Both the presence of a micropapillary component and the micropapillary predominant subtype predict poor prognosis after lung adenocarcinoma resection: a meta-analysis

The impact of postoperative adjuvant therapy on EGFR-mutated stage IA lung adenocarcinoma with micropapillary pathological subtypes

BACKGROUND

Micropapillary (MPP) adenocarcinoma is considered one of the most aggressive pathological types of lung adenocarcinoma (LADC). This retrospective study aimed to evaluate the prognostic significance and benefit of postoperative adjuvant therapy (PAT) in stage IA LADC patients with different proportions of MPP components.

MATERIALS AND METHODS

We retrospectively examined clinical stage IA LADC patients who underwent surgical resection between August 2012 and December 2019. In terms of the proportion of MPP components (TPM), the tumors were reclassified into three categories: MPP patterns absent (TPMN); low proportions of MPP components (TPML); and high proportions of MPP components (TPMH). The dates of recurrence and metastasis were identified based on physical examinations and were confirmed by histopathological examination.

RESULTS

Overall, 505 (TPMN, n = 375; TPML, n = 92; TPMH, n = 38) patients harboring EGFR mutations were enrolled in the study. Male sex (P = 0.044), high pathological stage (P < 0.001), and MPP pathological subtype (P < 0.001) were more frequent in the TPM-positive (TPMP) group than in the TPM-negative (TPMN) group. Five-year disease-free survival (DFS) rates were significantly lower in the TPMP group than in the TPMN group (84.5% vs. 93.4%, P = 0.006). In addition, patients with high proportions (greater than 10%) of MPP components had worse overall survival (OS) (91.0% vs. 98.9%, P = 0.025) than those with low proportions (5%≤ TPM ≤ 10%). However, postoperative EGFR tyrosine kinase inhibitors (TKIs) or adjuvant chemotherapy (ACT) cannot improve DFS and OS between EGFR-mutated patients with different proportions of MPP components.

CONCLUSION

MPP was related to earlier recurrence and shortened survival time, even in stage IA. Further research needs a larger sample size to clarify that EGFR-mutated stage IA patients with MPP components obtain survival benefits from adjuvant therapy.

A pro-metastatic tRNA fragment drives aldolase A oligomerization to enhance aerobic glycolysis in lung adenocarcinoma

Despite being the leading cause of lung cancer-related deaths, the underlying molecular mechanisms driving metastasis progression are still not fully understood. Transfer RNA-derived fragments (tRFs) have been implicated in various biological processes in cancer. However, the role of tRFs in lung adenocarcinoma (LUAD) remains unclear. Our study identified a tRF, tRF-Val-CAC-024, associated with the high-risk component of LUAD, through validation using 3 cohorts. Our findings demonstrated that tRF-Val-CAC-024 acts as an oncogene in LUAD. Mechanistically, tRF-Val-CAC-024 was revealed to bind to aldolase A (ALDOA) dependent on Q125/E224 and promote the oligomerization of ALDOA, resulting in increased enzyme activity and enhanced aerobic glycolysis in LUAD cells. Additionally, we provide preliminary evidence of its potential clinical value by investigating the therapeutic effects of tRF-Val-CAC-024 antagomir-loaded lipid nanoparticles (LNPs) in cell-line-derived xenograft models. These results could enhance our understanding of the regulatory mechanisms of tRFs in LUAD and provide a potential therapeutic target.

Sublobar resection for lung adenocarcinoma less than 2 cm containing solid or micropapillary components radiologically presented as consolidation-to-tumor ratio (CTR) ≤0.25 [ground-glass opacity (GGO)]

Background

The suitability of sublobar resection as a surgical approach for early-stage non-small cell lung cancer (NSCLC) remains unclear. This study investigated the feasibility of sublobar resection in patients with pathological-stage IA adenocarcinoma less than 2 cm characterized by a high-risk pathological subtype but exhibiting radiologically noninvasive features.

Methods

We conducted a retrospective review of patients diagnosed with pathological stage IA lung adenocarcinoma who underwent surgical intervention between 2013 and 2017. The inclusion criteria included a maximum tumor diameter of 2.0 cm or less, a consolidation-to-tumor ratio (CTR) of 0.25 or less, and a histopathological confirmation of a solid or micropapillary component. Patients were categorized into sublobar resection and lobectomy groups, and propensity score matching was employed to mitigate potential confounders. The primary endpoints were lung cancer-specific survival (LCSS) and overall survival (OS).

Results

The study comprised 149 patients, with 84 in the lobectomy group and 65 in the limited resection group. In the overall cohort, the 5-year LCSS was 100% for both groups, while the 5-year OS was 97.6% (95% CI: 94.41-100.00%) in the lobectomy group and 100% in the sublobar resection group (P=0.21). After propensity score matching, the LCSS remained at 100% for both groups, and the 5-year OS was 97.14% in the lobectomy group and 100% in the sublobar resection group (P=0.32).

Conclusions

Based on our experience, for lung adenocarcinoma containing solid/micropapillary subtype, a size less than 2 cm, and a CTR ≤0.25, the oncological outcomes appeared to be comparable between sublobar resection and lobectomy, suggesting that sublobar resection might serve as an equivalent alternative to lobectomy for such lesions.

CT morphological features and histogram parameters to predict micropapillary or solid components in stage IA lung adenocarcinoma

Objectives

This study aimed to construct prediction models based on computerized tomography (CT) signs, histogram and morphology features for the diagnosis of micropapillary or solid (MIP/SOL) components of stage IA lung adenocarcinoma (LUAC) and to evaluate the models' performance.

Methods

This clinical retrospective study included image data of 376 patients with stage IA LUAC based on postoperative pathology, admitted to Putian First Hospital from January 2019 to June 2023. According to the presence of MIP/SOL components in postoperative pathology, patients were divided into MIP/SOL+ and MIP/SOL- groups. Cases with tumors ≤ 3 cm and ≤ 2 cm were separately analyzed. Each subgroup of patients was then randomly divided into a training set and a test set in a ratio of 7:3. The training set was used to build the prediction model, and the test set was used for internal validation.

