Tumor cell proliferation (Ki-67) expression and its prognostic significance in histological subtypes of lung adenocarcinoma

Role of the Clinical Features and MRI Parameters on Ki-67 Expression in Hepatocellular Carcinoma Patients: Development of a Predictive Nomogram

PURPOSE

To develop a nomogram using clinical features and the MRI parameters for preoperatively predicting the expression of Ki-67 in patients with hepatocellular carcinoma (HCC).

METHODS

One hundred and forty patients (training cohorts: n = 108; validation cohorts: n = 32) with confirmed HCC were investigated. Mann-Whitney U test, independent sample t-test, and chi-squared test were used to analyze the continuous and categorical variables. Univariate and multivariate logistic regression analyses were performed to examine the clinical variables and parameters from MRI associated with Ki-67 expression. As a result, a nomogram was developed based on these associations in patients with HCC. The performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUC) and calibration curves.

RESULTS

In the training set, multivariable logistic regression analysis revealed that lens culinaris agglutinin-reactive fraction of alpha-fetoprotein (AFP-L3) levels, protein induced by vitamin K absence or antagonist-II (PIVKA-II) levels, and tumor shape were independent predictors for Ki-67 expression (p < 0.05). These three variables and the apparent diffusion coefficient (ADC) value were used to establish a nomogram, while the ADC value was found to be a marginal significant predictor. The model demonstrated a strong ability to discriminate Ki-67 expression in both the training and validation cohorts (AUC = 0.862, 0.877).

CONCLUSION

A non-invasive preoperative prediction method, which incorporates MRI variables and clinical features was developed, and showed effectiveness in evaluating Ki-67 expression in HCC patients.

LncRNA CARD8-AS1 suppresses lung adenocarcinoma progression by enhancing TRIM25-mediated ubiquitination of TXNRD1

Long non-coding RNAs (lncRNAs) play crucial roles in the tumorigenesis and progression of lung adenocarcinoma (LUAD). However, little was known about the role of lncRNAs in high-risk LUAD subtypes: micropapillary-predominant adenocarcinoma (MPA) and solid-predominant adenocarcinoma (SPA). In this study, we conducted a systematic screening of differentially expressed lncRNAs using RNA sequencing in 10 paired MPA/SPA tumor tissues and adjacent normal tissues. Consequently, 110 significantly up-regulated lncRNAs and 288 aberrantly down-regulated lncRNAs were identified (|Log2 Foldchange| ≥ 1 and corrected P < 0.05). The top 10 lncRNAs were further analyzed in 89 MPA/SPA tumor tissues and 59 normal tissues from The Cancer Genome Atlas database. Among them, CARD8-AS1 showed the most significant differential expression, and decreased expression of CARD8-AS1 was significantly associated with a poorer prognosis. Functionally, CARD8-AS1 overexpression remarkably suppressed the proliferation, migration and invasion of LUAD cells both in vitro and in vivo. Conversely, inhibition of CARD8-AS1 yielded opposite effects. Mechanistically, CARD8-AS1 acted as a scaffold to facilitate the interaction between TXNRD1 and E3 ubiquitin ligase TRIM25, thereby promoting the degradation of TXNRD1 through the ubiquitin-proteasome pathway. Additionally, TXNRD1 was found to promote LUAD cell proliferation, migration and invasion in vitro. Furthermore, the suppressed progression of LUAD cells resulting from CARD8-AS1 overexpression could be significantly reversed by simultaneous overexpression of TXNRD1. In conclusion, this study revealed that the lncRNA CARD8-AS1 played a suppressive role in the progression of LUAD by enhancing TRIM25-mediated ubiquitination of TXNRD1. The CARD8-AS1-TRIM25-TXNRD1 axis may represent a promising therapeutic target for LUAD.

A novel nomogram model based on Ki-67 characteristic expression to predict prognosis in head and neck squamous cell carcinoma

Objectives

This study aimed to examine Ki-67's correlation with clinicopathological characteristics of head and neck squamous cell carcinoma (HNSCC), evaluate its prognostic significance, and develop a Ki-67 integrated prognostic model.

Methods

The retrospective study included 764 HNSCC patients hospitalized from 2012 to 2022. Data were sourced from medical records and immunohistochemical analysis of surgical specimens.

Results

Ki-67 expression was significantly associated with sex, pathological grade, clinical stage, and metastasis, but not with age or recurrence. Higher Ki-67 levels were linked to poorer prognosis, as indicated by Kaplan-Meier survival analysis. Utilizing a Cox proportional hazards model, four prognostic factors were identified: age, recurrence, metastasis, and Ki-67 expression. These factors were used to construct a prognostic model and a nomogram. The model's predictive accuracy was confirmed by a high concordance index and a reliable calibration curve.

Conclusion

Ki-67 expression in HNSCC patients correlates with several clinicopathological features and serves as a negative prognostic marker. A prognostic model incorporating Ki-67 was successfully developed, offering a new tool for patient prognosis assessment in HNSCC.

Exploring a multiparameter MRI-based radiomics approach to predict tumor proliferation status of serous ovarian carcinoma

OBJECTIVES

To develop a multiparameter magnetic resonance imaging (MRI)-based radiomics approach that can accurately predict the tumor cell proliferation status of serous ovarian carcinoma (SOC).

MATERIALS AND METHODS

A total of 134 patients with SOC who met the inclusion and exclusion criteria were retrospectively screened from institution A, spanning from January 2016 to March 2022. Additionally, an external validation set comprising 42 SOC patients from institution B was also included. The region of interest was determined by drawing each ovarian mass boundaries manually slice-by-slice on T2-weighted imaging fat-suppressed fast spin-echo (T2FSE) and T1 with contrast enhancement (T1CE) images using ITK-SNAP software. The handcrafted radiomic features were extracted, and then were selected using variance threshold algorithm, SelectKBest algorithm, and least absolute shrinkage and selection operator. The optimal radiomic scores and the clinical/radiological independent predictors were integrated as a combined model.

RESULTS

Compared with the area under the curve (AUC) values of each radiomic signature of T2FSE and T1CE, respectively, the AUC value of the radiomic signature (T1CE-T2FSE) was the highest in the training set (0.999 vs. 0.965 and 0.860). The homogeneous solid component of the ovarian mass was considered the only independent predictor of tumor cell proliferation status among the clinical/radiological variables. The AUC of the radiomic-radiological model was 0.999.

