Does lung adenocarcinoma subtype predict patient survival?: A clinicopathologic study based on the new International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society international multidisciplinary lung adenocarcinoma classification. J Thorac Oncol. 2011;6:1496-1504. [PMID: 21642859 DOI: 10.1097/jto.0b013e318221f701]

Expression and Gene Regulation Network of Adenosine Receptor A2B in Lung Adenocarcinoma: A Potential Diagnostic and Prognostic Biomarker

Adenosinereceptor A2B (ADORA2B) encodes a protein belonging to the G protein–coupled receptor superfamily. Abnormal expression of ADORA2B may play a pathophysiological role in some human cancers. We investigated whether ADORA2B is a potential diagnostic and prognostic biomarker for lung adenocarcinoma (LUAD). The expression, various mutations, copy number variations, mRNA expression levels, and related network signaling pathways of ADORA2B were analyzed using bioinformatics-related websites, including Oncomine, UALCAN, cBioPortal, GeneMANIA, LinkedOmics, KM Plotter, and TIMER. We found that ADORA2B was overexpressed and amplified in LUAD, and a high ADORA2B expression predicted a poor prognosis for LUAD patients. Pathway analyses of ADORA2B in LUAD revealed ADORA2B-correlated signaling pathways, and the expression level of ADORA2B was associated with immune cell infiltration. Furthermore, ADORA2B mRNA and protein levels were significantly higher in human LUAD cell lines (A549 cells and NCl-H1299 cells) than in normal human bronchial epithelial (HBE) cells, and the transcript levels of genes positively or negatively correlated with ADORA2B were consistent and statistically significant. siRNA transfection experiments and functional experiments further confirmed these results. In vitro results were also consistent with those of bioinformatics analysis. Our findings provide a foundation for studying the role of ADORA2B in tumorigenesis and support the development of new drug targets for LUAD.

DeepRePath: Identifying the Prognostic Features of Early-Stage Lung Adenocarcinoma Using Multi-Scale Pathology Images and Deep Convolutional Neural Networks

Simple Summary

Pathology images are vital for understanding solid cancers. In this study, we created DeepRePath using multi-scale pathology images with two-channel deep learning to predict the prognosis of patients with early-stage lung adenocarcinoma (LUAD). DeepRePath demonstrated that it could predict the recurrence of early-stage LUAD with average area under the curve scores of 0.77 and 0.76 in cohort I and cohort II (external validation set), respectively. Pathological features found to be associated with a high probability of recurrence included tumor necrosis, discohesive tumor cells, and atypical nuclei. In conclusion, DeepRePath can improve the treatment modality for patients with early-stage LUAD through recurrence prediction.

Abstract

The prognosis of patients with lung adenocarcinoma (LUAD), especially early-stage LUAD, is dependent on clinicopathological features. However, its predictive utility is limited. In this study, we developed and trained a DeepRePath model based on a deep convolutional neural network (CNN) using multi-scale pathology images to predict the prognosis of patients with early-stage LUAD. DeepRePath was pre-trained with 1067 hematoxylin and eosin-stained whole-slide images of LUAD from the Cancer Genome Atlas. DeepRePath was further trained and validated using two separate CNNs and multi-scale pathology images of 393 resected lung cancer specimens from patients with stage I and II LUAD. Of the 393 patients, 95 patients developed recurrence after surgical resection. The DeepRePath model showed average area under the curve (AUC) scores of 0.77 and 0.76 in cohort I and cohort II (external validation set), respectively. Owing to low performance, DeepRePath cannot be used as an automated tool in a clinical setting. When gradient-weighted class activation mapping was used, DeepRePath indicated the association between atypical nuclei, discohesive tumor cells, and tumor necrosis in pathology images showing recurrence. Despite the limitations associated with a relatively small number of patients, the DeepRePath model based on CNNs with transfer learning could predict recurrence after the curative resection of early-stage LUAD using multi-scale pathology images.

Invasive Mucinous Adenocarcinomas With Spatially Separate Lung Lesions: Analysis of Clonal Relationship by Comparative Molecular Profiling

INTRODUCTION

Pulmonary invasive mucinous adenocarcinomas (IMAs) often present with spatially separate lung lesions. Clonal relationship between such lesions, particularly those involving contralateral lobes, is not well established. Here, we used comparative genomic profiling to address this question.

METHODS

Patients with genomic analysis performed on two IMAs located in different lung regions were identified. Molecular assays included DNA-based next-generation sequencing (NGS) for 410 to 468 genes (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets), RNA-based NGS for 62 genes (Memorial Sloan Kettering-Fusion), or non-NGS assays.

RESULTS

Comparative genomic profiling was performed on two separate IMAs in 24 patients, of whom 19 had contralateral lesions. Tumors from all but one patient shared matching driver alterations, including KRAS (n = 19), NRG1 (n = 2), ERBB2 (n = 1) or BRAF (n = 1). In addition, in patients with paired tumors profiled by NGS (n = 12), shared driver alterations were accompanied by up to 4 (average 2.6) other identical mutations, further supporting the clonal relationship between the tumors. Only in a single patient separate IMAs harbored entirely nonoverlapping mutation profiles, supporting clonally unrelated, distinct primary tumors. Notably, in a subset of patients (n = 3), molecular testing confirmed a clonal relationship between the original resected IMAs and subsequent contralateral IMA presenting after an extremely long latency (8.1-11.7 y).

CONCLUSIONS

Comparative molecular profiling supports that nearly all separate pulmonary IMA lesions represent intrapulmonary spread arising from a single tumor and documents a subset with a remarkably protracted course of intrapulmonary progression. This study reinforces the unique biology and clinical behavior of IMAs while further highlighting the value of genomic testing for clarifying the clonal relationship between multiple lung carcinomas.

FDG-PET/CT for pretherapeutic lymph node staging in non-small cell lung cancer: A tailored approach to the ESTS/ESMO guideline workflow

OBJECTIVES

In patients with NSCLC, current ESTS and ESMO guidelines recommend invasive lymph node (LN) staging with EBUS-TBNA even if FDG-PET/CT is negative for mediastinal LNs if at least one of three risk factors is present (cN1, non-peripheral primary or primary >3 cm). Modified workflows to avoid unnecessary invasive procedures were evaluated.

MATERIALS AND METHODS

Monocentric retrospective analysis of pretherapeutic FDG-PET/CT in 247 patients with NSCLC (62 % male; age, 68 [43-88] years) using an analog or digital PET/CT scanner. PET windowing was standardized. LNs were positive if 'LN uptake > mediastinal blood pool' or short axis >10 mm. Surgery or EBUS-TBNA served as reference for diagnostic accuracy per LN station. In all patients with negative mediastinal LNs by PET/CT, LN histology from surgery was available.

RESULTS

Among 700 L N stations analyzed, 180 were malignant. Sensitivity and specificity of PET/CT per LN station were 93 % and 71 %. Following current guidelines, 76 patients with mediastinal negative PET/CT required confirmatory invasive staging. Only 5/76 patients had unexpected pN2 (all had adenocarcinoma). In a modified approach, confirmatory invasive staging was confined to patients with mediastinal negative PET/CT who showed all three risk factors. Using this modification, EBUS-TBNA could have been omitted in 62 (82 %) of the 76 patients who required EBUS-TBNA based on current recommendation. Among these 62 patients, only one patient had unsuspected pN2 (single-level) while the remaining 61 of 62 omitted EBUS-TBNA were deemed unnecessary because mediastinal LNs were confirmed to be negative. No multi-level pN2 would have been missed.

CONCLUSION

In the current analysis, 82 % of EBUS-TBNA procedures in patients with mediastinal negative PET/CT could have been omitted by modifying the current guideline workflow as proposed (i.e., restricting EBUS-TBNA in patients with cN0/1 to those with all three risk factors). This was consistent with different PET/CT scanners. Prospective confirmation is required.

Genetic-pathological prediction for timing and site-specific recurrence pattern in resected lung adenocarcinoma

OBJECTIVES

We aimed to describe accurately the timing and site-specific recurrence pattern for surgical resected lung adenocarcinoma and develop genetic-pathological risk prediction models to guide individual postoperative surveillance strategies.

METHODS

We retrospectively analysed radiological, pathological and sequencing data concerning 9 common oncogenic driver mutations from 1531 patients with resected lung adenocarcinoma between 2008 and 2015. The first recurrence site and time-to-recurrence were recorded. Independent risk factors were identified by multivariable regression analysis and consequently incorporated into prediction models.

RESULTS

With a median follow-up of 53.2 months, postoperative recurrences were noted in 483 (31.5%) patients. Bone and brain recurrence tended to occur early (median 11.7 and 17.0 months, respectively) while thorax recurrence occurred later (median 22.2 months), which was validated across different tumour stages. EGFR mutation was an independent predictor for brain and bone recurrence and KRAS mutation for early recurrence. Both internal and external validation of the nomograms for brain and bone recurrence prediction showed optimal discrimination (concordance index: internal, 0.75 and 0.81, respectively; external, 0.77 and 0.84, respectively) and calibration. Recurrence occurred relatively evenly during the follow-up period in low-risk groups but mainly occurred within 2 years in high-risk groups.

CONCLUSIONS

Unique biological differences exist among lung adenocarcinoma leading to distinct patterns of recurrence. These user-friendly genetic-pathological nomograms may help physicians to better stratify patients and make individual postoperative follow-up plans.