Results

For tumors ≤ 3 cm, ground-glass opacity (GGO) [odds ratio (OR) = 0.244; 95% confidence interval (CI): 0.103-0.569; p = 0.001], entropy (OR = 1.748; 95% CI: 1.213-2.577; p = 0.004), average CT value (OR = 1.002; 95% CI: 1.000-1.004; p = 0.002), and kurtosis (OR = 1.240; 95% CI: 1.023-1.513; p = 0.030) were independent predictors of MIP/SOL components of stage IA LUAC. The area under the ROC curve (AUC) of the nomogram prediction model for predicting MIP/SOL components was 0.816 (95% CI: 0.756-0.877) in the training set and 0.789 (95% CI: 0.689-0.889) in the test set. In contrast, for tumors ≤ 2 cm, kurtosis was no longer an independent predictor. The nomogram prediction model had an AUC of 0.811 (95% CI: 0.731-0.891) in the training set and 0.833 (95% CI: 0.733-0.932) in the test set.

Conclusion

For tumors ≤ 3 cm and ≤ 2 cm, GGO, average CT value, and entropy were the same independent influencing factors in predicting MIP/SOL components of stage IA LUAC. The nomogram prediction models have potential diagnostic value for identifying MIP/SOL components of early-stage LUAC.

Clinicopathologic and Molecular Characteristics of HER2 (ERBB2)-Altered Non-Small Cell Lung Cancer: Implications for Precision Medicine

The heterogeneous relationship between protein expression, amplification, and mutations in human epidermal growth factor receptor 2 (HER2) in non-small cell lung cancer (NSCLC) and the optimal methods for detecting these alterations remain unclear. We aimed to elucidate the clinicopathological and molecular characteristics of HER2-altered NSCLC and investigate practical approaches for identifying patients who might benefit from HER2-targeted therapies. Using next-generation sequencing data from 1680 individuals, we searched for patients with HER2-altered NSCLCs, including amplifications and mutations. Clinicopathological data and tissue slides were reviewed. Immunohistochemistry (IHC) and silver in situ hybridization were performed according to the American Society of Clinical Oncology/College of American Pathologists guidelines. Our analysis identified 89 (5.3%) patients with HER2-altered NSCLCs, comprising 30 (1.8%) with amplification and 59 (3.6%) mutations, and they were compared with 165 control patients. Of the 59 HER2-mutated cases, 52 harbored tyrosine kinase domain (TKD) mutations, primarily HER2 exon 20 insertions. HER2 TKD alterations were associated with younger age, female sex, nonsmoking status, adenocarcinoma with a micropapillary pattern, lung-to-lung metastasis, and poor overall survival. The 33 patients with TKD mutations and 3 with non-TKD point mutations showed incomplete or complete membranous HER2 immunoreactivity (1+ and 2+, 61.07%). Six patients exhibiting amplifications had an IHC score of ≤2+ despite their high copy numbers and concomitantly displayed other actionable EGFR, KRAS, SMARCA4, and other HER2 mutations. These HER2-altered NSCLCs with molecular coalterations showed heterogeneous patterns through HER2 IHC and silver in situ hybridization. Therefore, next-generation sequencing should be used to identify HER2 mutations in patients with NSCLC who present with concomitant alterations. In addition, the above clinicopathological characteristics and HER2 IHC results can be valuable determinants for identifying patients with HER2-altered NSCLC. These insights hold promise for the development of more effective diagnostic and therapeutic strategies for this complex subset of NSCLC patients.

Computed tomography-based 3D convolutional neural network deep learning model for predicting micropapillary or solid growth pattern of invasive lung adenocarcinoma

PURPOSE

To investigate the value of a computed tomography (CT)-based deep learning (DL) model to predict the presence of micropapillary or solid (M/S) growth pattern in invasive lung adenocarcinoma (ILADC).

MATERIALS AND METHODS

From June 2019 to October 2022, 617 patients with ILADC who underwent preoperative chest CT scans in our institution were randomly placed into training and internal validation sets in a 4:1 ratio, and 353 patients with ILADC from another institution were included as an external validation set. Then, a self-paced learning (SPL) 3D Net was used to establish two DL models: model 1 was used to predict the M/S growth pattern in ILADC, and model 2 was used to predict that pattern in ≤ 2-cm-diameter ILADC.

RESULTS

For model 1, the training cohort's area under the curve (AUC), accuracy, recall, precision, and F1-score were 0.924, 0.845, 0.851, 0.842, and 0.843; the internal validation cohort's were 0.807, 0.744, 0.756, 0.750, and 0.743; and the external validation cohort's were 0.857, 0.805, 0.804, 0.806, and 0.804, respectively. For model 2, the training cohort's AUC, accuracy, recall, precision, and F1-score were 0.946, 0.858, 0.881,0.844, and 0.851; the internal validation cohort's were 0.869, 0.809, 0.786, 0.794, and 0.790; and the external validation cohort's were 0.831, 0.792, 0.789, 0.790, and 0.790, respectively. The SPL 3D Net model performed better than the ResNet34, ResNet50, ResNeXt50, and DenseNet121 models.

CONCLUSION

The CT-based DL model performed well as a noninvasive screening tool capable of reliably detecting and distinguishing the subtypes of ILADC, even in small-sized tumors.

Feasibility of UTE-MRI-based radiomics model for prediction of histopathologic subtype of lung adenocarcinoma: in comparison with CT-based radiomics model

OBJECTIVES

To assess the feasibility of the UTE-MRI radiomic model in predicting the micropapillary and/or solid (MP/S) patterns of surgically resected lung adenocarcinoma.