CONCLUSIONS

The radiomic-radiological model combining radiomic scores and the homogeneous solid component of the ovarian mass can accurately predict tumor cell proliferation status of SOC which has high repeatability and may enable more targeted and effective treatment strategies.

CRITICAL RELEVANCE STATEMENT

The proposed radiomic-radiological model combining radiomic scores and the homogeneous solid component of the ovarian mass can predict tumor cell proliferation status of SOC which has high repeatability and may guide individualized treatment programs.

KEY POINTS

• The radiomic-radiological nomogram may guide individualized treatment programs of SOC. • This radiomic-radiological nomogram showed a favorable prediction ability. • Homogeneous slightly higher signal intensity on T2FSE is vital for Ki-67.

NRIP1 regulates cell proliferation in lung adenocarcinoma cells

Nuclear receptor interacting protein 1 (NRIP1) is a transcription cofactor that regulates the activity of nuclear receptors and transcription factors. Functional expression of NRIP1 has been identified in multiple cancers. However, the expression and function of NRIP1 in lung adenocarcinoma have remained unclear. Thus, we aimed to clarify the NRIP1 expression and its functions in lung adenocarcinoma cells. NRIP1 and Ki-67 were immunostained in the tissue microarray section consisting of 64 lung adenocarcinoma cases, and the association of NRIP1 immunoreactivity with clinical phenotypes was examined. Survival analysis was performed in lung adenocarcinoma data from The Cancer Genome Atlas (TCGA). Human A549 lung adenocarcinoma cell line with an NRIP1-silencing technique was used in vitro study. Forty-three of 64 cases were immunostained with NRIP1. Ki-67-positive cases were more frequent in NRIP1-positive cases as opposed to NRIP1-negative cases. Higher NRIP1 mRNA expression was associated with poor prognosis in the TCGA lung adenocarcinoma data. NRIP1 was mainly located in the nucleus of A549 cells. NRIP1 silencing significantly reduced the number of living cells, suppressed cell proliferation, and induced apoptosis. These results suggest that NRIP1 participates in the progression and development of lung adenocarcinoma. Targeting NRIP1 may be a possible therapeutic strategy against lung adenocarcinoma.

CT-based radiomics for predicting Ki-67 expression in lung cancer: a systematic review and meta-analysis

Background

Radiomics, an emerging field, presents a promising avenue for the accurate prediction of biomarkers in different solid cancers. Lung cancer remains a significant global health challenge, contributing substantially to cancer-related mortality. Accurate assessment of Ki-67, a marker reflecting cellular proliferation, is crucial for evaluating tumor aggressiveness and treatment responsiveness, particularly in non-small cell lung cancer (NSCLC).

Methods

A systematic review and meta-analysis conducted following the preferred reporting items for systematic review and meta-analysis of diagnostic test accuracy studies (PRISMA-DTA) guidelines. Two authors independently conducted a literature search until September 23, 2023, in PubMed, Embase, and Web of Science. The focus was on identifying radiomics studies that predict Ki-67 expression in lung cancer. We evaluated quality using both Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and the Radiomics Quality Score (RQS) tools. For statistical analysis in the meta-analysis, we used STATA 14.2 to assess sensitivity, specificity, heterogeneity, and diagnostic values.

Results

Ten retrospective studies were pooled in the meta-analysis. The findings demonstrated that the use of computed tomography (CT) scan-based radiomics for predicting Ki-67 expression in lung cancer exhibited encouraging diagnostic performance. Pooled sensitivity, specificity, and area under the curve (AUC) in training cohorts were 0.78, 0.81, and 0.85, respectively. In validation cohorts, these values were 0.78, 0.70, and 0.81. Quality assessment using QUADAS-2 and RQS indicated generally acceptable study quality. Heterogeneity in training cohorts, attributed to factors like contrast-enhanced CT scans and specific Ki-67 thresholds, was observed. Notably, publication bias was detected in the training cohort, indicating that positive results are more likely to be published than non-significant or negative results. Thus, journals are encouraged to publish negative results as well.

Conclusion

In summary, CT-based radiomics exhibit promise in predicting Ki-67 expression in lung cancer. While the results suggest potential clinical utility, additional research efforts should concentrate on enhancing diagnostic accuracy. This could pave the way for the integration of radiomics methods as a less invasive alternative to current procedures like biopsy and surgery in the assessment of Ki-67 expression.

Spatial transcriptomics reveals heterogeneity of histological subtypes between lepidic and acinar lung adenocarcinoma

BACKGROUND

Patients who possess various histological subtypes of early-stage lung adenocarcinoma (LUAD) have considerably diverse prognoses. The simultaneous existence of several histological subtypes reduces the clinical accuracy of the diagnosis and prognosis of early-stage LUAD due to intratumour intricacy.

METHODS

We included 11 postoperative LUAD patients pathologically confirmed to be stage IA. Single-cell RNA sequencing (scRNA-seq) was carried out on matched tumour and normal tissue. Three formalin-fixed and paraffin-embedded cases were randomly selected for 10× Genomics Visium analysis, one of which was analysed by digital spatial profiler (DSP).

RESULTS

Using DSP and 10× Genomics Visium analysis, signature gene profiles for lepidic and acinar histological subtypes were acquired. The percentage of histological subtypes predicted for the patients from samples of 11 LUAD fresh tissues by scRNA-seq showed a degree of concordance with the clinicopathologic findings assessed by visual examination. DSP proteomics and 10× Genomics Visium transcriptomics analyses revealed that a negative correlation (Spearman correlation analysis: r = -.886; p = .033) between the expression levels of CD8 and the expression trend of programmed cell death 1(PD-L1) on tumour endothelial cells. The percentage of CD8+ T cells in the acinar region was lower than in the lepidic region.

CONCLUSIONS

These findings illustrate that assessing patient histological subtypes at the single-cell level is feasible. Additionally, tumour endothelial cells that express PD-L1 in stage IA LUAD suppress immune-responsive CD8+ T cells.

A gadoxetic acid-enhanced MRI-based model using LI-RADS v2018 features for preoperatively predicting Ki-67 expression in hepatocellular carcinoma

PURPOSE

To construct a gadoxetic acid-enhanced MRI (EOB-MRI) -based multivariable model to predict Ki-67 expression levels in hepatocellular carcinoma (HCC) using LI-RADS v2018 imaging features.

