Comprehensive analysis of clinicopathological profiles in adenosquamous carcinoma of the lung

OBJECTIVES

Adenosquamous carcinoma (ASC), an uncommon subtype within non-small cell lung cancer (NSCLC), manifests distinctive traits of aggressiveness, embodying a fusion of both adenocarcinoma (AC) and squamous cell carcinoma (SCC) components. The clinicopathological characteristics of distinct subtypes of ASC remain unclear.

METHODS

This retrospective study included 226 patients diagnosed with lung ASC who consecutively underwent surgical resection at Shanghai Pulmonary Hospital, Tongji University, between January 2015 and March 2021. Data regarding the clinical features and pathological features were collected.

RESULTS

Out of this study cohort, 125 patients exhibited AC-predominant ASC, while 81 had SCC-predominant ASC. No significant differences were observed between the two subgroups in terms of age, gender, smoking history, primary site, and T, N classification. AC-Predominant ASC displayed a higher susceptibility to genetic alterations compared to SCC-Predominant ASC (P=0.02). Additionally, we showed that irrespective of the predominant pathological subtype in ASC, when lymph node metastasis occurred, the lymph node biopsies were more likely to exhibit AC, and a chi-square test confirmed that the primary predominant pathological subtype was not associated with the lymph node metastasis subtype.

CONCLUSIONS

In conclusion, we describe an overview of ASC in the Chinese population, and upon stratifying into predominant pathological subgroups, we observed a higher frequency of driver gene mutations in AC-predominant ASC. We found that the AC component in ASC has a higher propensity for lymph node metastasis. These findings may suggest the predominant role of the AC component within the context of ASC.

Persistent increase and improved survival of stage I lung cancer based on a large-scale real-world sample of 26,226 cases

BACKGROUND

Lung cancer prevails and induces high mortality around the world. This study provided real-world information on the evolution of clinicopathological profiles and survival outcomes of lung cancer, and provided survival information within stage I subtypes.

METHODS

Patients pathologically confirmed with lung cancer between January 2009 and December 2018 were identified with complete clinicopathological information, molecular testing results, and follow-up data. Shifts in clinical characteristics were evaluated using χ2 tests. Overall survival (OS) was calculated through the Kaplan-Meier method.

RESULTS

A total of 26,226 eligible lung cancer patients were included, among whom 62.55% were male and 52.89% were smokers. Non-smokers and elderly patients took increasingly larger proportions in the whole patient population. The proportion of adenocarcinoma increased from 51.63% to 71.80%, while that of squamous carcinoma decreased from 28.43% to 17.60%. Gene mutations including EGFR (52.14%), KRAS (12.14%), and ALK (8.12%) were observed. Female, younger, non-smoking, adenocarcinoma patients and those with mutated EGFR had better survival prognoses. Importantly, this study validated that early detection of early-stage lung cancer patients had contributed to pronounced survival benefits during the decade. Patients with stage I lung cancer, accounted for an increasingly considerable proportion, increasing from 15.28% to 40.25%, coinciding with the surgery rate increasing from 38.14% to 54.25%. Overall, period survival analyses found that 42.69% of patients survived 5 years, and stage I patients had a 5-year OS of 84.20%. Compared with that in 2009-2013, the prognosis of stage I patients in 2014-2018 was dramatically better, with 5-year OS increasing from 73.26% to 87.68%. Regarding the specific survival benefits among stage I patients, the 5-year survival rates were 95.28%, 93.25%, 82.08%, and 74.50% for stage IA1, IA2, IA3, and IB, respectively, far more promising than previous reports.

CONCLUSIONS

Crucial clinical and pathological changes have been observed in the past decade. Notably, the increased incidence of stage I lung cancer coincided with an improved prognosis, indicating actual benefits of early detection and management of lung cancer.

The phosphorylation level of Cofilin-1 is related to the pathological subtypes of gastric cancer

The purpose of the study was to explore the relationship between multiple proteins belonging to the LIMK/Cofilin pathway, including LIMK1, LIMK2, Cofilin-1, and p-Cofilin-1 and clinical features of gastric cancer (GC) patients, including overall survival, TNM stages, and pathological subtypes. The expression of LIMK1, LIMK2, Cofilin-1 and p-Cofilin-1 in the GC tissues and adjacent normal stomach tissues from 141 patients were detected using immunohistochemistry (IHC) staining. Wilcoxon rank-sum test and Spearman rank correlation coefficients were used to measure the relationship between different TNM stages, pathological types, and selected parameters. OS was estimated using the Kaplan-Meier method and survival curves were compared using the log-rank test. Our results showed that, compared to those in the adjacent normal stomach tissues, LIMK1, LIMK2 and Cofilin-1 were up-regulated while p-Cofilin-1 was down-regulated in the GC tissues. LIMK1 level was positively correlated to the TNM stages of GC. According to the published dataset, the expression levels of both LIMK1 and LIMK2 were correlated to the overall survival time of GC patients. The level of Cofilin-1 was significantly different between GCs of different TNM stages. Moreover, most importantly, this is the first study to reveal that the level of Cofilin-1 is higher, and the level of p-Cofilin-1 is lower in the diffuse type of GC compared to that in intestinal type. Taken together, our study demonstrated that multiple factors in LIMK/Cofilin pathway including LIMK1, LIMK2, Cofilin-1, and p-Cofilin-1 were associated with the clinical and pathological features of GC, which is potentially helpful for the diagnosis and treatment of GC.