MATERIALS AND METHODS

We prospectively enrolled 74 lesions from 71 patients who underwent UTE-MRI and CT before curative surgery for early lung adenocarcinoma. For conventional radiologic analysis, we analyzed the longest lesion diameter and lesion characteristics at both UTE-MRI and CT. Radiomic features were extracted from the volume of interest of the lesions and Rad-scores were generated using the least absolute shrinkage and selection operator with fivefold cross-validation. Six models were constructed by combining the conventional radiologic model, UTE-MRI Rad-score, and CT Rad-score. The areas under the curves (AUCs) of each model were compared using the DeLong method. Early recurrence after curative surgery was analyzed, and Kaplan-Meier survival analysis was performed.

RESULTS

Twenty-four lesions were MP/S-positive, and 50 were MP/S-negative. The longitudinal size showed a small systematic difference between UTE-MRI and CT, with fair intermodality agreement of lesion characteristic (kappa = 0.535). The Rad-scores of the UTE-MRI and CT demonstrated AUCs of 0.84 and 0.841, respectively (p = 0.98). Among the six models, mixed conventional, UTE-MRI, and CT Rad-score model showed the highest diagnostic performance (AUC = 0.879). In the survival analysis, the high- and low-risk groups were successfully divided by the Rad-score in UTE-MRI (p = 0.01) and CT (p < 0.01).

CONCLUSION

UTE-MRI radiomic model predicting MP/S positivity is feasible compared with the CT radiomic model. Also, it was associated with early recurrence in the survival analysis.

CLINICAL RELEVANCE STATEMENT

A radiomic model utilizing UTE-MRI, which does not present a radiation hazard, was able to successfully predict the histopathologic subtype of lung adenocarcinoma, and it was associated with the patient's recurrence-free survival.

KEY POINTS

• No studies have reported the ultrashort echo time (UTE)-MRI-based radiomic model for lung adenocarcinoma. • The UTE-MRI Rad-score showed comparable diagnostic performance with CT Rad-score for predicting micropapillary and/or solid histopathologic pattern. • UTE-MRI is feasible not only for conventional radiologic analysis, but also for radiomics analysis.

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%.

EGFR co-mutation is associated with the risk of recurrence in invasive lung adenocarcinoma with the micropapillary component

BACKGROUND

Invasive lung adenocarcinoma (LUAD) patients with the micropapillary (MPP) component tend to have extremely poor prognosis. To optimize clinical outcomes, a better understanding of specific concurrent gene alterations and their impact on the prognosis of patients with the MPP component is necessary.

METHOD

A total of 621 Chinese patients with surgically resected invasive LUAD who underwent genetic testing for lung cancer were enrolled in this retrospective study. The genomic profiling of major lung cancer-related genes based on next-generation sequencing (NGS) was carried out on formalin-fixed paraffin-embedded tumor samples.

RESULT

Among 621 patients with invasive LUAD, 154 (24.8%, 154/621) had the MPP component. We found that PIK3CA (4.5% vs 1.3%), KRAS (9.1% vs 4.7%), and ROS1 (2.6% vs 0.4%) were more frequent in patients with the MPP component than those without the MPP component (P < 0.05). The co-mutation occurred in 66 patients (10.6%, 66/621), of which 19 patients with the MPP component. Most of them were EGFR co-mutations (89.5%, 17/19), including EGFR and PIK3CA, EGFR and ERBB2, and other types. Patients with the MPP component who harbored EGFR co-mutations showed significantly worse recurrence-free survival (RFS) than single EGFR mutation (median RFS 20.1 vs 30.5 months; hazard ratio [HR]: 8.008; 95% confidence interval [CI]: 1.322-48.508).

CONCLUSIONS

Patients with the MPP component harbored the co-mutation of driver genes had a higher risk of recurrence after surgery, especially in patients with EGFR co-mutation. EGFR co-mutation was a significant prognostic factor for RFS in patients with the MPP component.

Micropapillary or solid component predicts worse prognosis in pathological IA stage lung adenocarcinoma: A meta-analysis

BACKGROUND

Micropapillary and solid patterns indicate worse survival in lung adenocarcinoma patients, even in pathological stage IB patients. However, whether the presence of micropapillary or solid components is related to worse prognosis in pathological IA stage lung adenocarcinoma remains unclear.

METHODS

Several databases were searched up to December 31, 2022 for relevant studies investigating the association between micropapillary and solid components and the survival of IA stage lung adenocarcinoma patients. Primary and secondary outcomes are disease-free survival (DFS) and overall survival (OS), respectively. Hazard ratios (HRs) and 95% confident intervals (CIs) were combined, and subgroup analysis stratified by the pathological subtype and proportion of components was further performed.

RESULTS

A total of 19 studies with 12,562 cases were included. Pooled results indicated that micropapillary or solid components obviously predicted worse DFS (HR = 2.40, 95% CI: 1.96-2.94, P < .001) and OS (HR = 2.30, 95% CI: 1.68-3.15, P < .001). Subgroup analysis based on pathological subtype showed that both micropapillary and solid components were significantly associated with worse DFS (micropapillary: HR = 2.70, 95% CI: 1.70-4.28, P < .001; solid: HR = 3.98, 95% CI: 2.10-7.54, P < .001) and OS (micropapillary: HR = 2.29, 95% CI: 1.17-4.48, P = .015; solid: HR = 4.18, 95% CI: 1.72-10.17, P = .002). In addition, further subgroup analysis stratified by the proportion of micropapillary and solid components (>5%/1% or predominant) showed similar results.

CONCLUSION

Micropapillary and solid patterns predicted a significantly worse prognosis in pathological IA stage lung adenocarcinoma patients.