METHODS

A total of 121 patients with HCC who underwent EOB-MRI were enrolled in this study. The patients were divided into three groups according to Ki-67 cut-offs: Ki-67 ≥ 20% (n = 86) vs. Ki-67 < 20% (n = 35); Ki-67 ≥ 30% (n = 73) vs. Ki-67 < 30% (n = 48); Ki-67 ≥ 50% (n = 45) vs. Ki-67 < 50% (n = 76). MRI features were analyzed to be associated with high Ki-67 expression using logistic regression to construct multivariable models. The performance characteristic of the models for the prediction of high Ki-67 expression was assessed using receiver operating characteristic curves.

RESULTS

The presence of mosaic architecture (p = 0.045), the presence of infiltrative appearance (p = 0.039), and the absence of targetoid hepatobiliary phase (HBP, p = 0.035) were independent differential factors for the prediction of high Ki-67 status (≥ 50% vs. < 50%) in HCC patients, while no features could predict high Ki-67 status with thresholds of 20% (≥ 20% vs. < 20%) and 30% (≥ 30% vs. < 30%) (p > 0.05). Four models were constructed including model A (mosaic architecture and infiltrated appearance), model B (mosaic architecture and targetoid HBP), model C (infiltrated appearance and targetoid HBP), and model D (mosaic architecture, infiltrated appearance and targetoid HBP). The model D yielded better diagnostic performance than the model C (0.776 vs. 0.669, p = 0.002), but a comparable AUC than model A (0.776 vs. 0.781, p = 0.855) and model B (0.776 vs. 0.746, p = 0.076).

CONCLUSIONS

Mosaic architecture, infiltrated appearance and targetoid HBP were sensitive imaging features for predicting Ki-67 index ≥ 50% and EOB-MRI model based on LI-RADS v2018 features may be an effective imaging approach for the risk stratification of patients with HCC before surgery.

Assessment of Ki-67 proliferation index in prognosis prediction in patients with nonmetastatic clear cell renal cell carcinoma and tumor thrombus

PURPOSE

To determine the optimal cut-off value of Ki-67 for predicting the survival of patients with clear cell renal cell carcinoma (ccRCC) and tumor thrombus and to explore the correlation between Ki-67 expression and pathological features.

PATIENTS AND METHODS

We retrospectively analyzed Ki-67 immunohistochemical staining of ccRCC and tumor thrombus resected from February 2006 to February 2022. The survival rate was evaluated using the Kaplan-Meier method. The optimal cut-off value of the Ki-67 expression for predicting survival was determined by the minimum P-value method. Clinicopathological data were compared based on Ki-67 status (low versus high expression). Univariate and multivariate Cox regression analysis was used to explore independent predictors.

RESULTS

A total of 202 patients (median age, 58 years [IQR, 52-65 years], 147 men) with ccRCC and tumor thrombus were included in the study. The optimal cut-off value of Ki-67 for predicting survival was 30%. 159 (78.7%) and 43 (21.3%) patients were included in the low-expression and high-expression groups. Patients with Ki-67 high expression had significantly worse recurrence-free survival (P < 0.001) and cancer-specific survival (P < 0.001). Ki-67 high expression was associated with adverse pathological features, including tumor necrosis, ISUP nuclear grade, sarcomatoid differentiation, perirenal fat invasion, renal pelvis invasion, and inferior vena cava wall invasion (all P < 0.050). Ki-67 expression ≥ 30% (P = 0.016), tumor side (P = 0.003), diabetes (P = 0.040), blood loss (P = 0.016), inferior vena cava wall invasion (P = 0.016), and sarcomatoid differentiation (P = 0.014) were independent predictors of cancer-specific survival.

CONCLUSION

The optimal cut-off level of Ki-67 in predicting the prognosis of ccRCC and tumor thrombus was 30%. The high expression of Ki-67 was associated with the aggressive pathological phenotype and poor prognosis.

Combined utility of Ki-67 index and tumor grade to stratify patients with pancreatic ductal adenocarcinoma who underwent upfront surgery

OBJECTIVE

To investigate the prognostic prediction of a new indicator, combined by tumor grade and Ki-67, in patients with resected pancreatic ductal adenocarcinoma (PDAC).

METHODS

Data were retrospectively collected from consecutive patients who underwent primary resection of pancreas from December 2012 to December 2017. Tumor grade and Ki-67 were reviewed from routine pathological reports. G-Ki67 was classified as three categories as I (G1/2 and Ki-67 < 40%), II (G1/2 and Ki-67 ≥ 40%), and III(G3/4 and all Ki-67).

RESULTS

Cox regression analyses revealed that tumor stage (II vs. I: hazard ratio (HR), 3.781; 95% confidence index (CI), 2.844-5.025; P < 0.001; III vs. I: HR, 7.476; 95% CI, 5.481-10.20; P < 0.001) and G-Ki67 (II vs. I: HR, 1.299; 95% CI, 1.038-1.624; P = 0.022; III vs. I: HR, 1.942; 95% CI, 1.477-2.554; P < 0.001) were independent prognostic factors in the developing cohort. The result was rectified in the validation cohort. In subgroups analysis, G-Ki67 (II vs. I: HR, 1.866 ; 95% CI, 1.045-3.334; P = 0.035; III vs. I: HR, 2.333 ; 95% CI, 1.156-4.705; P = 0.018) also had a high differentiation for survival prediction.

CONCLUSION

Our findings indicate that three-categories of G-Ki67 in resectable PDAC according to the routine pathological descriptions provided additional prognostic information complementary to the TNM staging system.

