improvement.

Validation of the Novel International Association for the Study of Lung Cancer Grading System for Invasive Pulmonary Adenocarcinoma and Association With Common Driver Mutations

INTRODUCTION

We aimed to validate the use of the novel grading system proposed by the International Association for the Study of Lung Cancer pathology committee for prognosis stratification of invasive pulmonary adenocarcinomas (ADCs) in Chinese patients. Correlations between the grading system, common driver mutations, and adjuvant chemotherapy (ACT) were also investigated.

METHODS

From 2008 to 2016, the histologic patterns of a large cohort of 950 patients with invasive ADCs (stage I-III) were retrospectively analyzed and classified according to the proposed grading system. Subsequently, tumor grading was correlated with genetic data, ACT, and patient outcome.

RESULTS

Compared with conventional predominant pattern-based groups, the novel grading system carried improved survival discrimination (area under the curve = 0.768 for recurrence-free survival and 0.775 for overall survival). The area under the curve was not further improved when incorporated lymphovascular invasion status. EGFR mutations (p < 0.001) were correlated with moderate grade, whereas KRAS mutations (p = 0.041) and ALK fusions (p = 0.021) were significantly more prevalent in poor grade. The reclassification of the grading system based on EGFR mutation status revealed excellent survival discrimination (p < 0.001). In particular, patients on stage Ib to III with novel high-grade ADCs had an improved prognosis with ACT.

CONCLUSIONS

The novel International Association for the Study of Lung Cancer grading system is a practical and efficient discriminator for patient prognosis and should be part of an integrated pathologic-genetic subtyping to improve survival prediction. In addition, it may support patient stratification for aggressive adjuvant chemotherapy.

Pulmonary Functional Imaging for Lung Adenocarcinoma: Combined MRI Assessment Based on IVIM-DWI and OE-UTE-MRI

Purpose

The goal of current study was to introduce noninvasive and reproducible MRI methods for in vivo functional assessment of lung adenocarcinoma (LUAD).

Methods

Forty-four patients with pathologically confirmed LUAD were included in this study. All the lesions were classified as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma (IA). The IA lesions were further divided into five subtype patterns, including acinar, lepidic, papillary, micropapillary and solid. Tumors were grouped depending on predominant subtype: low grade (AIS, MIA or lepidic predominant), intermediate grade (papillary or acinar predominant) and high grade (micropapillary, or solid predominant). Spirometry was performed according to American Thoracic Society guidelines. For each patient, Intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) analysis and oxygen-enhanced MRI (OE-MRI) analysis were performed. Spearman's test was used to assess the relationship between a) whole lung mean percent signal enhancement (PSE) and pulmonary function tests (PFTs) parameters; b) IVIM-derived parameters and PFTs parameters; c) tumor mean PSE and IVIM-derived parameters. Kruskal -Wallis tests were applied to test the difference of tumor mean PSE and IVIM-derived parameters between different histological tumor grades. Receiver operating characteristics (ROC) analysis was used to evaluate the diagnostic performance.

Results

Whole lung mean PSE was significantly positively correlated with PFTs parameters (r = 0.40 ~ 0.44, P < 0.05). f value derived from IVIM-DWI was significantly negatively correlated with PFTs parameters (r = -0.38 ~ -0.47, P < 0.05). Both tumor mean PSE (P = 0.030 < 0.05) and f (P = 0.022 < 0.05) could differentiate different histological grades. f was negatively correlated with tumor mean PSE (r = -0.61, P < 0.001). For the diagnostic performance, the combination of tumor mean PSE and f outperformed than using tumor mean PSE or f alone in both sensitivity and area under the ROC curve.

Conclusions

The combined measurement of OE-MRI and IVIM-DWI may serve as a promising method for the noninvasive and non-radiation evaluation of pulmonary function. Quantitative analyses achieved by OE-MRI and IVIM-DWI offer an approach of the classification of LUAD subtypes.