Prognostic factors of resected pathological stage I lung adenocarcinoma: evaluating subtypes and PD-L1/CD155 expression

We aimed to compare the prognostic impacts of adenocarcinoma subtypes, programmed death-ligand I (PD-L1), and CD155 expression on patients with resected pathological stage (p-stage) I lung adenocarcinoma. In total, 353 patients with completely resected p-stage I lung adenocarcinomas were retrospectively reviewed. The expression levels of PD-L1 and CD155 in tumour cells from each adenocarcinoma subtype were evaluated using several clinicopathological and histological features, such as the presence of a micropapillary pattern. A total of 52 patients (14.7%) had PD-L1-positive tumours, whereas 128 patients (36.3%) had CD155-positive tumours, with a tumour proportion score of 5% for both PD-L1 and CD155 expression. Compared with patients with other adenocarcinoma subtypes, those with solid-predominant adenocarcinomas were significantly more positive for PD-L1 and CD155. Multivariate analysis showed that PD-L1 expression status was significantly associated with progression-free survival and overall survival, whereas CD155 expression and the presence of a micropapillary pattern were not significantly associated with either parameter. Patients with PD-L1-positive tumours had poorer prognoses than those with CD155-positive tumours. Moreover, PD-L1 and CD155 were significantly expressed in solid-predominant adenocarcinomas. The results of this study suggest that immune checkpoint inhibitors can be used as adjuvants in the treatment of patients with p-stage I adenocarcinoma.

Standardized Classification of Lung Adenocarcinoma Subtypes and Improvement of Grading Assessment Through Deep Learning

The histopathologic distinction of lung adenocarcinoma (LADC) subtypes is subject to high interobserver variability, which can compromise the optimal assessment of patient prognosis. Therefore, this study developed convolutional neural networks capable of distinguishing LADC subtypes and predicting disease-specific survival, according to the recently established LADC tumor grades. Consensus LADC histopathologic images were obtained from 17 expert pulmonary pathologists and one pathologist in training. Two deep learning models (AI-1 and AI-2) were trained to predict eight different LADC classes. Furthermore, the trained models were tested on an independent cohort of 133 patients. The models achieved high precision, recall, and F1 scores exceeding 0.90 for most of the LADC classes. Clear stratification of the three LADC grades was reached in predicting the disease-specific survival by the two models, with both Kaplan-Meier curves showing significance (P = 0.0017 and 0.0003). Moreover, both trained models showed high stability in the segmentation of each pair of predicted grades with low variation in the hazard ratio across 200 bootstrapped samples. These findings indicate that the trained convolutional neural networks improve the diagnostic accuracy of the pathologist and refine LADC grade assessment. Thus, the trained models are promising tools that may assist in the routine evaluation of LADC subtypes and grades in clinical practice.

Estimating the cure proportion of stage IA lung adenocarcinoma: a population-based study

BACKGROUND

We aimed to investigate the factors influencing the cure, recurrence, and metastasis rates of stage IA lung adenocarcinoma, using a mixed cure model.

METHODS

A total of 1,064 patients who underwent video-assisted thoracoscopic pulmonectomy were included. Variable screening was performed using the random forest algorithm and least absolute shrinkage and selection operator approaches. The mixed cure model was used to identify factors affecting patient cure and survival, and a sequential analysis was performed on 5%, 10%, and 20% of the presentational subtype concurrently. A receiver operating characteristics curve was used to determine the best model and construct a nomogram to predict the cure rate.

RESULTS

The median follow-up time was 58 (range: 3-115) months. Results from the cure part of the mixed model indicated that the predominant subtype, presentational subtype, and tumor diameter were the main prognostic factors affecting cure rate. Therefore, the nomogram to predict the cure rate was constructed based on these factors. The survival part indicated that the predominant subtype was the only factor that influenced recurrence and metastasis. A sequential analysis of the presentational subtype showed it had no significant effect on survival (P > 0.05). Regardless of the recording mode, no significant improvement was observed in the model's discriminative ability. Only a few postoperative pathological specimens showed lymphovascular invasion (LVI); however, the survival curve suggested a significant effect on patient survival.

CONCLUSIONS

After excluding the existence of long-term survivors, the predominant tumor subtype was determined to be the only factor influencing recurrence and metastasis. Although LVI is rare in stage IA lung adenocarcinoma, its significance cannot be discounted in terms of determining patient prognosis.

[Analysis of Clinicopathological Features on Spread Through Air Spaces of Lung Adenocarcinoma]

BACKGROUND

The biological and molecular characteristics of spread through air spaces (STAS), a newly recognized invasive mode of lung cancer, remain controversial. The aim of this study was to investigate the clinicopathological features and molecular characteristics of STAS in patients with pulmonary adenocarcinoma.

METHODS

A total of 694 resected invasive non-mucinous lung adenocarcinomas diagnosed by clinicopathology from July 2019 to March 2021 in the First Affiliated Hospital of Guangzhou Medical University were collected, and the relationship between STAS and clinicopathological factors was analyzed. The state of protein expression of anaplastic lymphoma kinase (ALK) was detected by immunohistochemical method. Epidermal growth factor receptor (EGFR) was detected by amplification refractory mutation system-polymerase chain reaction (ARMS-PCR). ROS proto-oncogene 1-receptor (ROS1) was detected by reverse transcription-PCR (RT-PCR).

RESULTS

A total of 344 STAS positive cases and 350 STAS negative cases were collected. By univariate analysis, STAS positivity was statistically associated with tumor maximum diameter (P<0.001), pleural invasion (P<0.001), lymphovascular invasion (P<0.001), nerve invasion (P=0.013), lymph node metastasis (P<0.001), clinical stage (P<0.001) and histological type (P<0.001). There was a statistical correlation between STAS and ALK protein expression (P=0.001). Multivariate analysis showed that STAS positive was correlated with pleural invasion (P=0.001), vascular invasion (P<0.001), lymph node metastasis (P=0.005)and ALK protein expression (P=0.032).

CONCLUSIONS

STAS is associated with highly aggressive biological behavior of lung adenocarcinoma, suggesting a poor prognosis.

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.

Micropapillary and Solid Histologic Patterns in N1 and N2 Lymph Node Metastases Are Independent Factors of Poor Prognosis in Patients With Stages II to III Lung Adenocarcinoma

INTRODUCTION

High-grade histologic patterns are associated with poor prognosis in patients with primary nonmucinous lung adenocarcinoma (ADC). We investigated whether the presence of micropapillary (MIP), solid (SOL), or both patterns in lymph node (LN) metastases has prognostic value.