A semi-automated microscopic image analysis method for scoring Ki-67 nuclear immunostaining

Nuclear proliferation marker MIB-1 (Ki-67) immunohistochemistry (IHC) is used to examine tumor cell proliferation. However, the diagnostic or prognostic value of the Ki-67 nuclear staining intensity and location, defined as nuclear gradient (NG), has not been assessed. This study examined the potential association between Ki-67 NG and cell cycle phases and its effect on the prognosis of pulmonary typical carcinoid (PTC) tumors. We propose a method for classifying the NG of Ki-67 during the cell cycle and compare the results between PTC, pulmonary adenocarcinoma (PAD), and breast ductal carcinoma (BDC). A literature review and objective analysis of IHC-stained paraffin sections were used to determine the Ki-67 labeling index and composed a stratification of the NG into NG1, NG2, and NG3/4 categories. A semi-automated image analysis protocol was established to determine the Ki-67 NG in PTC, PAD, and BDC. High intraobserver consistency and moderate interobserver agreement were achieved in the determination of Ki-67 NG in tumor specimens. NG1 and NG2 were lower in PTC than in PAD and BDC. Cox multivariate analysis of PTC after adjusting for age and number of metastatic lymph nodes showed that Ki-67 NG1 and NG2 significantly predicted clinical outcomes. The semi-automated method for quantification of Ki-67 nuclear immunostaining proposed in this study could become a valuable diagnostic and prognostic tool in PTC.

Deep Learning to Predict the Cell Proliferation and Prognosis of Non-Small Cell Lung Cancer Based on FDG-PET/CT Images

(1) Background: Cell proliferation (Ki-67) has important clinical value in the treatment and prognosis of non-small cell lung cancer (NSCLC). However, current detection methods for Ki-67 are invasive and can lead to incorrect results. This study aimed to explore a deep learning classification model for the prediction of Ki-67 and the prognosis of NSCLC based on FDG-PET/CT images. (2) Methods: The FDG-PET/CT scan results of 159 patients with NSCLC confirmed via pathology were analyzed retrospectively, and the prediction models for the Ki-67 expression level based on PET images, CT images and PET/CT combined images were constructed using Densenet201. Based on a Ki-67 high expression score (HES) obtained from the prediction model, the survival rate of patients with NSCLC was analyzed using Kaplan-Meier and univariate Cox regression. (3) Results: The statistical analysis showed that Ki-67 expression was significantly correlated with clinical features of NSCLC, including age, gender, differentiation state and histopathological type. After a comparison of the three models (i.e., the PET model, the CT model, and the FDG-PET/CT combined model), the combined model was found to have the greatest advantage in Ki-67 prediction in terms of AUC (0.891), accuracy (0.822), precision (0.776) and specificity (0.902). Meanwhile, our results indicated that HES was a risk factor for prognosis and could be used for the survival prediction of NSCLC patients. (4) Conclusions: The deep-learning-based FDG-PET/CT radiomics classifier provided a novel non-invasive strategy with which to evaluate the malignancy and prognosis of NSCLC.

CT radiomics model for predicting the Ki-67 proliferation index of pure-solid non-small cell lung cancer: a multicenter study

Purpose

This study aimed to explore the efficacy of the computed tomography (CT) radiomics model for predicting the Ki-67 proliferation index (PI) of pure-solid non-small cell lung cancer (NSCLC).

Materials and methods

This retrospective study included pure-solid NSCLC patients from five centers. The radiomics features were extracted from thin-slice, non-enhanced CT images of the chest. The minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) were used to reduce and select radiomics features. Logistic regression analysis was employed to build predictive models to determine Ki-67-high and Ki-67-low expression levels. Three prediction models were established: the clinical model, the radiomics model, and the nomogram model combining the radiomics signature and clinical features. The prediction efficiency of different models was evaluated using the area under the curve (AUC).

Results

A total of 211 NSCLC patients with pure-solid nodules or masses were included in the study (N=117 for the training cohort, N=49 for the internal validation cohort, and N=45 for the external validation cohort). The AUC values for the clinical models in the training, internal validation, and external validation cohorts were 0.73 (95% CI: 0.64-0.82), 0.75 (95% CI:0.62-0.89), and 0.72 (95% CI: 0.57-0.86), respectively. The radiomics models showed good predictive ability in diagnosing Ki-67 expression levels in the training cohort (AUC, 0.81 [95% CI: 0.73-0.89]), internal validation cohort (AUC, 0.81 [95% CI: 0.69-0.93]) and external validation cohort (AUC, 0.78 [95% CI: 0.64-0.91]). Compared to the clinical and radiomics models, the nomogram combining both radiomics signatures and clinical features had relatively better diagnostic performance in all three cohorts, with the AUC of 0.83 (95% CI: 0.76-0.90), 0.83 (95% CI: 0.71-0.94), and 0.81 (95% CI: 0.68-0.93), respectively.

Conclusion

The nomogram combining the radiomics signature and clinical features may be a potential non-invasive method for predicting Ki-67 expression levels in patients with pure-solid NSCLC.

Clinical characteristics and establishment of a 2-year-OS predictive model of EGFR mutation-positive patients with pleural invasion of lung adenocarcinoma

To investigate the differences between lung adenocarcinoma with the pleural invasion that has EGFR (epidermal growth factor receptor) 19-del or 21L858R mutations in terms of clinical characteristics and outcomes. EGFR mutation-positive patients with pleural metastasis of lung adenocarcinoma diagnosed in the Department of Respiratory Medicine of Yuhuangding Hospital of Yantai City, Shandong Province, from January 2014 to January 2022 were selected. The clinical data of the patients were collected to retrospectively analyze whether the clinical characteristics and prognosis of patients with 19-del or 21L858R mutation subtype were different and analyze the impact of clinical characteristics on the prognosis of patients. The difference in clinical characteristics between the 2 groups was analyzed by SPSS, P < .05. There was statistical significance. Univariate and multivariate regression analysis was performed with R soft. To establish a 2-year overall survival predictive model for patients with EGFR gene 19-del and 21L858R mutations in patients with pleural invasion of lung adenomas and to provide predictive model maps. Receiver operating characteristic curve, calibration curve, and decision curve analysis were used to evaluate the value of the prediction model in this study. Of the 74 patients included, the 19-del mutation group had a higher incidence of pleural thickening (P = .023) and a lower Ki-67 level (P = .035). There was no difference in 2-year overall survival and progression-free survival between the 2 mutations. There were differences in pleural thickening and Ki-67 index between the 2 groups, but no differences in disease outcome between the 2 groups. The nomogram model established based on gender, treatment regimen, CEA, lymph node metastasis, and pleural changes is accurate and feasible.