[Value of PET/CT Combined with CT Three-dimensional Reconstruction in Distinguishing Different Pathological Subtypes of Early Lung Adenocarcinoma]

背景与目的

早期肺腺癌中病理亚型以贴壁为主型的浸润性腺癌（lepidic predominant invasive adenocarcinoma, LPA）与原位腺癌（adenocarcinoma in situ, AIS）、微浸润性腺癌（microinvasive adenocarcinoma, MIA）的良好预后相似，临床上也迫切需要能够区分LPA与非LPA型浸润性腺癌（non-lepidic predominant invasive adenocarcinoma, non-LPA）的手段，本研究拟通过正电子发射型计算机断层显像（positron emission computed tomography, PET）/计算机断层扫描（computed tomography, CT）的最大标准化摄取值（maximal standard uptake value, SUVmax）和CT三维重建后参数探讨术前影像学表现为部分实性结节（part-solid nodules, PSNs）的早期肺腺癌不同病理亚型间的关系。

方法

回顾性分析2016年1月-2019年1月于江苏省苏北人民医院胸外科行解剖性肺切除术且影像学表现为PSNs的早期肺腺癌患者资料，所有患者胸部增强CT和PET/CT资料完整可获取，利用Mimics软件行三维重建，获取肿瘤体积、肿瘤三维平均CT值（3-dimensional mean-CT value, 3Dm-CT）、SUVmax等数据，采用SPSS 25.0进行统计分析，GraphPad Prism 8.3.0绘制受试者工作曲线（receiver operating curve, ROC），P < 0.05为差异有统计学意义。

结果

最终共计67例患者纳入本研究，按病理亚型不同将所有患者分为两组，AIS、MIA及浸润性腺癌（invasive adenocarcinoma, IAC）中的LPA归为低危组28例（41.8%），其余non-LPA如腺泡型（acinar pattern-predominant adeno-carcinoma, APA）、乳头型（papillary pattern-predominant adenocarcinoma, PPA）、微乳头型（micropapillary pattern-predominant adeno-carcinoma, MPA）归为高危组39例（58.2%），两组间SUVmax（t=3.153, P=0.002）、肿瘤体积（t=3.331, P=0.001)、实性/磨玻璃成分体积（t=2.74, P=0.006) /（t=3.127, P=0.002）、实性/磨玻璃成分3Dm-CT（t=3.655, P < 0.001) /（t=7.082, P < 0.001) 均具有显著统计学意义。ROC曲线提示：SUVmax[曲线下面积（area under curve, AUC）=0.727]、肿瘤体积（AUC=0.740）、磨玻璃成分体积（AUC=0.725）、实性成分3Dm-CT（AUC=0.763）、磨玻璃成分3Dm-CT（AUC=0.756）预测效能最佳。将上述AUC > 0.7的协变量纳入多因素ROC曲线分析，获得联合预测因子（AUC=0.835）具有中等以上预测价值。

结论

PET/CT中SUVmax和CT三维重建参数与影像学表现为PSNs的早期肺腺癌的不同病理亚型具有显著相关性，联合SUVmax、肿瘤体积、磨玻璃成分体积和实性/磨玻璃成分3Dm-CT对鉴别表现为PSNs的早期肺腺癌的病理亚型具有一定价值。

The Prognostic Value of Preoperative Serum Tumor Markers in Non-Small Cell Lung Cancer Varies With Radiological Features and Histological Types

Objectives

To assess the association between common-used serum tumor markers and recurrence of lung adenocarcinoma and squamous cell carcinoma separately and determine the prognostic value of serum tumor markers in lung adenocarcinoma featured as ground glass opacities.

Methods

A total of 2,654 non-small cell lung cancer patients undergoing surgical resection between January 2008 and September 2014 were analyzed. The serum levels of carcinoma embryonic antigen (CEA), cytokeratin 19 fragment (CYFRA21-1), neuron-specific enolase (NSE), carbohydrate antigen 125 (CA125), carbohydrate antigen 153 (CA153) and carbohydrate antigen 199 (CA199) were tested preoperatively. Survival analyses were performed with COX proportional hazard regression.

Results

Among patients with lung adenocarcinoma, elevated preoperative serum CEA(HR=1.246, 95%CI:1.043-1.488, P=0.015), CYFRA21-1(HR=1.209, 95%CI:1.015-1.441, P=0.034) and CA125(HR=1.361, 95%CI:1.053-1.757, P=0.018) were significantly associated with poorer recurrence free survival (RFS). Elevated preoperative serum CA199 predicted worse RFS in patients diagnosed with lung squamous cell carcinoma (HR=1.833, 95%CI: 1.216-2.762, P=0.004). Preoperative serum CYFRA21-1(HR=1.256, 95%CI:1.044-1.512, P=0.016) and CA125(HR=1.373, 95%CI: 1.050-1.795, P=0.020) were independent prognostic factors for patients with adenocarcinoma presenting as solid nodules while serum CEA (HR=2.160,95%CI:1.311-3.558, P=0.003) and CA125(HR=2.475,95%CI:1.163-5.266, P=0.019) were independent prognostic factors for patients with adenocarcinoma featured as ground glass opacities.

Conclusions

The prognostic significances of preoperative serum tumor markers in non-small cell lung cancer were associated with radiological features and histological types.

Rethinking a Non-Predominant Pattern in Invasive Lung Adenocarcinoma: Prognostic Dissection Focusing on a High-Grade Pattern

Simple Summary

Prognostic considerations for non-predominant histologic patterns are necessary because most lung adenocarcinomas have a mixed histologic pattern. We aimed to identify prognostic stratification by second most predominant pattern of lung adenocarcinomas and to more accurately assess prognostic factors with CT imaging analysis, particularly enhancing non-predominant but high-grade pattern. We confirmed that the second most predominant histologic pattern can stratify lung adenocarcinoma patients according to prognosis. Especially, when the second most predominant pattern was high-grade, recurrence risk increased by 4.2-fold compared with the low-grade group. Thus, predicting the malignant potential and establishing treatment policies should not rely only on the most predominant pattern. Also, imaging parameters of higher non-contrast CT value and higher SUVmax value are associated with non-predominant but high-grade histologic pattern.

Abstract

Background: Prognostic considerations for non-predominant patterns are necessary because most lung adenocarcinomas (ADCs) have a mixed histologic pattern, and the spectrum of actual prognosis varies widely even among lung ADCs with the same most predominant pattern. We aimed to identify prognostic stratification by second most predominant pattern of lung ADC and to more accurately assess prognostic factors with CT imaging analysis, particularly enhancing non-predominant but high-grade pattern. Methods: In this prospective study, patients with early-stage lung ADC undergoing curative surgery underwent preoperative dual-energy CT (DECT) and positron emission tomography (PET)/CT. Histopathology of ADC, the most predominant and second most predominant histologic patterns, and preoperative imaging parameters were assessed and correlated with patient survival. Results: Among the 290 lung ADCs included in the study, 231 (79.7%) were mixed-pathologic pattern. When the most predominant histologic pattern was intermediate-grade, survival curves were significantly different among the three second most predominant subgroups (p = 0.004; low, lepidic; intermediate, acinar and papillary; high, micropapillary and solid). When the second most predominant pattern was high-grade, recurrence risk increased by 4.2-fold compared with the low-grade group (p = 0.005). To predict a non-predominant but high-grade pattern, the non-contrast CT value of tumor was meaningful with a lower HU value associated with the histologic combination of lower grade (low-grade as most predominant and intermediate-grade as second most predominant pattern, OR = 6.15, p = 0.005; intermediate-grade as most predominant and high-grade as second most predominant pattern, OR = 0.10, p = 0.033). SUVmax of the tumor was associated with the non-predominant but high-grade pattern, especially in the histologic combination of intermediate-high grade (OR = 1.14, p = 0.012). Conclusions: The second most predominant histologic pattern can stratify lung ADC patients according to prognosis. Thus, predicting the malignant potential and establishing treatment policies should not rely only on the most predominant pattern. Moreover, imaging parameters of non-contrast CT value and SUVmax could be useful in predicting a non-predominant but high-grade histologic pattern.

Invasive adenocarcinoma manifesting as pure ground glass nodule with different size: radiological characteristics differ while prognosis remains the same

BACKGROUND

Invasive adenocarcinoma (IA) manifesting as pure ground-glass nodule is rare and not been well studied. Meanwhile, tumor size is considered as a predictor of invasiveness in lung adenocarcinoma. The present study aimed to investigate the radiological and pathological characteristics as well as prognosis of IA manifesting as pure ground-glass nodule with different sizes.

METHODS

Patients with solitary pure ground glass nodule (GGN) who underwent resection and were pathologically diagnosed as IA between July 2013 and July 2015 were included. Nodules were divided into four groups according to size: A, B, C, and D, corresponding to "≤1 cm," "1-2 cm," "2-3 cm," and ">3 cm," respectively. The correlations and differences in radiological and pathological characteristics as well as prognosis among these groups were analyzed.

RESULTS

The amounts of nodules in groups A, B, C, and D are 17, 148, 78, and 30, respectively. The average diameter of these 273 nodules is 1.9 (1.5-2.4) cm. A large tumor is likely to have low computed tomography (CT) value (P<0.001), irregular shape (P=0.001), spiculation appearance (P<0.001) and exhibit pleural indentation (P<0.001) and air bronchogram (P<0.001). The proportion of lepidic predominant adenocarcinoma (LPA) (n=239, 87.5%) is much higher than that of other subtypes (n=34, 12.5%). Currently, there is no case with lymphatic, pleural, or vessel invasion and lymph node involvement, and none died of recurrence or metastasis within 5 years after resection.

CONCLUSIONS

For IA manifesting as pure ground-glass nodule, size is correlated to invasiveness, and large tumors tend to have lower CT value, an irregular shape, lobulation and spiculation appearance and exhibit pleural indentation and air bronchogram. Nevertheless, the prognosis is excellent with 100% 5-year disease-free survival regardless of the size and pathological subtype.

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.

High proportion of tumor necrosis predicts poor survival in surgically resected high-grade neuroendocrine carcinoma of the lung

OBJECTIVES

Tumor necrosis is a negative prognostic factor in various cancers. High-grade neuroendocrine carcinomas (HGNEC) of the lung, such as small cell lung cancer (SCLC) and large cell neuroendocrine carcinoma (LCNEC), commonly have histopathological features of tumor necrosis. However, the prognostic value of tumor necrosis remains unknown.

MATERIALS AND METHODS

A total of 81 patients with HGNEC (SCLC, n = 42; LCNEC, n = 39) who underwent complete resection were enrolled. The proportion of necrosis in the tumor tissues was quantified using digital image analysis. We analyzed the relationship between the proportion of necrosis, clinicopathological factors, and prognosis. Moreover, we examined the correlation between genomic alterations and proportion of necrosis.

RESULTS

The median proportion of necrosis was 10.6 % (range, 0-62.8 %). The proportion of necrosis was not significantly different between SCLC (median, 5.1 %; range, 0-62.8 %) and LCNEC (median: 14.2 %; range, 0-59.3 %) (p =  0.14). The cumulative incidence of recurrence (CIR) and lung cancer-specific cumulative incidence of death (LC-CID) were significantly higher in patients with 10 % or higher necrosis (necrosis ≥ 10 %) than in those with less than 10 % (necrosis < 10 %) (hazard ratio [HR], 2.94; 95 % confidence interval [CI], 1.30-6.64, and HR, 2.87; 95 % CI, 1.13-7.29, respectively). In the bivariate analysis, necrosis ≥ 10 % was independently associated with higher CIR and tended to be associated with higher LC-CID. The frequency of genomic alterations in the PI3K/AKT/mTOR pathway, MYC family, MAPK/ERK pathway, and major RTK signaling pathways were not different between the necrosis ≥ 10 % and necrosis < 10 % groups for both SCLC and LCNEC.