METHODS

Patients who underwent lobectomy for pathologic stages II to III lung ADC with N1 or N2 LN metastases (N = 360; 2000-2012) were analyzed. We assessed overall survival (OS), lung cancer-specific cumulative incidence of death (LC-CID), and cumulative incidence of recurrence (CIR) between patients with and without MIP/SOL patterns in LN metastases. Multivariable Cox regression analysis was used to quantify the association between MIP/SOL patterns and outcomes.

RESULTS

MIP and SOL in LN metastases were associated with a higher incidence of smoking history (p = 0.004), tumor necrosis (p = 0.013), and spread of tumor through air spaces (p < 0.0001), a higher prevalence of MIP or SOL in the primary tumor (p < 0.0001), shorter OS (5-y OS, 40% [95% confidence interval or CI: 29%-56%] versus 63% [48%-83%] for no MIP/SOL in LNs, p = 0.03), higher LC-CID (5-y, 43% [29%-56%] versus 14% [4%-29%], p = 0.013), and higher CIR (5-y, 65% [50%-77%] versus 43% [25%-60%], p = 0.057). MIP and SOL in LN metastases were independently associated with poor outcomes: OS (hazard ratio [HR] = 1.81 [95% CI: 1.00-3.29], p = 0.05), LC-CID (HR = 3.10 [1.30-7.37], p = 0.01), and CIR (HR = 2.06 [1.09-3.90], p = 0.026).

CONCLUSIONS

MIP/SOL histologic patterns in N1 or N2 LN metastases are associated with worse outcomes in patients with stages II to III lung ADC. MIP/SOL histologic patterns in LN metastases can stratify patients with high-risk stages II to III lung ADC.

Association of CT findings with invasive subtypes and the new grading system of lung adenocarcinoma

AIM

To predict the differentiation between invasive growth patterns and new grades of lung adenocarcinoma (LAC) using computed tomography (CT).

MATERIALS AND METHODS

The CT features of 180 surgically treated LAC patients were compared retrospectively to pathological invasive subtypes and tumour grades as defined by the new grading system published in 2021 by the World Health Organization. Two radiologists reviewed the images semi-quantitatively and independently. Univariable and multivariable regression models were built from the statistical means of their assessments to predict invasive subtypes and grades. The area under the curve (AUC) calculation was used to select the best models. The Youden index was applied to determine the cut-off values for radiological parameters.

RESULTS

The acinar/papillary patterns were associated with ill-defined margins, lower consolidation/tumour ratio and air bronchogram. The solid growth pattern was associated with a well-defined margin and hypodensity, and the micropapillary (MP) subtype with spiculation. From Grades 1 to 3, the amount of air bronchogram decreased and the consolidation/tumour ratio increased. In the sub-analyses, the best model for differentiating Grade 2 from Grade 1 had the following CT features: solid/subsolid type, consolidation/tumour ratio, well-defined margin, and air bronchogram (AUC = 0.783) and Grade 3 from Grade 2: size of the consolidation part/whole tumour ratio, size of the consolidation part, and well-defined margin (AUC = 0.759). The interobserver agreements between the two radiologists varied between 0.67 and 0.98.

CONCLUSIONS

Air bronchogram, consolidation/tumour ratio, and well-defined margin are among the best imaging findings to discriminate between both invasive subtypes and the new grades in LAC.

Does the presence of a micropapillary component predict worse prognosis in pathological stage IA lung adenocarcinoma?

Considerable evidence has verified that the micropapillary pattern is significantly associated with worse prognosis in pulmonary adenocarcinoma. However, whether the presence of a micropapillary component in pathological stage IA lung adenocarcinoma is also related to worse prognosis remains unclear up to now. The aim of this meta-analysis was to identify the prognostic role of presence of a micropapillary component in pathological stage IA lung adenocarcinoma patients. Relevant studies were searched from the PubMed, EMBASE, Web of Science and CNKI databases and reviewed. The primary and secondary outcomes were the recurrence risk and long-term survival including the overall survival (OS) and disease-free survival (DFS), respectively. All statistical analysis were conducted by STATA 12.0 software. A total of 5257 lung adenocarcinoma patients at the pathological stage IA from ten retrospective studies were enrolled. The recurrence rates in pathological stage IA lung adenocarcinoma patients with and without the a micropapillary component were 32% [95% confidence interval (CI): 20%- 44%] and 7% (95% CI: 4%-10%) separately and pooled results indicated that presence of a micropapillary component was an obvious risk factor for recurrence [odds ratio (OR)= 3.41, 95% CI: 2.80-4.16, P＜0.001]. Besides, the presence of a micropapillary component was significantly related to poorer OS [hazard ratio (HR)= 2.44, 95% CI: 1.28-4.68, P = 0.007] and DFS (HR=2.60, 95% CI: 1.63-4.16, P＜0.001). Subgroup analysis focusing on invasive adenocarcinoma manifested consistent results. In pathological stage IA lung adenocarcinoma, the presence of a micropapillary component predicts obviously higher recurrence risk and worse prognosis even after focusing on invasive adenocarcinoma. However, more prospective high-quality studies are still needed to verify our findings.