The effectiveness of blood-activating and stasis-transforming traditional Chinese medicines (BAST) in lung cancer progression-a comprehensive review

ETHNOPHARMACOLOGICAL RELEVANCE

Blood-activating and stasis-transforming traditional Chinese medicines (BAST) are a class of herbs that have the effect of dilating blood vessels and dispersing stagnation. Modern pharmaceutical research has demonstrated that they are capable of improving hemodynamics and micro-flow, resist thrombosis and promote blood flow. BAST contain numerous active ingredients, which can theoretically regulate multiple targets at the same time and have a wide range of pharmacological effects in the treatment of diseases including human cancers. Clinically, BAST have minimal side effects and can be used in combination with Western medicine to improve patients' quality of life, lessen adverse effects and minimize the risk of recurrence and metastasis of cancers.

AIM OF THE REVIEW

We aimed to summarize the research progression of BAST on lung cancer in the past five years and present a prospect for the future. Particularly, this review further analyzes the effects and molecular mechanisms that BAST inhibit the invasion and metastasis of lung cancer.

MATERIALS AND METHODS

Relevant studies about BSAT were collected from PubMed and Web of science.

RESULTS

Lung cancer is one of the malignant tumors with the highest mortality rate. Most patients with lung cancer are diagnosed at an advanced stage and are highly susceptible to metastasis. Recent studies have shown that BAST, a class of traditional Chinese medicine (TCM) with the function of opening veins and dispersing blood stasis, significantly improve hemodynamics and microcirculation, prevent thrombosis and promote blood flow, and thereby inhibiting the invasion and metastasis of lung cancer. In the current review, we analyzed 51 active ingredients extracted from BAST. It was found that BAST and their active ingredients contribute to the prevention of invasion and metastasis of lung cancer through multiple mechanisms, such as regulation of EMT process, specific signaling pathway and metastasis-related genes, tumor blood vessel formation, immune microenvironment and inflammatory response of tumors.

CONCLUSIONS

BSAT and its active ingredients have showed promising anticancer activity and significantly inhibit the invasion and metastasis of lung cancer. A growing number of studies have realized their potential clinical significance in the therapy of lung cancer, which will provide substantial evidences for the development of new TCM for lung cancer therapy.

Aggressive progression to EGFR tyrosine kinase inhibitors in advanced NSCLC patients: concomitant mutations, prognostic indicator and subsequent management

BACKGROUND

EGFR tyrosine kinase (TKIs) are recommend as the first-line treatment for non-small cell lung cancer (NSCLC) patients with EGFR mutation. However, some patients experience aggressive progression with a progression-free survival (PFS) less than 6 months on the first-line EGFR TKI therapy. Therefore, our study is to analyze the potential influencing factors including clinical features, biomarkers, concomitant mutations et al. METHODS: A total of 1073 NSCLC patients with EGFR mutation in a multi-center study from January 2019 to December 2021. The datum pathological and molecular characteristics were collected. The area under the receiver operating characteristic (ROC) curve was used to evaluate the predictive effect of Ki-67 on the first-line TKI. The curve of PFS was conducted by Kaplan-Meier method and tested by bilateral log-rank. Cox regression model was used to predict and evaluate PFS of different variables. Chi-square or Fisher analysis was used for correlation between groups.

RESULTS

55 patients who show aggressive progression (PFS ≤ 6 months) on the first-line TKI therapy were analyzed in this study, while 71 with slow progression (PFS > 6 months). Concomitant mutations including AXIN2, P2CG and RAD51C mutations occurred only in the aggressively progressive group (P = 0.029). Correlation between Ki-67 index and the aggressive progression of the first-line TKI therapy was significant statistically different (P < 0.05). In the second-line therapy, the PFS of chemotherapy in combination with other treatments was better than single TKIs in the first ten months.

CONCLUSION

NSCLC harbored EGFR and concomitant mutations (such as AXIN2, PLCG2 and RAD51C), and/or Ki-67 high expression may indicate the aggressive progression to the first-line EGFR-TKI.

Rapid intraoperative Ki-67 immunohistochemistry for lung cancer using non-contact alternating current electric field mixing

OBJECTIVES

Locoregional recurrence of non-small cell lung cancer (NSCLC) occurs even among patients with stage I disease, as a result of tumor proliferative activity. The aim of this study was to evaluate the clinical reliability of a new rapid immunohistochemistry (IHC) technique for assessing malignant potential through detection of tumoral Ki-67 expression.

MATERIALS AND METHODS

The rapid IHC method uses non-contact alternating current (AC) mixing to achieve more rapid/stable staining within 20 min during surgery. First, to investigate the association between clinical outcomes and tumoral Ki-67 labeling with rapid IHC, 21 pairs of surgical patients treated between 2012 and 2020 for pStage IA1-3 NSCLC with/without recurrence were retrospectively reviewed. Second, 40 frozen section (FS) samples in patients with NSCLC for whom radical surgery was planned between April 2021 and February 2022 were deemed eligible for comparison of the clinical performance of conventional IHC and intraoperative rapid Ki-67 IHC with FS.

RESULTS

Detection of tumoral Ki-67 expression using rapid IHC with formalin-fixed, paraffin-embedded (FFPE) blocks was significantly associated with clinical outcomes in R0 pStage IA NSCLC surgical patients, including overall and recurrence-free survival (P = 0.0043 and P < 0.0001, respectively). Levels of Ki-67 expression among resectable NSCLC patients detected using rapid IHC with FS significantly correlated with those detected using conventional FFPE-IHC (p < 0.001). An intraoperative cut-off of > 7.5 % tumor cell Ki-67 positivity accurately predicted pathological stage more advanced than IA3 [P = 0.0185, Odds ratio = 20.477, 95 % confidence interval (CI): 1.660-252.55].

CONCLUSION

Rapid Ki-67 IHC with AC mixing could potentially serve as a clinical tool for intraoperative determination of tumor malignancy status. The present study suggests that segmentectomy for early small NSCLCs is oncologically safe and a reasonable alternative to lobectomy, but only when there is adequate intraoperative selection for primary tumors with low-grade malignancy, which could be verified using intraoperative rapid Ki-67 IHC with FS.

Pathological components and CT imaging analysis of the area adjacent pleura within the pure ground-glass nodules with pleural deformation in invasive lung adenocarcinoma

Background

Pleural deformation is associated with the invasiveness of lung adenocarcinoma(LAC). Our study focused on the pathological components of the area adjacent pleura in pulmonary pure ground-glass nodules(pGGNs) with pleural deformations(P-pGGNs) confirmed to be invasive LAC without visceral pleural invasion (VPI) pathologically.