CONCLUSION

High proportion of tumor necrosis (≥ 10 %) had a negative prognostic value in surgically resected HGNEC.

A systematic dissection of the epigenomic heterogeneity of lung adenocarcinoma reveals two different subclasses with distinct prognosis and core regulatory networks

BACKGROUND

Lung adenocarcinoma (LUAD) is a highly malignant and heterogeneous tumor that involves various oncogenic genetic alterations. Epigenetic processes play important roles in lung cancer development. However, the variation in enhancer and super-enhancer landscapes of LUAD patients remains largely unknown. To provide an in-depth understanding of the epigenomic heterogeneity of LUAD, we investigate the H3K27ac histone modification profiles of tumors and adjacent normal lung tissues from 42 LUAD patients and explore the role of epigenetic alterations in LUAD progression.

RESULTS

A high intertumoral epigenetic heterogeneity is observed across the LUAD H3K27ac profiles. We quantitatively model the intertumoral variability of H3K27ac levels at proximal gene promoters and distal enhancers and propose a new epigenetic classification of LUAD patients. Our classification defines two LUAD subgroups which are highly related to histological subtypes. Group II patients have significantly worse prognosis than group I, which is further confirmed in the public TCGA-LUAD cohort. Differential RNA-seq analysis between group I and group II groups reveals that those genes upregulated in group II group tend to promote cell proliferation and induce cell de-differentiation. We construct the gene co-expression networks and identify group-specific core regulators. Most of these core regulators are linked with group-specific regulatory elements, such as super-enhancers. We further show that CLU is regulated by 3 group I-specific core regulators and works as a novel tumor suppressor in LUAD.

CONCLUSIONS

Our study systematically characterizes the epigenetic alterations during LUAD progression and provides a new classification model that is helpful for predicting patient prognosis.

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.

The Prognostic Value of Non-Predominant Micropapillary Pattern in a Large Cohort of Resected Invasive Lung Adenocarcinoma Measuring ≤3 cm

The aim of this study was to analyze the influence of non-predominant micropapillary pattern in small sized invasive lung adenocarcinoma. A total of 986 lung adenocarcinoma patients with tumor size ≤3 cm were identified and classified according to the IALSC/ATS/ERS classification. Emphasis was placed on the impact of non-predominant micropapillary pattern on disease-free survival (DFS) and overall survival (OS). The relationship between lung adenocarcinoma subtype and lymph node involvement, EGFR mutation and KRAS mutation was also evaluated. A nomogram was developed to predict the probability of 3- and 5-year OS for these patients. The concordance index and calibration plot were used to validate this model. Among all 986 patients, the percentages of lymph node involvement were: 58.1, 50.0, 33.5, 21.4, 21.1, 10.9, 0, and 0% for micropapillary predominant, solid predominant, acinar predominant, papillary predominant, invasive mucinous adenocarcinoma (IMA), lepidic predominant, minimally invasive adenocarcinoma (MIA), adenocarcinoma in situ (AIS), respectively. The frequency of EGFR mutation in the cases of lepidic predominant, acinar predominant, MIA, micropapillary predominant, papillary predominant, solid predominant, IMA, and AIS were 51.1, 45.2, 44.4, 36.8, 29.3, 26.8, 8.3, and 0%, respectively. A non-predominant micropapillary pattern was observed in 344 (38.4%) invasive adenocarcinoma (IAC), and its presence predicted a poorer DFS (median: 56.0 months vs. 66.0 months, P <0.001) and OS (median: 61.0 months vs. 70.0 months, P <0.001). After propensity score matching, non-predominant micropapillary pattern retained its unfavorable effect on DFS (P = 0.007) and OS (P = 0.001). Multivariate analysis showed that non-predominant micropapillary pattern was identified as an independent prognostic factor for DFS (P = 0.003) and OS (P <0.001) in IAC. The nomogram showed good calibration and reliable discrimination ability (C-index = 0.775) to evaluated the 3- and 5-year OS. This retrospective analysis of patients with small sized IAC suggests the value of non-predominant micropapillary pattern to predict poor prognosis. A reliable nomogram model was constructed to provide personalized survival predictions.

Risk stratification model for patients with stage I invasive lung adenocarcinoma based on clinical and pathological predictors

Background

The aim of this study was to propose a new kind of pathological classification and further establish a prognostic model for resected stage I invasive adenocarcinoma (IADC).

Methods

Clinicopathological data were collected from 2 hospitals. The new proposed pathological reclassification was defined according to certain subtype instead of a predominant one. Survival curves were plotted by Kaplan-Meier analysis. Cox regressions were analyzed for recurrence-free survival (RFS) and overall survival (OS), through which prognostic scores and stratification models were established. The comparison between risk models and the eighth edition of tumor, node, metastasis (TNM) classification was conducted through receiver operating characteristic curves (ROC), as identified by the area under the curve (AUC) and z test.

Results

In all, 1,196 patients were enrolled. At multivariable analysis, solid and micropapillary of the new pathological reclassification, along with stage IA3 and IB were independent predictors for poorer RFS. Stage IB and smoking status significantly indicated worse OS. After normalization and standardization of log-hazard ratio (HR), personalized scores were calculated and the risk stratifications with 3 risk groups were generated. Compared with TNM classification, the risk model of RFS showed advantage over early-recurrence prediction (1-year: 0.653 vs. 0.556, P=0.033; 3-year: 0.663 vs. 0.076, P=0.008). No marked difference was observed in long-term RFS or OS.

Conclusions

Considering the harboring of certain patterns may be a new concept in adenocarcinoma classification. The risk stratification model based on this pathological classification and the eighth TNM classification showed remarkable superiority over TNM alone in predicting early recurrence of stage I adenocarcinoma. However, TNM classification remained valuable for long-term recurrence and survival prediction.

An NKX2-1/ERK/WNT feedback loop modulates gastric identity and response to targeted therapy in lung adenocarcinoma

Cancer cells undergo lineage switching during natural progression and in response to therapy. NKX2-1 loss in human and murine lung adenocarcinoma leads to invasive mucinous adenocarcinoma (IMA), a lung cancer subtype that exhibits gastric differentiation and harbors a distinct spectrum of driver oncogenes. In murine BRAFV600E-driven lung adenocarcinoma, NKX2-1 is required for early tumorigenesis, but dispensable for established tumor growth. NKX2-1-deficient, BRAFV600E-driven tumors resemble human IMA and exhibit a distinct response to BRAF/MEK inhibitors. Whereas BRAF/MEK inhibitors drive NKX2-1-positive tumor cells into quiescence, NKX2-1-negative cells fail to exit the cell cycle after the same therapy. BRAF/MEK inhibitors induce cell identity switching in NKX2-1-negative lung tumors within the gastric lineage, which is driven in part by WNT signaling and FoxA1/2. These data elucidate a complex, reciprocal relationship between lineage specifiers and oncogenic signaling pathways in the regulation of lung adenocarcinoma identity that is likely to impact lineage-specific therapeutic strategies.

Targeted Sequencing Analysis of Predominant Histological Subtypes in Resected Stage I Invasive Lung Adenocarcinoma

Objective: Lung adenocarcinoma (LADC) is classified into five main histological subtypes with distinct clinicopathologic characteristics: lepidic-predominant adenocarcinoma (LPA), acinar-predominant adenocarcinoma (APA), papillary-predominant adenocarcinoma (PPA), micropapillary-predominant adenocarcinoma (MPA) and solid-predominant adenocarcinoma (SPA). However, the mutational profiles of predominant histological subtypes have not been well defined. In this study, we aimed to reveal the genomic landscape of 5 main histological subtypes. Patients and Methods: We performed next-generation sequencing (NGS) in a cohort of 86 stage I invasive adenocarcinoma (IAC) patients, using a customized panel including 168 cancer-associated genes. Results: Our analysis identified a total of 302 genomic alterations. Five subtypes showed different mutation profiles with LPA, APA, PPA, MPA and SPA had an average mutation rate of 1.95 (range: 0-5), 2.56 (range: 1-6), 3.5 (range: 1-7), 3.75 (range: 1-8) and 6.05 (range: 2-12), respectively (p=4.17e-06). Driver mutations occurred in 96.55% (83/86) of all patients. EGFR (73.3%), KRAS (9.3%), ALK (4.7%) and MET (4.7%) are the most commonly mutated lung cancer driver genes, TP53 is the top mutated tumor suppressor gene. SPA patients harbored more driver mutations and higher frequency of TP53 than LPA patients. Interestingly, LRP1B mutations, which has been reported to be associated with high tumor mutation burden and better response to immunotherapy, were only detected from 5 SPA patients (p=0.001). No patients from other four cohorts harbored LRP1B mutations. Conclusions: We revealed distinctive mutation landscape of the 5 major histological subtypes of LADC, evident by distinctive average mutation rate with SPA and LPA having the highest and lowest average mutation rate, respectively. SPA patients showed higher mutation rate of LRP1B and higher rates for PD-L1 positivity, indicating that SPA patients may have better response to immunotherapy.

Diffuse expression of MUC6 defines a distinct clinicopathological subset of pulmonary invasive mucinous adenocarcinoma

Invasive mucinous adenocarcinoma (IMA) of the lung is a unique variant of lung adenocarcinoma. Aberrant mucin expression is associated with cancer development and metastasis. However, the clinicopathological significance of mucin expression in IMA is not fully understood. Herein, we evaluated the clinicopathological, immunohistochemical, and molecular characteristics of 70 IMA tumors. EGFR, KRAS, GNAS, and TP53 mutations were assessed by PCR-based sequencing. Next-generation sequencing was used to assess cases without EGFR/KRAS mutations. A NanoString-based screening for fusions was performed in all IMAs without mitogenic driver mutations. Expression of mucins (MUC1, MUC2, MUC4, MUC5AC, and MUC6) was evaluated by immunohistochemistry and categorized as follows: negative (<10% of tumor cells), patchy expression (<90% of tumor cells), or diffuse expression (≥90% of tumor cells). Immunohistochemical testing for transcription factors (TTF-1, CDX2, HNF1β, HNF3α, HNF3β, and HNF4α) was also performed. As expected, KRAS mutations were the most common (in 67% of cases), followed by small numbers of other alterations. Patchy or diffuse expression of MUC1, MUC2, MUC4, MUC5AC, and MUC6 was observed in 52% or 6%, 3% or 0%, 30% or 3%, 26% or 73%, and 59% or 27% of cases, respectively. Furthermore, all IMAs were generally positive for HNF1β (100%), HNF3α (100%), HNF3β (100%), and HNF4α (99%) but were positive less often for TTF-1 (6%) and CDX2 (9%). Overall, there was no significant correlation between mucin expression and transcription factor expression. Unexpectedly, diffuse expression of MUC6 was significantly associated with KRAS-wild-type tumors (p = 0.0008), smaller tumor size (p = 0.0073), and tumors in female patients (p = 0.0359) in multivariate analyses. Furthermore, patients with tumors exhibiting diffuse MUC6 expression had significantly favorable outcomes. Notably, none of these patients died of the disease. Our data suggested that diffuse expression of MUC6 defines a distinct clinicopathological subset of IMA characterized by wild-type KRAS and possibly less aggressive clinical course.