[Advances in the Study of Invasive Non-mucinous Adenocarcinoma with Different Pathological Subtypes]

Lung cancer is the leading cause of cancer death in the world today, and adenocarcinoma is the most common histopathological type of lung cancer. In May 2021, World Health Organization (WHO) released the 5th edition of the WHO classification of thoracic tumors, which classifies invasive non-mucinous adenocarcinoma (INMA) into lepidic adenocarcinoma, acinar adenocarcinoma, papillary adenocarcinoma, solid adenocarcinoma, and micropapillary adenocarcinoma based on its histological characteristics. These five pathological subtypes differ in clinical features, treatment and prognosis. A complete understanding of the characteristics of these subtypes is essential for the clinical diagnosis, treatment options, and prognosis predictions of patients with lung adenocarcinoma, including recurrence and progression. This article will review the grading system, morphology, imaging prediction, lymph node metastasis, surgery, chemotherapy, targeted therapy and immunotherapy of different pathological subtypes of INMA.
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Minor histological components predict the recurrence of patients with resected stage I acinar- or papillary-predominant lung adenocarcinoma

Objective

Invasive lung adenocarcinoma is composed of five different histological subgroups with diverse biological behavior and heterogeneous morphology, the acinar/papillary-predominant lung adenocarcinomas are the most common subgroups and recognized as an intermediate-grade group. In the real world, clinicians primarily consider predominant patterns and ignore the impact of minor components in the prognosis of lung adenocarcinoma. The study evaluated the clinicopathologic characteristics of the lepidic, solid, and micropapillary patterns as non-predominant components and whether the minimal patterns had prognostic value on acinar/papillary-predominant lung adenocarcinomas.

Methods

A total of 153 acinar/papillary-predominant lung adenocarcinoma patients with tumor size ≤4 cm were classified into four risk subgroups based on the presence of lepidic and micropapillary/solid components: MP/S^-Lep⁺, MP/S⁺Lep⁺, MP/S^-Lep^-, and MP/S⁺Lep^- groups. The Cox-proportional hazard regression model was used to assess disease-free survival (DFS).

Results

The risk subgroups based on the non-predominant patterns were associated with differentiation (P = 0.001), lymphovascular invasion (P = 0.001), and recurrence (P = 0.003). In univariate analysis, DFS was correlated with non-predominant components (P = 0.014), lymphovascular invasion (P = 0.001), carcinoembryonic antigen (CEA) (P = 0.001), and platelet-to-lymphocyte ratio (PLR) (P = 0.012). In the multivariate analysis, non-predominant components (P = 0.043) and PLR (P = 0.032) were independent prognostic factors for DFS. The 5-year survival rates of MP/S^-Lep⁺, MP/S⁺Lep⁺, MP/S^-Lep^- and MP/S⁺Lep^- subgroups were 93.1%,92.9%,73.1%,61.9%, respectively. The MP/S^-Lep⁺ subgroup had the favorable prognosis than MP/S⁺Lep^- subgroup with a statistically significant difference (P = 0.002). As minor components, the lepidic patterns were a protective factor, and the solid and micropapillary components were poor factors. The recurrence was related to the presence of non-predominant patterns rather than their proportion. Adjuvant chemotherapy did not significantly improve the prognosis of the MP/S⁺Lep^- subgroup (P = 0.839).

Conclusions

Regardless of the proportion, the presence of micropapillary/solid components and the absence of lepidic patterns are aggressive factors of DFS in patients with resected stage I acinar- or papillary-predominant lung adenocarcinoma.

Genomic and clinicopathological features of lung adenocarcinomas with micropapillary component

BACKGROUND

Lung adenocarcinoma (LA) with a micropapillary component (LAMPC) is a histological subtype of lung cancer that has received increasing attention due to its correlation with poor prognosis, and its tendency to recur and metastasize. At present, comprehensive genomic profiles and clinicopathological features for LAMPC remain unclear and require further investigation.

METHODS

From September 2009 to October 2020, a total of 465 LAMPC patients were recruited and divided into four groups according to MPC proportions, and the correlations between varying proportions of MPCs and clinicopathological characteristics were analyzed. Twenty-nine (29) LAMPC patients and 89 LA patients without MPC (non-MPC) that had undergone NGS testing were selected for further study The comprehensively analyze genomic variations and the difference between LAMPC and MPC were determined. In addition, Gene alterations of LAMPC between Chinese and Western populations were also compared using cBioPortal data.

RESULTS

A higher proportion of MPCs, associated with higher tumor stage, pleural invasion, and vascular tumor thrombus formation, was determined in LA patients. Compared to non-MPC patients, LAMPC patients were determined to have a lower frequency of single nucleotide variants and a higher frequency of insertion-deletion mutations. Mutations in TP53, CTNNB1, and SMAD4, and ALK rearrangements/fusions were significantly more frequent in LAMPC patients. ERBB2 mutations were only detected in non-MPC patients. Gene mutations in the Wnt pathway were significantly more common in LAMPC patients as compared to non-MPC patients. ALK fusions were more prevalent in younger patients. Patients with KRAS or LBP1B mutations had significantly larger tumor diameters than patients with wild-type KRAS or LBP1B. Patients with KRAS mutations were more likely to develop vascular tumor thrombus. Using the cBioPortal public database, we determined that mutations in EGFR were significantly higher in Chinese patients than in a Memorial Sloan Kettering Cancer Center (MSKCC) Western cohort. ALK fusions were exclusively detected in the Chinese cohort, while mutations in KEAP1 and NOTCH4 were only detected in the MSKCC cohort. Our analysis of signaling pathways revealed that Wnt pathway gene mutations were significantly higher in the Chinese cohort.

CONCLUSION

LA patients with higher proportions of MPCs were determined to have a higher tumor stage, pleural invasion, and vascular tumor thrombosis formation. We comprehensively analyzed the genomic mutation characteristics of LAMPC patients and identified multiple, novel MPC-related gene alterations and pathway changes. Our data provide further understanding of the nature of the LAMPC and potential drug-targeted gene alterations, which may lead to new therapeutic strategies.

Solid Attenuation Components Attention Deep Learning Model to Predict Micropapillary and Solid Patterns in Lung Adenocarcinomas on Computed Tomography

BACKGROUND

High-grade adenocarcinoma subtypes (micropapillary and solid) treated with sublobar resection have an unfavorable prognosis compared with those treated with lobectomy. We investigated the potential of incorporating solid attenuation component masks with deep learning in the prediction of high-grade components to optimize surgical strategy preoperatively.