Methods

Computed tomography(CT) imaging features of nodules and pathological components of the area adjacent pleura were analyzed and recorded. Statistical analysis was performed for subgroups of P-pGGNs.

Results

The 81 enrolled patients with 81 P-pGGNs were finally involved in the analysis. None of solid/micropapillary group and none of VPI was observed, 54 alveoli/lepidics and 27 acinar/papillarys were observed. In P-pGGN with acinar/papillary components of the area adjacent pleura, invasive adenocarcinoma (IAC) was more common compared to minimally invasive adenocarcinoma (MIA, 74.07% vs. 25.93%; p < 0.001). The distance in alveoli/lepidic group was significantly larger (1.50 mm vs. 0.00 mm; p < 0.001) and the depth was significantly smaller (2.00 mm vs. 6.00 mm; p < 0.001) than that in acinar/papillary group. The CT attenuation value, maximum diameter and maximum vertical diameter was valuable to distinguish acinar/papillary group form alveoli/lepidic group(p < 0.05). The type d pleural deformation was the common pleural deformation in IAC(p = 0.028).

Conclusions

The pathological components of the area adjacent pleura in P-pGGN without VPI confirmed to be invasive LAC could included alveoli/lepidics and acinar/papillarys. Some CT indicators that can identify the pathological invasive components of the area adjacent pleura in P-pGGNs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10043-2.

Nomogram Based on CT Radiomics Features Combined With Clinical Factors to Predict Ki-67 Expression in Hepatocellular Carcinoma

Objectives

The study developed and validated a radiomics nomogram based on a combination of computed tomography (CT) radiomics signature and clinical factors and explored the ability of radiomics for individualized prediction of Ki-67 expression in hepatocellular carcinoma (HCC).

Methods

First-order, second-order, and high-order radiomics features were extracted from preoperative enhanced CT images of 172 HCC patients, and the radiomics features with predictive value for high Ki-67 expression were extracted to construct the radiomic signature prediction model. Based on the training group, the radiomics nomogram was constructed based on a combination of radiomic signature and clinical factors that showed an independent association with Ki-67 expression. The area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) were used to verify the performance of the nomogram.

Results

Sixteen higher-order radiomic features that were associated with Ki-67 expression were used to construct the radiomics signature (AUC: training group, 0.854; validation group, 0.744). In multivariate logistic regression, alfa-fetoprotein (AFP) and Edmondson grades were identified as independent predictors of Ki-67 expression. Thus, the radiomics signature was combined with AFP and Edmondson grades to construct the radiomics nomogram (AUC: training group, 0.884; validation group, 0.819). The calibration curve and DCA showed good clinical application of the nomogram.

Conclusion

The radiomics nomogram developed in this study based on the high-order features of CT images can accurately predict high Ki-67 expression and provide individualized guidance for the treatment and clinical monitoring of HCC patients.

Study on the Correlation Between CT Features and Vascular Tumor Thrombus Together With Nerve Invasion in Surgically Resected Lung Adenocarcinoma

Background

We aimed to analyze the relationship between pulmonary adenocarcinoma patients with vascular tumor thrombus and nerve invasion and different CT features.

Methods

The preoperative CT scanning data of 86 patients with lung adenocarcinoma who underwent surgical resection in our hospital from January 2020 to January 2022 were analyzed in the form of retrospective analysis. The CT images of all patients were observed, and the relationship between them and vascular tumor thrombus and nerve invasion of lung adenocarcinoma was analyzed. At the same time, the sensitivity, specificity, and accuracy of enhanced CT and plain CT were compared to evaluate the diagnostic efficacy of both.

Results

The results showed that the vascular tumor thrombus of lung adenocarcinoma was mainly related to the solid components and lobulated and calcified tumors in CT images, and the nerve invasion of lung adenocarcinoma was mainly related to the tumors with bronchial inflation sign in CT images (P < 0.05). The sensitivity, specificity, and accuracy of enhanced CT in the diagnosis of vascular tumor thrombus were 78.26%, 96.83%, and 91.86%, respectively, and the sensitivity, specificity, and accuracy in the diagnosis of nerve invasion were 75.00%, 98.72%, and 96.51%, respectively. The sensitivity, specificity, and accuracy of plain CT in the diagnosis of vascular tumor thrombus were 43.48%, 92.06%, and 79.07%, respectively, and the sensitivity, specificity, and accuracy in the diagnosis of nerve invasion were 25.00%, 94.87%, and 88.37%, respectively. The contrast showed that the sensitivity and accuracy of enhanced CT were higher than those of plain CT (P < 0.05), but the difference of specificity was not obvious (P > 0.05).

Conclusions

Solid components and lobulated and calcified tumors in CT signs are closely related to vascular tumor thrombus of lung adenocarcinoma, while patients with bronchial inflation sign are related to nerve invasion.

Predicting Ki-67 labeling index level in early-stage lung adenocarcinomas manifesting as ground-glass opacity nodules using intra-nodular and peri-nodular radiomic features

Objectives

To explore the diagnostic value of radiomics in differentiating between lung adenocarcinomas appearing as ground‐glass opacity nodules (GGO) with high‐ and low Ki‐67 expression levels.

Materials and Methods

From January 2018 to January 2021, patients with pulmonary GGO who received lung resection were evaluated for potential enrollment. The included GGOs were then randomly divided into a training cohort and a validation cohort with a ratio of 7:3. Logistic regression (LR), decision tree (DT), support vector machines (SVM), and adaboost (AB) were applied for radiomic model construction. Area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of the established models.

Results

Seven hundred and sixty‐nine patients with 769 GGOs were included in this study. Two hundred and forty‐five GGOs were confirmed to be of high Ki‐67 labeling index (LI). In the training cohort, gender, age, spiculation sign, pleural indentation sign, bubble sign, and maximum 2D diameter of the nodule were found to be significantly different between high‐ and low Ki‐67 LI groups (p < 0.05), and spiculation sign and maximum 2D diameter of the nodule were further confirmed to be risk factors for Ki‐67 LI. The radiomic model established using SVM exhibited an AUC of 0.731 in the validation cohort, which was higher than that of the clinical‐radiographic model (AUC = 0.675). Moreover, radiomic model combining both intra‐ and peri‐nodular features showed better diagnostic efficacy than using intra‐nodular features alone (AUC = 0.731 and 0.720, respectively).