Comprehensive analysis of the clinicopathological features, targetable profile, and prognosis of mucinous adenocarcinoma of the lung

PURPOSE

The clinicopathological or genetic features related to the prognosis of mucinous adenocarcinoma are unknown because of its rarity. The clinicopathological or targetable features were investigated for better management of patients with mucinous adenocarcinoma of the lung.

METHODS

We comprehensively evaluated the clinicopathological and genetic features of 60 completely resected mucinous lung adenocarcinomas. Targetable genetic variants were explored using nCounter and polymerase chain reaction, PD-L1 and TTF-1 expression were evaluated using immunohistochemistry. We analyzed the prognostic impact using the Kaplan-Meier method and log-rank test.

RESULTS

Of the 60 enrolled patients, 13 (21.7%) had adenocarcinoma in situ/minimally invasive adenocarcinoma, and 47 (78.3%) had invasive mucinous adenocarcinoma (IMA). Fifteen patients (25%) showed a pneumonic appearance on computed tomography (CT). CD74-NRG1 fusion, EGFR mutations, and BRAF mutation were detected in three (5%), four (6.7%), and one (1.7%) patient(s), respectively. KRAS mutations were detected in 31 patients (51.7%). Two patients (3.5%) showed immunoreactivity for PD-L1. No in situ or minimally invasive cases recurred. IMA patients with pneumonic appearance had significantly worse recurrence-free survival (RFS) and overall survival (OS) (p < 0.001). Furthermore, IMA patients harboring KRAS mutations had worse RFS (p = 0.211). Multivariate analysis revealed that radiological pneumonic appearance was significantly associated with lower RFS (p < 0.003) and OS (p = 0.012). KRAS mutations served as an unfavorable status for RFS (p = 0.043).

CONCLUSION

Mucinous adenocarcinoma had a low frequency of targetable genetic variants and PD-L1 immunoreactivity; however, KRAS mutations were frequent. Pneumonic appearance on CT imaging and KRAS mutations were clinicopathological features associated with a worse prognosis.

Texture features of primary tumor on 18F-FDG PET images in non-small cell lung cancer: The relationship between imaging and histopathological parameters

OBJECTIVES

The aims of this study were to evaluate the relationships between textural features of the primary tumor on FDG PET images and clinical-histopathological parameters which are useful in predicting prognosis in newly diagnosed non-small cell lung cancer (NSCLC) patients.

MATERIAL AND METHODS

PET/CT images of ninety (90) patients with NSCLC prior to surgery were analyzed retrospectively. All patients had resectable tumors. From the images we acquired data related to metabolism (SUVmax, metabolic tumor volume [MTV] and total lesion glycolysis [TLG]) and texture features of primary tumors. Histopathological tumor types and subgroups, degree of Ki-67 expression and necrosis rates of the primary tumor, mediastinal lymph node (MLN) status and nodal stages were recorded.

RESULTS

Among the 2histologic tumor types (adenocarcinoma and squamous cell carcinoma) significant differences were present regarding metabolic parameters, Ki-67 index with higher values and kurtosis with lower values in the latter group. Textural heterogeneity was found to be higher in poorly differentiated tumors compared to moderately differentiated tumors in patients with adenocarcinoma. While Ki-67 index had significant correlations with metabolic parameters and kurtosis, tumor necrosis rate was only significantly correlated with textural features. By univariate and multivariate analyses of the imaging and histopathological factors examined, only gradient variance was significant predictive factor for the presence of MLN metastasis.

CONCLUSIONS

Textural features had significant associations with histologic tumor types, degree of pathological differentiation, tumor proliferation and necrosis rates. Texture analysis has potential to differentiate tumor types and subtypes and to predict MLN metastasis in patients with NSCLC.

Solid subtype predicts early bone metastases in sensitive EGFR-mutated lung adenocarcinoma patients after surgery

This study aimed to explore the prognostic significance of solid pattern for bone metastases (BM) in epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma patients after surgery. A total of 237 stage I-III lung adenocarcinoma patients with EGFR mutation were analyzed after procedure. The patients were divided into four groups: the solid-present patients with BM, the solid-absent patients with BM, the solid-present patients without BM and the solid-absent patients without BM. The bone disease-free survival (bDFS), systemic disease-free survival (DFS) and overall survival (OS) were assessed. The results revealed that the patients with solid pattern had shorter DFS (15 months vs. 19 months; P < 0.001) and OS (47 months vs. 77 months; P = 0.001). Moreover, bDFS of solid-present patients was significantly shorter than solid-absent patients (27 months vs. 14 months; P < 0.001). In addition, patients with solid component had worsened bDFS, no matter with BM as first-site development (12.5 months vs. 16.5 months; P = 0.016) or non-first-site development (16.5 months vs. 45.5 months; P < 0.001). These findings suggested that solid pattern predicted worse DFS and OS and also showed shortened interval between surgery and BM.

Predicting benign, preinvasive, and invasive lung nodules on computed tomography scans using machine learning

OBJECTIVE

The study objective was to investigate if machine learning algorithms can predict whether a lung nodule is benign, adenocarcinoma, or its preinvasive subtype from computed tomography images alone.

METHODS

A dataset of chest computed tomography scans containing lung nodules was collected with their pathologic diagnosis from several sources. The dataset was split randomly into training (70%), internal validation (15%), and independent test sets (15%) at the patient level. Two machine learning algorithms were developed, trained, and validated. The first algorithm used the support vector machine model, and the second used deep learning technology: a convolutional neural network. Receiver operating characteristic analysis was used to evaluate the performance of the classification on the test dataset.

RESULTS

The support vector machine/convolutional neural network-based models classified nodules into 6 categories resulting in an area under the curve of 0.59/0.65 when differentiating atypical adenomatous hyperplasia versus adenocarcinoma in situ, 0.87/0.86 with minimally invasive adenocarcinoma versus invasive adenocarcinoma, 0.76/0.72 atypical adenomatous hyperplasia + adenocarcinoma in situ versus minimally invasive adenocarcinoma, 0.89/0.87 atypical adenomatous hyperplasia + adenocarcinoma in situ versus minimally invasive adenocarcinoma + invasive adenocarcinoma, and 0.93/0.92 atypical adenomatous hyperplasia + adenocarcinoma in situ + minimally invasive adenocarcinoma versus invasive adenocarcinoma. Classifying benign versus atypical adenomatous hyperplasia + adenocarcinoma in situ + minimally invasive adenocarcinoma versus invasive adenocarcinoma resulted in a micro-average area under the curve of 0.93/0.94 for the support vector machine/convolutional neural network models, respectively. The convolutional neural network-based methods had higher sensitivities than the support vector machine-based methods but lower specificities and accuracies.

CONCLUSIONS

The machine learning algorithms demonstrated reasonable performance in differentiating benign versus preinvasive versus invasive adenocarcinoma from computed tomography images alone. However, the prediction accuracy varies across its subtypes. This holds the potential for improved diagnostic capabilities with less-invasive means.

Inclusion of multiple high-risk histopathological criteria improves the prediction of adjuvant chemotherapy efficacy in lung adenocarcinoma

Aims

The decision to consider adjuvant chemotherapy (AC) for non‐small cell lung cancer is currently governed by clinical stage. This study aims to assess other routinely collected pathological variables related to metastasis and survival for their ability to predict the efficacy of AC in lung adenocarcinoma.

Methods and results

A retrospective single‐centre series of 620 resected lung non‐mucinous adenocarcinoma cases from 2005 to 2015 was used. Digital images of all slides were subjected to central review, and data on tumour histopathology, AC treatment and patient survival were compiled. A statistical case matching approach was used to counter selection bias. Several high‐risk pathological criteria predict both pathological nodal involvement and early death: positive vascular invasion status (VI+) (HR = 2.10, P < 0.001), positive visceral pleural invasion status (VPI+) (HR = 2.16, P < 0.001), and solid/micropapillary‐predominant WHO tumour type (SPA/MPPA) (HR = 3.29, P < 0.001). Crucially, these criteria also identify patient groups benefiting from AC (VI + HR = 0.69, P = 0.167, VPI + HR = 0.44, P = 0.004, SPA/MPPA HR = 0.36, P = 0.006). Cases showing VI+/VPI+/SPA/MPPA histology in the absence of AC stage criteria were common (170 of 620 total), and 8 had actually received AC. This group showed much better outcomes than equivalent untreated cases in matched analysis (3‐year OS 100.0% versus 31.3%). Inclusion of patients with VI+/VPI+/SPA/MPPA histology would increase AC‐eligible patients from 51.0% to 84.0% of non‐mucinous tumours in our cohort.

Conclusions

Our data provide preliminary evidence that the consideration of AC in patients with additional high‐risk pathological indicators may significantly improve outcomes in operable lung adenocarcinoma, and that AC may be currently underused.

Risk of development of brain metastases according to the IASLC/ATS/ERS lung adenocarcinoma classification in locally advanced and metastatic disease

INTRODUCTION

Brain metastases (BM) are frequent among lung cancer patients, affecting prognosis and quality of life. The International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS) and European Respiratory Society (ERS) lung adenocarcinoma (LADC) classification (IASLC/ATS/ERS) has prognostic impact in early-stage disease; however, its role in the advanced setting is not precise. This study aims to determine the correlation between the predominant histological subtype and the risk of developing brain metastases (BM) in locally advanced and metastatic (stages IIIB-IV) LADC.

METHODS

A total of 710 patients with LADC were treated at our institution from January 2010 to December 2017. After excluding patients with brain metastases at diagnoses (n = 151), they were categorized according to the IASLC/ATS/ERS LADC classification to estimate the risk of developing brain metastases. A competing risk analysis was employed, considering death a competing risk event.

RESULTS

From 559 patients, the mean age was 59 ± 13.2 years, women (52.4 %), and clinical-stage IV (79.2 %). LADC subtypes distribution was lepidic (11.6 %), acinar (37.9 %), papillary (10.2 %), micropapillary (6.8 %), and solid (33.5 %). A total of 27.0 % of patients developed BM, 32.9 % died without brain affection, and 40.0 % did not progress. The predominantly solid subtype showed the greatest probability of all subtypes for developing BM [HR 4.0; 95 % CI (1.80-8.91), p = 0.0006], followed by micropapillary [HR1.11; 95 % CI (0.36-3.39), p = 0.85). The solid subtype, moderately differentiated tumors, age, and ECOG PS (>2) were associated with increased hazards in the multivariate analysis.