METHODS

A total of 502 patients with pathologically confirmed high-grade adenocarcinomas were retrospectively enrolled between 2016 and 2020. The SACs attention DL model was developed to apply solid-attenuation-component-like subregion masks (tumor area ≥ - 190 HU) to guide the DL model for predicting high-grade subtypes. The SACA-DL was assessed using 5-fold cross-validation and external validation in the training and testing sets, respectively. The performance, which was evaluated using the area under the curve (AUC), was compared between SACA-DL and the DL model without SACs attention (DL_woSACs), the prior radiomics model, or the model based on the consolidation/tumor (C/T) diameter ratio.

RESULTS

We classified 313 and 189 patients into training and testing cohorts, respectively. The SACA-DL achieved an AUC of 0.91 for the cross-validation, which was significantly superior to those of the DL_woSACs (AUC = 0.88; P = 0.02), prior radiomics model (AUC = 0.85; P = 0.004), and C/T ratio (AUC = 0.84; P = 0.002). An AUC of 0.93 was achieved for external validation in the SACA-DL and was significantly better than those of the DL_woSACs (AUC = 0.89; P = 0.04), prior radiomics model (AUC = 0.85; P < 0.001), and C/T ratio (AUC = 0.85; P < 0.001).

CONCLUSIONS

The combination of solid-attenuation-component-like subregion masks with the DL model is a promising approach for the preoperative prediction of high-grade adenocarcinoma subtypes.

[Pattern of Recurrence and Metastasis after Radical Resection of Non-small Cell Lung Cancer]

The rate of recurrence and metastasis of non-small cell lung cancer after radical resection is still very high. The risk factors for recurrence and metastasis have been extensively studied, but the dynamic pattern of postoperative recurrence hazard over time is relatively lacking. The dynamic recurrence hazard rate curve is applied to describe the rate of recurrence at any point time among the "at-risk" patients. In this article, by reviewing the previous literature, the characteristics of the dynamic recurrence and metastasis pattern after radical resection of non-small cell lung cancer and the clinical factors affecting the recurrence and metastasis pattern are summarized, in order to screen out specific populations with high recurrence risk and give them personalized follow-up strategy and diagnosis and treatment.
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Factors associated with lymph node metastasis upstage after resection for patients with micropapillary lung adenocarcinoma

Background

Micropapillary adenocarcinoma has a poor prognostic histological pattern. Additionally, preoperative detection of lymph node metastases by preoperative examination is difficult in some patients with micropapillary adenocarcinoma, and postoperative upstage may occur. However, clinicopathological features of patients with micropapillary adenocarcinoma with nodal upstage have not been established, therefore this study aimed to identify the factors associated with potential lymph node metastases during preoperative examination to ensure effective surgical procedures.

Methods

Between January 2011 and December 2020, 1029 patients received complete resection for primary non‐small‐cell lung cancer by lobectomy or more extensive resection with systematic lymph node dissection at this institution. One hundred and thirty‐one patients diagnosed with adenocarcinoma with micropapillary component were included in this study. The clinicopathological features of patients with nodal upstage whose postoperative N stage was more advanced than the preoperative N stage were examined.

Results

Forty patients had nodal upstage after resection. ¹⁸F‐fluorodeoxyglucose (FDG) positron emission tomography‐computed tomography (PET‐CT) revealed that a maximum standardized uptake value (SUVmax) ≥5 for the primary lesion was significantly associated with postoperative nodal upstage. There were no significant differences in terms of sex, age, smoking history, surgical procedure, and diabetes. Among 38 patients with nodal upstage, 23 patients had no significant preoperative lymphadenopathy and showed no abnormal FDG uptake in the lymph nodes on ¹⁸F‐FDG‐PET‐CT, respectively.

Conclusions

Lymph node metastases were suspected in patients preoperatively diagnosed with micropapillary adenocarcinoma with FDG SUVmax ≥5 for the primary tumor. Therefore, standard surgical resection and careful lymph node dissection should be performed for such patients.

The 2021 WHO Classification of Lung Tumors: Impact of advances since 2015

The 2021 World Health Organisation (WHO) Classification of Thoracic Tumours was published earlier this year, with classification of lung tumors being one of the chapters. The principles remain those of using morphology first, supported by immunohistochemistry and then molecular techniques. In 2015, there was particular emphasis on using immunohistochemistry to make classification more accurate. In 2021, there is greater emphasis throughout the book on advances in molecular pathology across all tumor types. Major features within this edition are 1) broader emphasis on genetic testing than in the 2015 WHO Classification, 2) a chapter entirely dedicated to the classification of small diagnostic samples, 3) continued recommendation to document percentages of histological patterns in invasive non-mucinous adenocarcinomas, with utilization of these features to apply a formal grading system, as well as using only invasive size for T-factor size determination in part lepidic non-mucinous lung adenocarcinomas as recommended by the 8^th Edition TNM Classification, 4) recognition of spread through airspaces (STAS) as a histological feature with prognostic significance, 5) moving lymphoepithelial carcinoma to squamous cell carcinomas, 6) update on evolving concepts in lung neuroendocrine neoplasm classification, 7) recognition of bronchiolar adenoma/ciliated muconodular papillary tumor (BA/CMPT) as a new entity within the adenoma subgroup, 8) recognition of thoracic SMARCA4-deficient undifferentiated tumor, and 9) inclusion of essential and desirable diagnostic criteria for each tumor.

Deep learning for predicting subtype classification and survival of lung adenocarcinoma on computed tomography

OBJECTIVES

The subtype classification of lung adenocarcinoma is important for treatment decision. This study aimed to investigate the deep learning and radiomics networks for predicting histologic subtype classification and survival of lung adenocarcinoma diagnosed through computed tomography (CT) images.