Conclusions

The established radiomic model exhibited good diagnostic efficacy in differentiating between lung adenocarcinoma GGOs with high and low Ki‐67 LI, which was higher than the clinical‐radiographic model. Peri‐nodular radiomic features showed added benefits to the radiomic model. As a novel noninvasive method, radiomics have the potential to be applied in the preliminary classification of Ki‐67 expression level in lung adenocarcinoma GGOs.

Noninvasive Method for Predicting the Expression of Ki67 and Prognosis in Non-Small-Cell Lung Cancer Patients: Radiomics

Purpose

In this study, we aimed to develop and validate a noninvasive method based on radiomics to evaluate the expression of Ki67 and prognosis of patients with non-small-cell lung cancer (NSCLC). Patients and Methods. A total of 120 patients with NSCLC were enrolled in this retrospective study. All patients were randomly assigned to a training dataset (n = 85) and test dataset (n = 35). According to the preprocessed F-FDG PET/CT image of each patient, a total of 384 radiomics features were extracted from the segmentation of regions of interest (ROIs). The Spearman correlation test and least absolute shrinkage and selection operator (LASSO), after normalization on the features matrix, were applied to reduce the dimensionality of the features. Furthermore, multivariable logistic regression analysis was used to propose a model for predicting Ki67. The survival curve was used to explore the prognostic significance of radiomics features.

Results

A total of 62 Ki67 positive patients and 58 Ki67 negative patients formed the training set and test training dataset and test dataset. Radiomics signatures showed good performance in predicting the expression of Ki67 with AUCs of 0.86 (training dataset) and 0.85 (test dataset). Validation and calibration showed that the radiomics had a strong predictive power in patients with NSCLC survival, which was significantly close to the effect of Ki67 expression on the survival of patients with NSCLC.

Conclusion

Radiomics signatures based on preoperative F-FDG PET/CT could distinguish the expression of Ki67, which also had a strong predictive performance for the survival outcome.

Serum tumor markers level and their predictive values for solid and micropapillary components in lung adenocarcinoma

Background

This study aims to reveal the serum tumor marker (STM) levels in lung adenocarcinoma (LUAD) histological subtypes and evaluate their values in predicting the solid and micropapillary components (SMC).

Methods

We retrospectively analyzed 3100 invasive LUAD patients between January 2017 and December 2020. Associations between preoperative STMs (CEA, CYFRA21‐1, CA199, CA724, NSE, AFP) and LUAD subtypes were evaluated. Multivariate regression analyses were used to determine the independent predictors. Predictive models for SMC were constructed and AUC (area under the curve) was calculated.

Results

CEA and CYFRA21‐1 levels differed across the LUAD histological subtypes, with the SPA (solid‐predominant adenocarcinoma) having the highest level and the LPA (lepidic‐predominant adenocarcinoma) harboring the lowest level (p <0.001). Tumors with SMC also had higher CEA and CYFRA21‐1 levels than those absence of SMC. Gender, tumor size, CEA, Ki‐67, EGFR mutation (solid components only), and tumor differentiation were significantly independently associated with the containing of SMC. Patients were split into two data sets (training set: 2017–2019 and validation set: 2020). The model with gender and tumor size yielded an AUC of 0.723 (training set) and 0.704 (validation set) for the solid component. Combination of CEA, gender, and tumor size led to a significant increase in the predictive accuracy (training set: 0.771, p = 0.009; validation set: 0.747, p = 0.034). The AUC of the model for micropapillary component with only gender and tumor size was 0.699 and 0.711 in the training set and validation set, respectively. Integration of CEA with gender and tumor size significantly improved the predictive performance with an AUC of 0.746 (training set, p = 0.045) and 0.753 (validation set, p <0.001).

Conclusion

Serum CEA and CYFRA21‐1 varied considerably according to LUAD histological subtypes. The combination of serum CEA and other factors showed prominent values in predicting the SMC.

Complete Lymphadenectomy for Clinical Stage I Lepidic Adenocarcinoma of the Lung: Is it justified?

The role of a systematic lymphadenectomy in patients undergoing surgery for clinical stage I lung lepidic adenocarcinoma is still unclear. In the last years, some authors have advocated the possibility to avoid a complete lymph-node dissection in this setting. Results of patients who received systematic hilar-mediastinal nodal dissection for this oncologic condition are here reported. Between 2012 and March 2019, 135 consecutive patients underwent lung resection for clinical stage I lepidic adenocarcinoma, at our institution. Only patients (n=98) undergoing lobectomy or sublobar resection associated with systematic hilar-mediastinal nodal dissection were retrospectively enrolled in the study. Patients' mean age was 67.8±8.7 years (range 37-84). Three were 52 females and 46 males. Resection was lobectomy in 77.6% (n=76) and sublobar in 22.4% (n=22). All the resections were complete (R0). Histology was lepidic predominant adenocarcinoma in 85 cases and minimally invasive adenocarcinoma in 13 cases. At pathologic examination, N0 was confirmed in 78 patients (79.6%), while N+ was found in 20 cases (20.4%), (N1 in 12, 12.2% and N2 in 8, 8.2%). No mortality occurred. Complication rate was 8.2%. At a median follow-up of 45.5 months, recurrence rate was 26.5%. Disease-free 5-year survival was 98.6% for stage I, 75% for stage II and 45% for stage III, p<0.001. A complete nodal dissection can reveal occult nodal metastases in lepidic adenocarcinoma patients and can increase the accuracy of pathologic staging. N1/N2 disease is a negative prognostic factor for this histology. A systematic lymph-node dissection should be considered even in this setting.

Pre-operative Prediction of Ki-67 Expression in Various Histological Subtypes of Lung Adenocarcinoma Based on CT Radiomic Features

Purpose: The aims of this study were to combine CT images with Ki-67 expression to distinguish various subtypes of lung adenocarcinoma and to pre-operatively predict the Ki-67 expression level based on CT radiomic features.