CONCLUSION

According to the IASLC/ATS/ERS classification, the predominantly solid pattern was significantly associated with an increased risk of developing BM in patients with locally advanced and metastatic LADC. Its prognostic value might help explore novel clinical approaches, modify monitoring for earlier detection, prevent complications, and reduce morbidity.

Predictors of upstage and treatment strategies for stage IA lung cancers after sublobar resection for adenocarcinoma in situ and minimally invasive adenocarcinoma

Background

Invasive adenocarcinoma intraoperatively underestimated as adenocarcinoma in situ (AIS) or minimally invasive adenocarcinoma (MIA) based on frozen section (FS) is more likely to undergo insufficient resection. We aimed to investigate the predictors of upstage and treatment strategies for stage IA invasive adenocarcinoma after sublobar resection for AIS and MIA.

Methods

We identified 2,006 patients from January 2012 to December 2016 with early-stage lung adenocarcinoma who underwent sublobar resection based on FS diagnosis to guide surgical decision-making. All FS were categorized into three groups in real-time: (I) atypical adenomatous hyperplasia (AAH), (II) AIS, and (III) MIA.

Results

A total of 272 (13.5%, 272/2,006) cases were upstaged in the final pathology (FP) diagnosis (82 AAH to AIS, 127 AIS to MIA, and nine AIS and 54 MIA to invasive adenocarcinoma), and most upstage cases (64.3%, 175/272) were attributed to sampling error. Multivariate logistic regression showed that tumor size ≥1 cm was the only independent predictor of upstage. The upstage of 209 cases to AIS or MIA had no influence on the therapy because the extent of their resection was enough. Of the 63 cases upstaged to invasive adenocarcinoma, only 13 cases agreed to receive complementary treatment: five patients underwent complementary lobectomy, and seven patients received chemotherapy. Two invasive adenocarcinoma cases without complementary treatment experienced a local recurrence after surgery. No recurrence was observed in AAH, AIS and MIA. No patient died until December 01, 2019.

Conclusions

Timely complementary treatment is encouraged in AIS/MIA upstaged to invasive adenocarcinoma based on the FP after sublobar resection to avoid local recurrence. Pathologists should be more cautious about AIS and MIA with tumor size ≥1 cm to avoid underestimation and potentially insufficient resection.

A predictive model for identifying candidates for adjuvant chemotherapy based on recurrence risk profile of resected, node-negative (N0) non-small cell lung cancer

Background

The decision for administering adjuvant chemotherapy (AC) in completely resected node-negative non-small cell lung cancer (NSCLC) is guided by likelihood of disease recurrence or death based on tumor, node, metastasis (TNM) stage. However, within each TNM stage are sub-groups of patients that are more or less likely to relapse than stage alone predicts.

Methods

In this retrospective cohort study, prospective data from 394 consecutive patients who underwent complete resection of node-negative NSCLC without adjuvant therapies, between 2002 and 2019 was retrospectively analyzed. Independent tumor and host risk factors for recurrence were subjected to multivariate analysis to develop a predictive risk model distributing patients into low-risk or high-risk categories.

Results

Recurrence risk was independently predicted by a neutrophil:lymphocyte ratio (NLR) of ≥3.5 [hazard ratio (HR), 1.9; 95% confidence interval (CI), 1.1–3.5], visceral pleural invasion (HR, 2.2; 95% CI, 1.3–3.8), histopathology other than adenocarcinoma or squamous cell (HR, 2.6; 95% CI, 1.2–5.5) and tumor size >33 mm (HR, 3.9; 95% CI, 2.3–6.7). The specific combination of risk factors contributed to a score for a risk model which classified 9% of Stage I and 69% of Stage ≥II patients as high-risk. The predicted 5-year disease-free survival (DFS) for high-risk and low-risk patients as scored by the predictive model was 30% and 85%, respectively.

Conclusions

Our readily reproducible, low-technology model, developed from individually validated tumor/host risk factors, identified sub-groups of resected node-negative NSCLC patients at significantly discordant risk of recurrence to their TNM stage category.

Optimised architecture-based grading system as an independent prognostic factor in resected lung adenocarcinoma

AIMS

Considering morphological heterogeneity of lung adenocarcinoma (LUAD) and no objective prognostic grading system existing currently, we aim to establish an 'optimised architecture-based grading system' (OAGS) to predict prognosis for resected LUAD.

METHODS

A multicentral study involving three independent cohorts of LUAD was conducted. Predictive ability of the OAGS for recurrence-free probability (RFP) and overall survival (OS) was assessed in training cohort (n=228) by the area under the receiver operating characteristic curve (AUC), Harrell's concordance index (C-index) and Kaplan-Meier survival analyses, which was validated in testing (n=135) and validation (n=226) cohorts.

RESULTS

The OAGS consists of: grade 1 for lepidic, papillary or acinar predominant tumour with no or less than 5% of high-grade patterns (cribriform, solid and or micropapillary), grade 2 for lepidic, papillary or acinar predominant tumour with 5% or more of high-grade patterns, and grade 3 for cribriform, solid or micropapillary predominant tumour. In all stages, the OAGS outperformed the pattern-dominant grading system and IASLC grading system for predicting RFP (C-index, 0.649; AUC, 0.742) and OS (C-index, 0.685; AUC, 0.754). Multivariate analysis identified it as an independent predictor of both (RFP, p<0.001; OS, p<0.001). Furthermore, in pT1-2aN0M0 subgroup, the OAGS maintained its ability to predict recurrence (C-index, 0.699; AUC, 0.769) and stratified patients into different risk groups of RFP (p<0.001). These results were confirmed in testing and validation cohorts.

CONCLUSIONS

The OAGS is an independent prognostic factor and shows a robust ability to predict prognosis for resected LUAD.

Solid component ratio influences prognosis of GGO-featured IA stage invasive lung adenocarcinoma

Background

The computed tomography (CT) characteristic of ground glass opacity (GGO) were shown to be associated with clinical significance in lung adenocarcinoma. We evaluated the prognostic value of the solid component ratio of GGO IA invasive lung adenocarcinoma.

Methods

We retrospectively analyzed the records of GGO IA patients who received surgical resection from April 2012 to December 2015. The solid component ratio was calculated based on thin-slice CT scans. Baseline features were compared stratified by the ratio. Cox proportional hazard models and survival analyses were adopted to explore potential prognostic value regarding overall survival (OS) and disease-free survival (DFS).

Results

Four hundred fifteen patients were included. The higher ratio was significantly associated with larger tumor diameter, pathological subtypes and choice of surgical type. There was a significantly worse DFS with a > 50% ratio. The subgroups of 0% and ≤ 50% ratio showed close survival curves of DFS. Similar trends were observed in OS. Multivariate analyses revealed that the ratio was a significant predictor for DFS, but not for OS. No significant prognostic difference was observed between lobectomy and limited resections.

Conclusion

A higher solid component ratio may help to predict a significantly worse prognosis of GGO IA lung adenocarcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40644-020-00363-6.

Multi-Window CT Based Radiological Traits for Improving Early Detection in Lung Cancer Screening

Rationale and Objectives

Evaluate ability of radiological semantic traits assessed on multi-window computed tomography (CT) to predict lung cancer risk.

Materials and Methods

A total of 199 participants were investigated, including 60 incident lung cancers and 139 benign positive controls. Twenty lung window features and 2 mediastinal window features were extracted and scored on a point scale in three screening rounds. Multivariate logistic regression analysis was used to explore the association of these radiological traits with the risk of developing lung cancer. The areas under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and positive predictive value (PPV) were computed to evaluate the best predictive model.

Results

Combining mediastinal window-specific features with the lung window features-based model significantly improves performance compared to individual window features. Model performance is consistent both at baseline and the first follow-up scan, with an AUROC increased from 0.822 to 0.871 (p = 0.009) and from 0.877 to 0.917 (p = 0.008), respectively, for single to multi-window feature models. We also find that the multi-window CT based model showed better specificity and PPV, with PPV at the second follow-up scan improved to 0.953.

Conclusion

We find combining window semantic features improves model performance in identifying cancerous nodules. We also find that lung window features are more informative compared to mediastinal features in predicting malignancy.

Comparison of Surgical Outcomes Between Invasive Mucinous and Non-Mucinous Lung Adenocarcinoma

BACKGROUND

Invasive mucinous adenocarcinoma (IMA) is a rare subtype of invasive lung adenocarcinoma. However, the clinical course and prognostic outcomes following IMA resection, particularly postoperative recurrence, remain unclear.

METHODS

We pathologically reevaluated 1362 lung adenocarcinoma resections performed at our institution, categorizing cases into the IMA group (72 cases) and non-IMA group (1290 cases). The IMA group was further classified into pneumonia and nodular types based on preoperative computed tomography.

RESULTS

Overall, the IMA group had lower carcinoembryonic antigen levels (3 vs 8 ng/mL; P < .01), fewer lymph node metastasis (4% vs 24%; P < .01), and more KRAS mutations (56% vs 7%; P < .01) than the non-IMA group. Although postoperative recurrence rates did not differ between both groups (32% vs 27%; P = 0.35), lung recurrence occurred more frequently in the IMA group (83% vs 17%; P < .01). Propensity score-matched pair analysis showed that the IMA group had fewer lymph node metastasis (3% vs 35%; P < .01), more KRAS mutations (56% vs 9%; P < .01), and higher intrapulmonary recurrence rate (84% vs 31%; P < .01) than the non-IMA group. The 5-year overall survival rates did not differ between both groups (74% vs 81%; P = 0.26). However, among patients with intrapulmonary recurrence, those in the IMA group had significantly worse prognosis than those in the non-IMA group (35% vs 77%; P < .01).

CONCLUSIONS

Intrapulmonary recurrence, which induced significantly worse prognosis, was more likely to occur in the IMA than non-IMA group.

Immunotherapy Moves to the Early-Stage Setting in Non-Small Cell Lung Cancer: Emerging Evidence and the Role of Biomarkers

Despite numerous advances in targeted therapy and immunotherapy in the last decade, lung cancer continues to present the highest mortality rate of all cancers. Targeted therapy based on specific genomic alterations, together with PD-1 and CTLA-4 axis blocking-based immunotherapy, have significantly improved survival in advanced non-small cell lung cancer (NSCLC) and both therapies are now well-established in this clinical setting. However, it is time for immunotherapy to be applied in patients with early-stage disease, which would be an important qualitative leap in the treatment of lung cancer patients with curative intent. Preliminary data from a multitude of studies are highly promising, but therapeutic decision-making should be guided by an understanding of the molecular features of the tumour and host. In the present review, we discuss the most recently published studies and ongoing clinical trials, controversies, future challenges and the role of biomarkers in the selection of best therapeutic options.