DeepLN: A Multi-Task AI Tool to Predict the Imaging Characteristics, Malignancy and Pathological Subtypes in CT-Detected Pulmonary Nodules

Objectives

Distinction of malignant pulmonary nodules from the benign ones based on computed tomography (CT) images can be time-consuming but significant in routine clinical management. The advent of artificial intelligence (AI) has provided an opportunity to improve the accuracy of cancer risk prediction.

Methods

A total of 8950 detected pulmonary nodules with complete pathological results were retrospectively enrolled. The different radiological manifestations were identified mainly as various nodules densities and morphological features. Then, these nodules were classified into benign and malignant groups, both of which were subdivided into finer specific pathological types. Here, we proposed a deep convolutional neural network for the assessment of lung nodules named DeepLN to identify the radiological features and predict the pathologic subtypes of pulmonary nodules.

Results

In terms of density, the area under the receiver operating characteristic curves (AUCs) of DeepLN were 0.9707 (95% confidence interval, CI: 0.9645-0.9765), 0.7789 (95%CI: 0.7569-0.7995), and 0.8950 (95%CI: 0.8822-0.9088) for the pure-ground glass opacity (pGGO), mixed-ground glass opacity (mGGO) and solid nodules. As for the morphological features, the AUCs were 0.8347 (95%CI: 0.8193-0.8499) and 0.9074 (95%CI: 0.8834-0.9314) for spiculation and lung cavity respectively. For the identification of malignant nodules, our DeepLN algorithm achieved an AUC of 0.8503 (95%CI: 0.8319-0.8681) in the test set. Pertaining to predicting the pathological subtypes in the test set, the multi-task AUCs were 0.8841 (95%CI: 0.8567-0.9083) for benign tumors, 0.8265 (95%CI: 0.8004-0.8499) for inflammation, and 0.8022 (95%CI: 0.7616-0.8445) for other benign ones, while AUCs were 0.8675 (95%CI: 0.8525-0.8813) for lung adenocarcinoma (LUAD), 0.8792 (95%CI: 0.8640-0.8950) for squamous cell carcinoma (LUSC), 0.7404 (95%CI: 0.7031-0.7782) for other malignant ones respectively in the malignant group.

Conclusions

The DeepLN based on deep learning algorithm represented a competitive performance to predict the imaging characteristics, malignancy and pathologic subtypes on the basis of non-invasive CT images, and thus had great possibility to be utilized in the routine clinical workflow.

The association between the inflammatory potential of diet and the risk of histopathological and molecular subtypes of breast cancer in northwestern Iran: Results from the Breast Cancer Risk and Lifestyle study

BACKGROUND

This study explored the association between diet-associated inflammation and the risk of different molecular subtypes of breast cancer (BrCA) in a large, population-based case-control study conducted in northwestern Iran.

METHODS

The study consisted of 1007 women with histopathologically confirmed BrCA and 1004 controls admitted to hospitals in Tabriz, northwestern Iran, for nonneoplastic conditions. Dietary Inflammatory Index scores and energy-adjusted Dietary Inflammatory Index (E-DII) scores, with and without supplements, were computed on the basis of dietary intake collected using a validated 136-item food frequency questionnaire.

RESULTS

Women with the highest E-DII scores (quartile 4) versus those with the lowest E-DII scores (quartile 1) showed a significantly increased BrCA risk (odds ratio for quartile 4 vs quartile 1 [OR_Q4vsQ1 ], 1.87; 95% confidence interval [CI], 1.42-2.47), particularly for lobular carcinoma (OR_Q4vsQ1 , 3.07; 95% CI, 1.34-7.02). Findings were similar for premenopausal women diagnosed with luminal A BrCA (OR_Q4vsQ1 , 2.71; 95% CI, 1.74-4.22) or luminal B BrCA (OR_Q4vsQ1 , 2.86; 95% CI, 1.39-5.89). Women consuming the most proinflammatory diets were 3 times more likely to have triple-negative BrCA (OR_Q4vsQ1 , 3.00; 95% CI, 1.002-8.96) while compared to luminal A BrCA. The BrCA risk for women consuming diets in the highest half of E-DII scores (E-DII > 0) was 59% greater than the risk for those in the lowest half (95% CI, 1.29-1.97). Also, higher E-DII scores that took into account supplements were associated with larger tumor sizes (T3 > 5 cm; P < .05).