METHODS

A dataset of 1222 patients with lung adenocarcinoma were retrospectively enrolled from three medical institutions. The anonymised preoperative CT images and pathological labels of atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive adenocarcinoma, invasive adenocarcinoma (IAC) with five predominant components were obtained. These pathological labels were divided into 2-category classification (IAC; non-IAC), 3-category and 8-category. We modeled the classification task of histological subtypes based on modified ResNet-34 deep learning network, radiomics strategies and deep radiomics combined algorithm. Then we established the prognostic models in lung adenocarcinoma patients with survival outcomes. The accuracy (ACC), area under ROC curves (AUCs) and C-index were primarily performed to evaluate the algorithms.

RESULTS

This study included a training set (n = 802) and two validation cohorts (internal, n = 196; external, n = 224). The ACC of deep radiomics algorithm in internal validation achieved 0.8776, 0.8061 in the 2-category, 3-category classification, respectively. Even in 8 classifications, the AUC ranged from 0.739 to 0.940 in internal set. Further, we constructed a prognosis model that C-index was 0.892(95% CI: 0.846-0.937) in internal validation set.

CONCLUSIONS

The automated deep radiomics based triage system has achieved the great performance in the subtype classification and survival predictability in patients with CT-detected lung adenocarcinoma nodules, providing the clinical guide for treatment strategies.

Clinical Value and Pathologic Basis of Cystic Airspace Within Subsolid Nodules Confirmed as Lung Adenocarcinomas by Surgery

PURPOSE

To investigate the clinical value and pathologic basis of cystic airspace within lung adenocarcinomas manifesting as subsolid nodules.

PATIENTS AND METHODS

A retrospective study was conducted on a total of 541 surgically confirmed lung adenocarcinomas manifesting as subsolid nodules in computed tomography images, including 87 cases with cystic airspace and 454 cases without cystic airspace. The pathologic characteristics of the cases with and without cystic airspace were compared. The investigation of the pathologic structure of cystic airspace was attempted on the postoperative paraffin sections.

RESULTS

There was a significant difference in the containing of cystic airspace between preinvasive and invasive adenocarcinomas (10.5 vs 26.6%; P < .001). Multivariate analysis indicated that cystic airspace is an independent predictor of invasive adenocarcinomas (odds ratio, 3.220; 95% confidence interval, 1.822-5.687). Nodules containing multiple cystic airspaces are more likely to be invasive adenocarcinomas than nodules with a single cystic airspace (47.1 vs 72.2%; P < .05). On paraffin sections, the walls of the cystic airspace seemed to be mainly composed of atypical hyperplasia and/or tumor cells on the surface and the remaining smooth muscle cells and stroma below, which is similar to the structure of bronchi.

CONCLUSIONS

Cystic airspace may be a reliable predictor of invasive adenocarcinomas, the classification method based on the number of cystic airspaces might be suitable for the computed tomography-based typing of cystic airspace within subsolid nodules. Cystic airspace may derive from the destroyed and enlarged bronchi owing to the growth or infiltration of atypical hyperplasia and/or tumor cells.

Adenocarcinoma of High-Grade Patterns Associated with Distinct Outcome of First-Line Chemotherapy or EGFR-TKIs in Patients of Relapsed Lung Cancer

Purpose

High-grade patterns (micropapillary/solid/complex gland) are associated with a higher recurrence rate and shorter disease-free survival. Thus far, it remains unclear whether the efficacy of first-line anticancer therapy is different from that of the other adenocarcinoma subgroups for patients with high-grade patterns. The study aimed to investigate the association between an adenocarcinoma with high-grade patterns with the outcomes of first-line treatment in patients with lung cancer.

Patients and Methods

Patients with a high-grade pattern adenocarcinoma (more than 20% of micropapillary/solid components/complex glandular patterns) were retrospectively analyzed between June 2015 and June 2017. Patients’ clinical characteristics and treatment outcomes were compared with those of the remaining control adenocarcinoma subgroups.

Results

In total, 239 patients with adenocarcinoma, including 115 (48.1%) high-grade patterns and 124 (51.9%) control groups, were enrolled. Patients’ clinical characteristics such as age, sex, smoking status, and stage were similar between the two groups. Among them, 108 patients received first-line chemotherapy, and 131 received epidermal growth factor receptor–tyrosine kinase inhibitors (EGFR-TKIs). In the chemotherapy group, adenocarcinoma of high-grade patterns had a significantly lower objective response rate (ORR; 15.6% vs 36.4%, P=0.045), shorter progression-free survival (PFS; median 4.1 vs 5.4 months, P=0.007) and overall survival (OS, median 19.6 vs 23.8 months, P=0.048) compared with the control group. As for these treated with EGFR-TKIs, a similar ORR (70.7% vs 72.1%, P=0.703), PFS (median 11.3 vs 13.9 months, P=0.065) and OS (median 34.1 vs 29.6%, p=0.575) were observed between these two groups.

Conclusion

An adenocarcinoma with high-grade patterns is associated with inferior outcomes to first-line chemotherapy in relapsed lung cancer. Patients who received chemotherapy had a significantly shorter PFS and OS and lower ORR than control subjects, while there was no difference in the EGFR-TKI cohort. This study is the first to report the distribution of adenocarcinoma with high-grade patterns.

Micropapillary pattern of stage IIIA-N2 lung adenocarcinoma is a prognostic factor after adjuvant chemoradiotherapy

Aim: This study aims to investigate the significance of a micropapillary pattern in stage IIIA-N₂ lung adenocarcinoma after adjuvant chemoradiotherapy. Patients & methods: A total of 257 patients with stage IIIA-N₂ lung adenocarcinoma were enrolled in this study. Patients were classified into three groups based on the proportion of micropapillary components: micropapillary negative, micropapillary minor component and micropapillary predominant component. Results: The micropapillary predominant group had the shortest median disease-free survival and overall survival times compared with the micropapillary minor component and micropapillary negative groups (median overall survival time: 54 months vs 64 months vs not reached; p = 0.004). Furthermore, the micropapillary pattern was an independent prognostic factor for disease-free survival and overall survival (p < 0.05). Conclusion: The micropapillary pattern of IIIA-N₂ lung adenocarcinoma is related to worse prognosis.