Exceptional Survival Among Kentucky Stage IV Non-small Cell Lung Cancer Patients: Appalachian Versus Non-Appalachian Populations

PURPOSE

To determine differences in exceptional survival (ES)-survival of 5 years or more past diagnosis-between stage IV non-small cell lung cancer (NSCLC) patients residing in the Appalachian versus non-Appalachian regions of Kentucky.

METHODS

This was a population-based, retrospective case-control study of Kentucky patients, diagnosed with stage IV NSCLC between January 1, 2000, and December 31, 2011. The data were drawn from the Kentucky Cancer Registry.

FINDINGS

Findings from the multivariable logistic regression revealed no significant differences in the odds of ES between patients who resided in Appalachian versus non-Appalachian Kentucky. Being female and undergoing surgery only as the first course of treatment were associated with higher odds of ES. Increasing age, unspecified histology, having poorly differentiated or undifferentiated carcinomas, and receiving radiation therapy only as the first course of treatment were associated with decreased odds of ES.

CONCLUSION

Differences in the odds of ES among stage IV NSCLC patients were not related to residence in Appalachian versus non-Appalachian Kentucky. ES was associated with other nongenetic and treatment factors that warrant further investigations.

New International Association for the Study of Lung Cancer (IASLC) Pathology Committee Grading System for the Prognostic Outcome of Advanced Lung Adenocarcinoma

Simple Summary

This study investigated the association between survival outcome and the new grading system among advanced stage lung adenocarcinoma (LADC) (stages IIIA, IIIB and IV) patients who were diagnosed as LADC with a pathologic report according to a new grading system by the International Association for the Study of Lung Cancer (IASLC) pathology committee. The results indicate that the poorly differentiated group had a poorer prognosis in PFS, as did patients with wild-type EGFR who were treated with chemotherapy. No survival difference could be found among EGFR mutation patients. Older age and a lower body mass index also led to worse survival. Patients with poorly differentiated adenocarcinoma likewise had worse survival, especially compared to those with moderately differentiated adenocarcinoma. Our findings highlight that the therapeutic regimen should be adjusted for wild-type EGFR patients with poorly differentiated adenocarcinoma treated with chemotherapy to provide better outcomes. No survival difference could be seen among EGFR mutation patients.

Abstract

The impact of the new International Association for the Study of Lung Cancer pathology committee grading system for advanced lung adenocarcinoma (LADC) on survival is unclear, especially in Asian populations. In this study, we reviewed the prognostic outcomes of patients with late-stage disease according to the new grading system. We reviewed 136 LADC cases who underwent a small biopsy from 2007 to 2018. Tumors were classified according to the new grading system for LADC. Baseline characteristics (age, sex, smoking status, body mass index, and driver gene mutations) were analyzed. Kaplan–Meier and Cox regression analyses were used to determine correlations with the new grading system and prognosis. Patients with poorly differentiated adenocarcinoma were significantly correlated with a poor progression-free survival (PFS) (p = 0.013) but not overall survival (OS) (p = 0.154). Subgroup analysis showed that wild-type EGFR patients with poorly differentiated adenocarcinoma treated with chemotherapy had significantly worse PFS (p = 0.011). There was no significant difference in survival among the patients with epidermal growth factor receptor mutations who were treated with tyrosine kinase inhibitors. Patients aged >70 years and those with a BMI ≤ 25 kg/m² and wild-type patients had significantly worse OS in both univariate (HR = 1.822, p = 0.006; HR = 2.250, p = 0.004; HR = 1.537, p = 0.046, respectively) and multivariate analyses (HR = 1.984, p = 0.002; HR = 2.383, p = 0.002; HR = 1.632, p = 0.028, respectively). Despite therapy, patients with poorly differentiated tumors still fared worse than those with better differentiated tumors. No differences were found among the EGFR mutations treated with TKI. Our findings highlight that the therapeutic regimen should be adjusted for EGFR Wild-type patients with poorly differentiated adenocarcinoma treated with chemotherapy to provide better outcomes.

Prognostic impact of lung adenocarcinoma second predominant pattern from a large European database

BACKGROUND AND OBJECTIVES

Adenocarcinoma patterns could be grouped based on clinical behaviors: low- (lepidic), intermediate- (papillary or acinar), and high-grade (micropapillary and solid). We analyzed the impact of the second predominant pattern (SPP) on disease-free survival (DFS).

METHODS

We retrospectively collected data of surgically resected stage I and II adenocarcinoma.

SELECTION CRITERIA

anatomical resection with lymphadenectomy and pathological N0. Pure adenocarcinomas and mucinous subtypes were excluded. Recurrence rate and factors affecting DFS were analyzed according to the SPP focusing on intermediate-grade predominant pattern adenocarcinomas.

RESULTS

Among 270 patients, 55% were male. The mean age was 68.3 years. SPP pattern appeared as follows: lepidic 43.0%, papillary 23.0%, solid 14.4%, acinar 11.9%, and micropapillary 7.8%. The recurrence rate was 21.5% and 5-year DFS was 71.1%. No difference in DFS was found according to SPP (p = .522). In patients with high-grade SPP, the percentage of SPP, age, and tumor size significantly influenced DFS (p = .016). In patients with lepidic SPP, size, male gender, and lymph-node sampling (p = .005; p = .014; p = .038, respectively) significantly influenced DFS.

CONCLUSIONS

The impact of SPP on DFS is not homogeneous in a subset of patients with the intermediate-grade predominant patterns. The influence of high-grade SPP on DFS is related to its proportion in the tumor.

Prognostic Significance of Ground-Glass Opacity Components in 5-Year Survivors With Resected Lung Adenocarcinoma

BACKGROUND

Reports on the prognosis for 5-year survivors with lung adenocarcinoma after resection are sparse. This study aimed to identify factors associated with overall survival (OS) and cancer-specific survival (CSS) for 5-year survivors with completely resected lung adenocarcinoma, and to determine whether preoperative imaging factors, including the presence of ground-glass opacity (GGO) components, affect late recurrence in long-term survivors.

METHODS

Complete resection of lung adenocarcinoma was performed for 1681 patients between January 2000 and December 2013. Of these patients, 936 who survived 5 years or longer after surgery were identified, and factors associated with OS and CSS were determined using the Cox proportional hazard model.

RESULTS

Multivariable analysis demonstrated that lymph node metastasis (p < 0.01) and absence of GGO components (p < 0.01) were independently associated with OS and CSS for the 5-year survivors. The absence of GGO components was significantly associated with OS (p < 0.01) and CSS (p < 0.01) also for the 5-year survivors with stage 1 disease (n = 782) and for the 5-year survivors without recurrence (n = 809). The incidence of recurrence anytime during the 10-year postoperative follow-up period differed significantly between the 5-year survivors with and without GGO components.

CONCLUSIONS

The absence of GGO components was significantly associated with an unfavorable prognosis for the 5-year survivors with completely resected lung adenocarcinoma regardless whether they had recurrences not.

A retrospective study of the relationship between the pathologic subtype and lymph node metastasis of lung adenocarcinomas of ≤3 cm diameter

To analyze the relationship between pathologic subtype and lymph node metastasis for lung adenocarcinomas of ≤3 cm diameter.We retrospectively studied 384 patients with operable lung adenocarcinomas of ≤3 cm diameter that had been radically resected by lobectomy or anatomic segmentectomy with systematic nodal dissection, at the Fujian Medical University Union Hospital between March 2014 and March 2016.Lymph node metastasis pN1 + pN2 (pN+) was found in 2 of 104 (1.9%) patients with tumor diameter ≤1.0 cm, 12 of 159 (7.5%) patients with tumor diameter >1.0 cm but ≤2.0 cm, and 35 of 121 (28.9%) patients with tumor size >2.0 cm but ≤3.0 cm (P < .01). Lymph node metastasis pN+ was found in 19 of 53 (35.8%) patients with visceral invasion pleural (VIP) and 30 of 331 (9.0%) patients without VIP (P < .05). It was also found in 16 of 51 (31.3%) patients with high serum CEA concentrations and 28 of 297 (9.4%) patients with normal concentrations (P < .05). In a multivariate analysis, tumor diameter, VIP, high serum CEA concentration, and pathologic subtype were significant risk factors. The prevalences of lymph node metastasis pN+ were: 0.0% (0/2), 0.0% (0/89), 3.2% (1/31), 16.2% (34/209), 7.7% (1/13), 46.7% (7/15), 100% (4/4), and 11.8% (2/17) for adenocarcinoma in situ (AIS); minimally invasive adenocarcinoma (MIA); predominantly lepidic (LEP), acinar (ACI), papillary, solid (SOL), and micropapillary (MIP) tumors; and variants of invasive adenocarcinoma, respectively (P < .05). For predominant SOL and MIP tumors, the prevalences of lymph node involvement were significantly higher than for the other subtypes.We have shown that lymph node metastasis in patients with tumor diameter ≤3 cm differs according to lung adenocarcinoma subtype. AIS and MIA were not associated with lymph node metastasis; therefore, systematic nodal dissection may be unnecessary. The prevalence of lymph node metastasis rate was low for LEP, suggesting that systemic lymph node sampling is sufficient. In contrast, for other pathologic subtypes, including SOL and MIP, systematic lymph node dissection should be performed.

Differences in PET/CT standardized uptake values involvement and survival compared to histologic subtypes of lung adenocarcinoma

PURPOSE

Lung adenocarcinoma is histologically diverse but has distinct histologic growth patterns. There is no consensus on the clinical benefit of this histologic model. We aimed to evaluate the differences in the distribution of the preoperative primary tumor positron emission tomography (PET)/computed tomography (CT) standardized uptake values (SUVs) and survival in the lung adenocarcinoma subtypes.

METHODS

We retrospectively evaluated the data of 107 patients with resected lung adenocarcinoma who had preoperative PET/CT between 2005 and 2017 in a single center. Patients had lepidic, acinar, papillary, micropapillary, and solid histologic subtypes. We compared fluorodeoxyglucose SUVs and survival data of histologic subtypes.