CONCLUSIONS

A proinflammatory diet, as indicated by higher E-DII scores, appears to increase the risk of BrCA in Iranian women. Large increases in risk were seen in invasive molecular subtypes of BrCA. Anti-inflammatory diets are suggested to prevent the risk of overall BrCA and more aggressive forms of BrCA in particular.

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.

The prognosis of prechemotherapy blastemal predominant histology subtype in Wilms tumor: A retrospective study in China

PURPOSE

This study aimed to retrospectively analyze survival outcomes for Chinese patients with prechemotherapy blastemal predominant histology type Wilms tumors (WTs).

METHODS

We collected and analyzed clinical data concerning patients aged <15 years with favorable histology (FH) WTs treated at the Sun Yat-Sen University Cancer Center from December 2005 to May 2016, based on the Children's Oncology Group protocol. Pathological specimens were collected through biopsy or surgical resection before initiation of chemotherapy. We analyzed survival outcomes involving different prechemotherapy histology subtypes.

RESULTS

We enrolled 97 patients with FH WTs (median follow-up, 71.5 months; range, 22.2-170.7). The total recurrence rate was 17.5%, and the subtype recurrence rates were as follows: blastemal predominant (45.5%), mixed (7.5%), epithelial (14.3%), and mesenchymal (9.5%) (P = .010). Five-year event-free survival (EFS) and overall survival (OS) rates were 84.9% and 81.4%, respectively. Respective 5-year EFS and OS rates for subtypes were as follows: blastemal predominant (54.5% and 68.2%), mixed (90.0% and 88.9%), epithelial (85.7% and 85.1%), and mesenchymal (90.5% and 94.7%). Multivariate survival analyses showed that the blastemal predominant subtype was an independent prognostic factor of EFS (P = .001) and OS (P = .017).

CONCLUSIONS

Our findings showed that prechemotherapy blastemal predominant WTs had higher recurrence and lower EFS and OS rates. Our findings suggested that, albeit with some deficiencies, blastemal predominant histology WT-diagnosed prechemotherapy may have prognostic relevance. Further research into other potential confounding variables are required to determine whether such patients warrant altered risk-stratified therapy.

Characterization of breast lesions using diffusion kurtosis model-based imaging: An initial experience

OBJECTIVE

To investigate the characterization of breast lesions using diffusion kurtosis model-based imaging.

METHODS

This prospective study included 120 consecutive patients underwent preoperative DCE-MRI examinations and multi-b-value diffusion-weighted imaging (DWI). Among them, 88 malignant lesions and 44 benign lesions were detected, 56 normal fibroglandular breast tissue were selected as normal control. Conventional apparent diffusion coefficient (ADC), DKI-based parameters mean kurtosis (MK) and mean diffusivity (MD) were analyzed by lesions types and histological subtypes using one-way ANOVA and receiver operating characteristic (ROC) curve.

RESULTS

(1) The malignant group showed significantly lower ADC and MD (1.07±0.32×10-3 mm2/s and 1.30±0.40×10-3 mm2/s, respectively) and higher MK (0.87±0.18) than those in the benign group (1.29±0.26×10-3 mm2/s, 1.62±0.31×10-3 mm2/s and 0.67±0.18) and control group (1.67±0.33×10-3 mm2/s, 2.24±0.28×10-3 mm2/s and 0.52±0.08) with all P < 0.001. (2) Areas under ROC curve (AUC) for diagnosing malignant lesions were 0.936 for MD, 0.911 for MK and 0.897 for ADC, respectively. AUC for MD was significantly higher than that for ADC (P = 0.015). The optimal cut-off value, sensitivity, specificity, positive predictive value, negative predictive value and accuracy were as follow: ADC = 1.18×10-3mm2/s, 78.3%, 93.2%, 81.2%, 81.6%, 81.4%; MD = 1.48×10-3mm2/s, 82.2%, 98.3%, 84.4%, 87.8%, 86.2%; MK = 0.78, 91.5%, 85.3%, 89.0%, 85.8%, 87.2%. (3) Invasive ductal carcinoma (IDC), ductal carcinoma in situ (DCIS) and mucinous adenocarcinoma also showed significant differences among ADC, MD and MK (with P < 0.05).

CONCLUSIONS

MR-DKI parameters enable to improve breast lesion characterization and have diagnostic potential applying to different pathological subtypes of breast cancers.