Methods: Data from 215 patients with 237 pathologically proven lung adenocarcinoma lesions who underwent CT and immunohistochemical Ki-67 from January 2019 to April 2021 were retrospectively analyzed. The receiver operating curve (ROC) identified the Ki-67 cut-off value for differentiating subtypes of lung adenocarcinoma. A chi-square test or t-test analyzed the differences in the CT images between the negative expression group (n = 132) and the positive expression group (n = 105), and then the risk factors affecting the expression level of Ki-67 were evaluated. Patients were randomly divided into a training dataset (n = 165) and a validation dataset (n = 72) in a ratio of 7:3. A total of 1,316 quantitative radiomic features were extracted from the Analysis Kinetics (A.K.) software. Radiomic feature selection and radiomic classifier were generated through a least absolute shrinkage and selection operator (LASSO) regression and logistic regression analysis model. The predictive capacity of the radiomic classifiers for the Ki-67 levels was investigated through the ROC curves in the training and testing groups.

Results: The cut-off value of the Ki-67 to distinguish subtypes of lung adenocarcinoma was 5%. A comparison of clinical data and imaging features between the two groups showed that histopathological subtypes and air bronchograms could be used as risk factors to evaluate the expression of Ki-67 in lung adenocarcinoma (p = 0.005, p = 0.045, respectively). Through radiomic feature selection, eight top-class features constructed the radiomic model to pre-operatively predict the expression of Ki-67, and the area under the ROC curves of the training group and the testing group were 0.871 and 0.8, respectively.

Conclusion: Ki-67 expression level with a cut-off value of 5% could be used to differentiate non-invasive lung adenocarcinomas from invasive lung adenocarcinomas. It is feasible and reliable to pre-operatively predict the expression level of Ki-67 in lung adenocarcinomas based on CT radiomic features, as a non-invasive biomarker to predict the degree of malignant invasion of lung adenocarcinoma, and to evaluate the prognosis of the tumor.

A Novel Strategy for the Diagnosis of Pulmonary High-Grade Neuroendocrine Tumor

Correctly diagnosing a histologic type of lung cancer is important for selecting the appropriate treatment because the aggressiveness, chemotherapy regimen, surgical approach, and prognosis vary significantly among histologic types. Pulmonary NETs, which are characterized by neuroendocrine morphologies, represent approximately 20% of all lung cancers. In particular, high-grade neuroendocrine tumors (small cell lung cancer and large cell neuroendocrine tumor) are highly proliferative cancers that have a poorer prognosis than other non-small cell lung cancers. The combination of hematoxylin and eosin staining, Ki-67, and immunostaining of classic neuroendocrine markers, such as chromogranin A, CD56, and synaptophysin, are normally used to diagnose high-grade neuroendocrine tumors; however, they are frequently heterogeneous. This article reviews the diagnostic methods of lung cancer diagnosis focused on immunostaining. In particular, we describe the usefulness of immunostaining by Stathmin-1, which is a cytosolic phosphoprotein and a key regulator of cell division due to its microtubule depolymerization in a phosphorylation-dependent manner, for the diagnosis of high-grade neuroendocrine tumors.

Prognostic and Clinicopathological Value of Ki-67 in Melanoma: A Meta-Analysis

Background

The prognostic and clinicopathological value of Ki-67 in melanoma is controversial. The purpose of this meta-analysis was to determine the prognostic role of Ki-67 in melanoma patients.

Materials and Methods

The PubMed, Cochrane Library, Web of Science, and Embase databases were searched systematically up to April 9, 2021. We calculated the pooled hazard ratios (HRs) and 95% confidence intervals (CIs) to determine the relationship between Ki-67 overexpression and survival outcomes. We also calculated the combined odds ratios (ORs) and 95% CIs to determine the relationship between Ki-67 expression levels and clinicopathologic parameters. All data were statistically analyzed by Stata 11.0.

Results

A total of 10 studies involving 929 patients were included in our meta-analysis. The pooled HR showed that Ki-67 overexpression was connected with poor overall survival rates (HR=2.92, 95% CI=2.17-3.91, p<0.000). However, there was no correlation between Ki-67 overexpression and the PFS (HR=0.999, 95% CI =0.958-1.041, P =0.958; I2 = 21.80%, P =0.258) or RFS (HR=1.14, 95% CI = 0.42-3.11, P =0.993; I2 = 85.00%, P =0.01) rates. Ki-67 expression levels were associated with tumor thickness, but not sex, location, ulceration or vascular invasion.

Conclusion

Ki-67 is a useful poor prognostic indicator for melanoma patients.

Assessment of relationships among clinicopathological characteristics, morphological computer tomography features, and tumor cell proliferation in stage I lung adenocarcinoma

Background

Surgically resected stage I lung adenocarcinoma (ADC) has wide variation in prognosis. It is significant to identify high-risk patients and optimize therapeutic strategy. This study aimed to investigate the relationships among histological grade, serum tumor marker index (TMI), morphological computer tomography (CT) features, and a well-established prognosticator cell proliferation (Ki-67) in stage I ADC.

Methods

Preoperative CT was performed in 182 patients with stage I ADC confirmed by pathology. The Ki-67 expression was acquired by immunohistochemistry. TMI was the square root of standardized serum carcinoembryonic antigen (CEA) and cytokeratin 19 fragments (CYFRA 21-1) values. Tumor shadow disappearance rate (TDR) and other morphological CT features were interpreted by two radiologists. Histological grade, TMI, CT features were statistically evaluated to explore the associations with Ki-67 expression.

Results

In univariate analysis, gender, smoking history, pack-year, histological grade, TNM stage (IA and IB), serum CEA and CYFRA 21-1 status, TMI status, as well as TDR, long-axis diameter, short-axis diameter, lobulation, spiculation, attenuation types, vacuolation, vascular invasion, vascular convergence, thickened bronchovascular bundles, pleural attachment and peripheral fibrosis were significantly associated with Ki-67 expression (all P<0.05). Solid-predominant ADC had the highest Ki-67 expression, followed by micropapillary, papillary and acinar-predominant ADC, while lepidic-predominant ADC had the lowest Ki-67 expression (P<0.001). TDR was negatively correlated with Ki-67 (r =−0.478, P<0.001). Multivariate logistic regression analysis revealed that gender, histological grade, TDR and attenuation types were independent factors associated with Ki-67 expression.

Conclusions

Ki-67 expression differed distinctly according to ADC histological subtypes. High Ki-67 expression is independently associated with male patients of stage I ADC with worse differentiation, lower TDR and solid tumors, which might be of prognostic value for poor prognosis in stage I ADC.