RESULTS

The median age of the patients was 62 years (40-75), 76.4% were male, the median SUVmax was 9.4 (1-36.7), and the median follow-up time was 29 months (3-135 months). The median overall survival (OS) was 71 months and the median progression-free survival (PFS) was 33 months. SUVmax was significantly different in histologic subtypes: values for papillary, micropapillary, solid, acinar, and lepidic subtypes were 9.7, 8, 12, 9.1, and 3.9, respectively (p = 0.000). Solid predominant adenocarcinoma had significantly higher SUVmax than the other subtypes (p = 0.001). Lepidic predominant adenocarcinoma had significantly lower SUVmax than the other subtypes (p = 0.000). There was no significant difference in OS between histologic subtypes (p = 0.66), but PFS was significantly different between the groups (p = 0.017), and the solid subtype had a shorter PFS than the other histologic subtypes.

CONCLUSION

Lung adenocarcinoma consists of a diverse group of diseases. Different SUVmax values are seen in different histologic subtypes of nonmetastatic lung adenocarcinoma. Solid predominant types have high SUVmax values while lepidic predominant types have lower SUVmax values. The solid subtype had a shorter PFS than the other histologic subtypes.

Prognosis of early stage pulmonary mucinous adenocarcinoma with different treatments

BACKGROUND

The effects of surgical approach and adjuvant chemotherapy (AC) of early stage pulmonary mucinous adenocarcinoma (MAD) have not been thoroughly studied yet. This study intends to clarify whether AC provides clinical benefit to the early stage MAD patients and the survival difference between surgical approaches.

METHODS

All cases of stage I MAD were identified from the SEER database during the period of 2009-2014. The primary cohort was divided into AC and surgery (S) groups. Meanwhile, the patients with tumor ≤1 cm were divided into lobectomy and sublobar resection group. Clinical characteristics, treatments and survival data including overall survival (OS) and cancer-specific survival (CSS) were analyzed.

RESULTS

A total of 1,816 patients were included in the final cohort. Referring to surgical procedure, 140 patients received lobectomy and 75 patients received sublobar resection. AC showed worse survival outcomes than surgery alone (OS: 71.2 vs. 93.4 months; CSS: 74.9 vs. 101.1 months). No significant difference was observed between lobectomy group and sublobar resection group (OS: 97.3 vs. 93.1 months; CSS: 103.7 vs. 101.3 months). Consistent results were also shown after the propensity score matching analysis (PSM) was applied.

CONCLUSIONS

Early stage of MAD has an ideal prognosis. AC may bring adverse effects which would lower OS and CSS of stage I MAD patients. No significant difference is observed in the comparison of prognosis between lobectomy and sublobar resection in tumor size ≤1 cm MAD patients.

Predicting the invasiveness of lung adenocarcinomas appearing as ground-glass nodule on CT scan using multi-task learning and deep radiomics

Background

Due to different treatment method and prognosis of different subtypes of lung adenocarcinomas appearing as ground-glass nodules (GGNs) on computed tomography (CT) scan, it is important to classify invasive adenocarcinomas from non-invasive adenocarcinomas. The purpose of this paper is to build and evaluate the performance of deep learning networks on the differentiation the invasiveness of lung adenocarcinoma appearing as GGNs.

Methods

This retrospective study included 886 GGNs from 794 pathological confirmed patients with lung adenocarcinoma for training and testing the proposed networks. Three deep learning networks, namely XimaNet (deep learning-based classification model), XimaSharp (classification and nodule segmentation model), and Deep-RadNet (deep learning and radiomics combined classification model, i.e., deep radiomics) were built. Three classification tasks, namely task 1: classification of AAH/AIS and MIA, task 2: classification of MIA and IAC, and task 3: classification of non-invasive adenocarcinomas and invasive adenocarcinomas (AAH/AIS&MIA and IAC) were conducted to evaluate the model performance. The Z-test was used to compare the model performance.

Results

The AUC for classification of AAH/AIS with MIA were 0.891, 0.841 and 0.779 for Deep-RadNet, XimaNet and XimaSharp respectively. The AUC for classification of MIA with IAC were 0.889, 0.785 and 0.778 for three networks and AUC for classification of AAH/AIS&MIA with IAC were 0.941, 0.892 and 0.827 respectively. The performance of deep_RadNet was better than the other two models with the Z-test (P<0.05).

Conclusions

Deep-RadNet with the visual heat map could evaluate the invasiveness of GGNs accurately and intuitively, providing a theoretical basis for individualized and accurate medical treatment of patients with GGNs.

Molecular differences across invasive lung adenocarcinoma morphological subgroups

Background

Lung adenocarcinomas (ADCs) show heterogeneous morphological patterns that are classified into five subgroups: lepidic predominant, papillary predominant, acinar predominant, micropapillary predominant and solid predominant. The morphological classification of ADCs has been reported to be associated with patient prognosis and adjuvant chemotherapy response. However, the molecular mechanisms underlying the morphology differences among different subgroups remain largely unknown.

Methods

Using the molecular profiling data from The Cancer Genome Atlas (TCGA) lung ADC (LUAD) cohort, we studied the molecular differences across invasive ADC morphological subgroups.

Results

We showed that the expression of proteins and mRNAs, but not the gene mutations copy number alterations (CNA), were significantly associated with lung ADC morphological subgroups. In addition, expression of the FOXM1 gene (which is negatively associated with patient survival) likely plays an important role in the morphological differences among different subgroups. Moreover, we found that protein abundance of PD-L1 were associated with the malignancy of subgroups. These results were validated in an independent cohort.

Conclusions

This study provides insights into the molecular differences among different lung ADC morphological subgroups, which could lead to potential subgroup-specific therapies.

CT-Based Deep Learning Model for Invasiveness Classification and Micropapillary Pattern Prediction Within Lung Adenocarcinoma

Objective: Identification of tumor invasiveness of pulmonary adenocarcinomas before surgery is one of the most important guides to surgical planning. Additionally, preoperative diagnosis of lung adenocarcinoma with micropapillary patterns is also critical for clinical decision making. We aimed to evaluate the accuracy of deep learning models on classifying invasiveness degree and attempted to predict the micropapillary pattern in lung adenocarcinoma.

Methods: The records of 291 histopathologically confirmed lung adenocarcinoma patients were retrospectively analyzed and consisted of 61 adenocarcinoma in situ, 80 minimally invasive adenocarcinoma, 117 invasive adenocarcinoma, and 33 invasive adenocarcinoma with micropapillary components (>5%). We constructed two diagnostic models, the Lung-DL model and the Dense model, based on the LeNet and the DenseNet architecture, respectively.

Results: For distinguishing the nodule invasiveness degree, the area under the curve (AUC) value of the diagnosis with the Lung-DL model is 0.88 and that with the Dense model is 0.86. In the prediction of the micropapillary pattern, overall accuracies of 92 and 72.91% were obtained for the Lung-DL model and the Dense model, respectively.

Conclusion: Deep learning was successfully used for the invasiveness classification of pulmonary adenocarcinomas. This is also the first time that deep learning techniques have been used to predict micropapillary patterns. Both tasks can increase efficiency and assist in the creation of precise individualized treatment plans.

[Progress in Research on the Cribriform Component in Lung Adenocarcinoma]

The morbidity of lung cancer ranks top in the world. At present, lung adenocarcinoma (LUAD) is the most common histologic type of lung cancer. However, the prognoses of LUAD patients with the same subtype remain heterogeneous. Histological heterogeneity is one of the main causes of diverse prognoses of patients with LUAD. Studies have shown that there are other histologic patterns that affect the clinical outcomes of LUAD patients, in addition to the five growth patterns of invasive LUAD classified by the World Health Organization (WHO) in 2015. The cribriform component (CC) is one of the research hotspots among histopathology of LUAD. Previous studies have shown that the presence of CC can further stratify the prognoses of patients with LUAD. Along with the progressively deep insights into the aforementioned topic, researchers are dedicating to unveiling the relationships among CC and and other clinicopathological factors as well as their joint influence on the survival of LUAD patients. The review manages to generalize the latest research progress in the CC in LUAD patients.

Value of 18F-FDG PET/CT-based radiomics model to distinguish the growth patterns of early invasive lung adenocarcinoma manifesting as ground-glass opacity nodules

Background

To establish and validate ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET/CT-based radiomics model and use it to predict the intermediate-high risk growth patterns in early invasive adenocarcinoma (IAC).

Methods

Ninety-three ground-glass nodules (GGNs) from 91 patients with stage I who underwent a preoperative ¹⁸F-FDG PET/CT scan and histopathological examination were included in this study. The LIFEx software was used to extract 52 PET and 49 CT radiomic features. The least absolute shrinkage and selection operator (LASSO) algorithm was used to select radiomic features and develop radiomics signatures. We used the receiver operating characteristics curve (ROC) to compare the predictive performance of conventional CT parameters, radiomics signatures, and the combination of these two. Also, a nomogram based on conventional CT indicators and radiomics signature score (rad-score) was developed.

Results

GGNs were divided into lepidic group (n = 18) and acinar-papillary group (n = 75). Four radiomic features (2 for PET and 2 for CT) were selected to calculate the rad-score, and the area under the curve (AUC) of rad-score was 0.790, which was not significantly different as the attenuation value of the ground-glass opacity component on CT (CT_GGO) (0.675). When rad-score was combined with edge (joint model), the AUC increased to 0.804 (95% CI [0.699–0.895]), but which was not significantly higher than CT_GGO (P = 0.109). Furthermore, the decision curve of joint model showed higher clinical value than rad-score and CT_GGO, especially under the purpose of screening for intermediate-high risk growth patterns.

Conclusion

PET/CT-based radiomics model shows good performance in predicting intermediate-high risk growth patterns in early IAC. This model provides a useful method for risk stratification, clinical management, and personalized treatment.

Histopathological subtyping is a prognostic factor in stage IV lung adenocarcinoma

Lung adenocarcinoma is a heterogeneous tumor made of different architectural patterns. These tumors are classified into subtypes according to the predominant pattern in the primary tumor because the predominant pattern is related to overall survival. The prognostic role of these subtypes in stage IV disease is not well known, and most lung adenocarcinomas are diagnosed at the stage of metastatic disease. We aimed to evaluate the prognostic role of histopathological subtypes in lung adenocarcinoma metastases in a retrospective study of 253 patients with clinical, histopathological and molecular data. The presence of the solid subtype was related to overall survival (p = 0.045); the median overall survival was 6.8 months (95 % confidence interval (95 %CI) 4.4-9.1) when present and 11.1 months (95 %CI 8.6-21.3) when absent. Thyroid transcription factor 1 (TTF-1) immunohistochemistry was related to overall survival (p < 0.001); the median overall survival was 11.2 months (95 %CI 8.4-17.7) when positive and 4 months (95 %CI 2.3-5.7) when negative. On multivariate analysis, the presence of the solid subtype (p = 0.0036, hazard ratio (HR) 1.55, 95 %CI 1.03-2.34), TTF-1 positivity (p = 0.044, HR 0.64, 95 %CI 0.42-0.98), age <60 years at the time of resection (p = 0.017, HR 1.89; 95 %CI 1.12-3.21), performance status <2 (p = 0.017, HR 0.57; 95 %CI 0.36-0.91), treatment by chemotherapy (p = 0.033, HR 0.54, 95 %CI 0.31-0.95), and treatment by tyrosine kinase inhibitor or immunotherapy (p = 0.013, HR 0.36, 95 %CI 0.17-0.81) were related to overall survival. The evaluation of architectural pattern in metastases in stage IV patients provides further information for physicians about patient prognosis. This information might be included in clinical trials in patients with stage IV lung adenocarcinoma.

Microenvironmental Activation of Nrf2 Restricts the Progression of Nrf2-Activated Malignant Tumors

The transcription factor Nrf2 activates transcription of cytoprotective genes during oxidative and electrophilic insults. Nrf2 activity is regulated by Keap1 in a stress-dependent manner in normal cells, and somatic loss-of-function mutations of Keap1 are known to induce constitutive Nrf2 activation, especially in lung adenocarcinomas, conferring survival and proliferative benefits to tumors. Therefore, several therapeutic strategies that aim to inhibit Nrf2 in tumors have been developed for the treatment of Nrf2-activated cancers. Here we addressed whether targeting Nrf2 activation in the microenvironment can suppress the progression of Nrf2-activated tumors. We combined two types of Keap1-flox mice expressing variable levels of Keap1 with a Kras-driven adenocarcinoma model to generate Keap1-deficient lung tumors surrounded by normal or Keap1-knockdown host cells. In this model system, activation of Nrf2 in the microenvironment prolonged the survival of Nrf2-activated tumor-bearing mice. The Nrf2-activated microenvironment suppressed tumor burden; in particular, preinvasive lesion formation was significantly suppressed. Notably, loss of Nrf2 in bone marrow-derived cells in Nrf2-activated host cells appeared to counteract the suppression of Nrf2-activated cancer progression. Thus, these results demonstrate that microenvironmental Nrf2 activation suppresses the progression of malignant Nrf2-activated tumors and that Nrf2 activation in immune cells at least partially contributes to these suppressive effects. SIGNIFICANCE: This study clarifies the importance of Nrf2 activation in the tumor microenvironment and in the host for the suppression of malignant Nrf2-activated cancers and proposes new cancer therapies utilizing inducers of Nrf2.

Appreciation of Pattern in Diagnosis of Lung Adenocarcinoma from Cytology Specimen: Our Experience with Fine Needle Aspiration Cytology and Cell Block in a Resource Constraint Setup

BACKGROUND AND AIMS

Advent of personalised treatment needs correct diagnosis of lung adenocarcinoma with its molecular subtyping. Minimal use of special stain or immunohistochemistry (IHC) in small specimens save material for molecular testing. Various histologic patterns in adenocarcinoma (ADC) subtypes have different prognostic implications and current recommendation is to describe these patterns in small specimens. Aim of this study was to diagnose adenocarcinoma from cytology specimens depending on adenocarcinoma pattern on fine needle aspiration smears and cell blocks. We also studied the additional role of cell blocks as a platform for special stain and IHC.

MATERIALS AND METHODS

Conventional smears and cell block (CB) preparation were examined from transthoracic CT guided FNA samples of suspicious lung malignancy cases. Clear defining architectural pattern and cytomorphological features in favour of adenocarcinoma were evaluated and mucin stain and IHC were used as and when required.

RESULTS

A total of 86 cases were included in this study, of which 83 cases were diagnosed as adenocarcinoma, 52 (62.5%) showed clear cut evidence of adenocarcinoma from smears and CBs. CB morphology alone aided the diagnosis in 12. Various ADC patterns in combination or alone were appreciated in these 64 cases. Sixteen needed mucin stain and 3 needed IHC for diagnosis. Forty one were ADC with solid pattern of which 39 showed high nuclear grade.

CONCLUSION

Adequately cellular FNA smears and corresponding cell blocks of optimal quality can aid effectively in diagnosing adenocarcinoma and appreciating its pattern. Therefore, it would minimize the need for special stain and/or IHC with preservation of more material for molecular testing.

Association of histologic subtypes with genetic alteration and PD-L1 expression in pulmonary adenocarcinoma

Genetic alteration and programmed death-ligand 1 (PD-L1) expression have been revealed to be associated with various subtypes of pulmonary adenocarcinoma (ADC). The present study aimed to explore the association between histological subtypes and genetic alterations and PD-L1 expression. A total of 375 cases of pulmonary ADC were included. Genetic alterations were determined using next generation sequencing (NGS) in 136 cases. PD-L1 expression was detected by immunohistochemistry (based on clone 22C3) in the remaining 239 cases. Mutations in the epidermal growth factor receptor gene (EGFR) were detected in 76 (55.8%) cases associated with the papillary subtype (P=0.038). Mutations in the Kirsten rat sarcoma viral oncogene homolog gene (KRAS) were present in 46 (33.8%) cases associated with the lepidic subtype (P<0.001) and mucinous ADC (P=0.037). PD-L1 expression was identified in 63 (26.4%) cases associated with the solid subtype (P<0.001). In conclusion, the present study demonstrated that EGFR and KRAS mutations, alongside PD-L1 protein expression are significantly associated with specific subtypes of pulmonary ADC. These results should aid our ability to accurately select appropriate areas of the heterogeneous tumor for molecular testing methods and to predict patient outcomes and prognosis.

Predicting postoperative non-small cell lung cancer prognosis via long short-term relational regularization

OBJECTIVES

Lung cancer is the leading cause of cancer death worldwide. Prognosis of lung cancer plays a crucial role in the clinical decision-making process to optimize the treatment for patients. Most of the existing data-driven prognostic prediction models explore the relations between patient's characteristics and outcomes at a specific time interval. Although valuable, they neglect the relations between long-term and short-term prognoses and thus may limit the prediction performance.

METHODS

In this study, we present a novel prognostic prediction approach for postoperative NSCLC patients. Specifically, we formulate the learning objective function by exploiting the relations between long-term and short-term prognoses via a long short-term relational regularization. The regularization term is composed of two parts, i.e., the similarities between prognoses measured by patients' outcomes and the L₂ -norms between the corresponding prognoses' weight vectors. Based on this regularization, the proposed method can extract critical risk factors that comprehensively consider the long-term and short-term prognoses to facilitate the estimation of clinical risks.

RESULTS

We evaluate the proposed model on a clinical dataset containing 693 consecutive postoperative NSCLC patients with more than 5-year follow-up from 2006 to 2015. Our best models achieve 0.743, 0.709, and 0.746 AUCs for 1-year, 3-year, and 5-year survival prediction, 0.696, 0.724, and 0.736 AUCs for 1-year, 3-year, and 5-year recurrence prediction, respectively. The experimental results show the efficiency of our proposed model in improving the performances on 1-year prognostic prediction in comparison with benchmark models. By comparing with the model without the long short-term relational regularization, the proposed model extracts more consistent critical risk factors for both long-term and short-term prognoses and contains fewer unreasonable risk factors under the clinician's review.

CONCLUSIONS

We conclude that the proposed model can effectively exploit the relations between long-term and short-term prognoses. And the risk factors recognized by the proposed model have the potentials for further prognostic prediction of postoperative non-small cell lung cancer patients.

Deep learning combined with radiomics may optimize the prediction in differentiating high-grade lung adenocarcinomas in ground glass opacity lesions on CT scans

PURPOSE

Adenocarcinoma (ADC) is the most common histological subtype of lung cancers in non-small cell lung cancer (NSCLC) in which ground glass opacifications (GGOs) found on computed tomography (CT) scans are the most common lesions. However, the presence of a micropapillary or a solid component is identified as an independent predictor of prognosis, suggesting a more extensive resection. The purpose of our study is to explore imaging phenotyping using a method combining radiomics with deep learning (RDL) to predict high-grade patterns within lung ADC.

METHODS

Included in this study were 111 patients differentiated as having GGOs and pathologically confirmed ADC. Four different groups of methods were compared to classify the GGOs for the prediction of the pathological subtypes of high-grade lung ADCs in definitive hematoxylin and eosin stain, including radiomics with gray-level features, radiomics with textural features, deep learning method, and the RDL.

RESULTS

We evaluated the performance of different models on 111 NSCLC patients using 4-fold cross-validation. The proposed RDL has achieved an overall accuracy of 0.913, which significantly outperforms the other methods (p <  0.01, analysis of variation, ANOVA). In addition, we also verified the generality and practical effectiveness of these models on an independent validation dataset of 28 patients. The results showed that our RDL framework with an accuracy of 0.966 significantly surpassed other methods.

CONCLUSION

High-grade lung ADC based on histologic pattern spectrum in GGO lesions might be predicted by the framework combining radiomics with deep learning, which reveals advantage over radiomics alone.

Diagnostic value and imaging features of multi-detector CT in lung adenocarcinoma with ground glass nodule patients

This study investigated the application value and imaging features of multi-detector CT (MDCT) in the treatment of lung adenocarcinoma with ground glass nodules (GGN). The medical data of 168 patients with pulmonary GGN in Shengli Oilfield Central Hospital from January 2013 to June 2015 were analyzed. Patients with microinvasive adenocarcinoma and invasive adenocarcinoma were included in group A (invasive lung adenocarcinoma, n=98), while patients with atypical adenomatous hyperplasia and adenocarcinoma in situ were included in group B (pre-invasive lung adenocarcinoma, n=70). The imaging features of MDCT were compared. ROC curves of the size of nidus and the size of solid component were drawn for the diagnosis of invasive lung adenocarcinoma. Logistic multivariate regression analysis was used to analyze the risk factors that affected invasive lung adenocarcinoma. There were significant differences in nidus, burr, and lobes of the patients between groups A and B. The size of nidus and the size of solid component of the patients in group A were significantly higher than those of the patients in group B. The AUCs of the size of the nidus and the size of the solid component of the invasive lung adenocarcinoma were 0.891 and 0.902, respectively. The AUC of the combined diagnosis was 0.984. Size of the nidus, size of the solid component, nature of the lesion, burr, and lobes were all risk factors for invasive lung adenocarcinoma. In patients with GGN, size of the nidus and size of the solid component can be used as excellent diagnostic parameters for invasive lung adenocarcinoma, and nidus size (≥9.8 mm), size of the solid component (≥0.9 mm), the mixed GGN nature of the nidus, burr and lobes can distinguish invasive lung adenocarcinoma and pre-invasive lesions.