Prognostic factors of EGFR-mutated metastatic adenocarcinoma of lung

Prognostic value of combining clinical factors, 18F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study

OBJECTIVE

To investigate the prognostic value of 18F-FDG PET-based intensity, volumetric features, and deep learning (DL) across different generations of PET scanners in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma receiving tyrosine kinase inhibitor (TKI) treatment.

METHODS

We retrospectively analyzed the pre-treatment 18F-FDG PET of 217 patients with advanced-stage lung adenocarcinoma and actionable EGFR mutations who received TKI as first-line treatment. Patients were separated into analog (n = 166) and digital (n = 51) PET cohorts. 18F-FDG PET-derived intensity, volumetric features, ResNet-50 DL of the primary tumor, and clinical variables were used to predict progression-free survival (PFS). Independent prognosticators were used to develop prediction model. Model was developed and validated in the analog and digital PET cohorts, respectively.

RESULTS

In the analog PET cohort, female sex, stage IVB status, exon 19 deletion, SUVmax, metabolic tumor volume, and positive DL prediction independently predicted PFS. The model devised from these six prognosticators significantly predicted PFS in the analog (HR = 1.319, p < 0.001) and digital PET cohorts (HR = 1.284, p = 0.001). Our model provided incremental prognostic value to staging status (c-indices = 0.738 vs. 0.558 and 0.662 vs. 0.598 in the analog and digital PET cohorts, respectively). Our model also demonstrated a significant prognostic value for overall survival (HR = 1.198, p < 0.001, c-index = 0.708 and HR = 1.256, p = 0.021, c-index = 0.664 in the analog and digital PET cohorts, respectively).

CONCLUSIONS

Combining 18F-FDG PET-based intensity, volumetric features, and DL with clinical variables may improve the survival stratification in patients with advanced EGFR-mutated lung adenocarcinoma receiving TKI treatment. Implementing the prediction model across different generations of PET scanners may be feasible and facilitate tailored therapeutic strategies for these patients.

PDL1-status predicts primary resistance of metastatic, EGFR-mutated non small cell lung cancers to EGFR tyrosine-kinase inhibitors

BACKGROUND

EGFR tyrosine-kinase inhibitors (TKIs) are the reference treatment for metastatic, EGFR-mutated, non-small-cell lung cancers (EGFRm NSCLCs). However, 16-20% of those tumors progress early (3-6 months) and factors predicting that resistance are unknown. This study was undertaken to examine PDL1 status as such a factor.

METHODS

This retrospective analysis included metastatic, EGFRm-NSCLC patients who received first-line 1st-, 2nd- or 3rd-generation EGFR TKIs with PDL1 expression determined in pretreatment biopsies. Kaplan-Meier estimations of probabilities of progression-free survival (PFS) and overall survival (OS) were compared with log-rank test, and logistic-regression analyses.

RESULTS

PDL1 status of the 145 included patients was ≥1% (47%), 1-49% (33%) or ≥50% (14%). For PDL1-positive vs PDL1-negative patients, respectively, median PFS lasted 8 (95% CI: 6-12) vs 12 (95% CI: 11-17) months (p = 0.008), with 18% vs. 8% (NS) of NSCLCs progressing at 3 months, and 47% vs. 18% (HR 0.25 [95% CI 0.10-0.566], p<0.001) at 6 months. Multivariate analysis retained 1st- or 2nd-generation EGFR TKI, brain metastases and albuminemia <35 g/L at diagnosis as significantly associated with shorter PFS, but not PDL1 status, which was independently associated with progression at 6 months (HR 3.76 [1.23-12.63], p = 0.02). PDL1-negative and PDL1-positive patients' OS lasted 27 (95% CI 24-39) and 22 (95% CI 19-41) months, respectively (NS). Multivariate analysis retained only brain metastases or albuminemia <35 g/L at diagnosis as being independently associated with OS.

CONCLUSION

PDL1 expression ≥1% seems to be associated with early progression during the first 6 months of first-line EGFR-TKI treatment of metastatic EGFRm NSCLCs, without impacting OS.

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.

Analysis of non-small cell lung cancer with miliary lung metastasis in patients harboring epidermal growth factor receptor mutations

Miliary lung metastasis is a unique feature of lung metastasis in non-small cell lung cancer (NSCLC), indicating hematogenous dissemination. Some studies reported more frequency of epidermal growth factor receptor (EGFR) mutation and worse prognosis in these patients. Cases were identified from Chi-Mei medical center cancer registry for the period 2015-2019. Inclusion criteria were NSCLC with contra-lateral lung metastasis harboring EGFR mutation, under tyrosine kinase inhibitor (TKI) prescription. Patients with miliary or non-miliary lung metastasis were enrolled for survival analysis. 182 NSCLC patients were enrolled for assessing time to discontinuation of TKI (TD-TKI), progression-free survival (PFS) and overall survival (OS). 54 patients with miliary lung metastasis had average 13.2 months [95% confidence interval (CI) 10.7-15.6] of TD-TKI, 11.4 months (95% CI 9.3-13.6) of PFS, and 21.3 months (95% CI 16.8-25.8) of OS, which were shorter than non-miliary group with marginally statistical significance. In multivariate analysis, miliary lung metastasis had no statistical significance, and other strong prognostic indicators were found including performance status, liver metastasis, EGFR type, and generation of TKI. In NSCLC patients harboring EGRF mutation under TKI prescription, miliary lung metastasis was not a dominant indicator for outcomes evaluation.

Prognostic Impact of Pleural Effusion in Patients with Malignancy: A Systematic Review and Meta-Analysis

The exact role of pleural effusion in the prognosis of cancer patients remains unclear. We aimed to systematically review the prognostic value of pleural effusion in patients with cancer. We performed a systematic review and meta‐analysis with a systematic literature search. All cohort studies with available overall survival (OS) and progression‐free survival (PFS) results for patients with cancer with or without pleural effusion were included. The Mantel–Haenszel method was used to calculate the pooled hazard ratios (HRs) and 95% confidence intervals (CIs). Heterogeneity and publication bias were examined. Subgroup analysis and sensitivity analysis were performed. A total of 47 studies with 146,117 patients were included in the analysis. For OS, pleural effusion was a prognostic factor associated with a poor prognosis for patients with cancer (HR, 1.58, 95% CI, 1.43–1.75; I² 94.8%). In the subgroup analysis, pleural effusion was a prognostic factor associated with poor survival for patients with lung cancer (HR, 1.44, 95% CI, 1.35–1.54; I² 60.8%), hematological cancer (HR, 2.79, 95% CI, 1.63–4.77; I² 29.4%) and other types of cancer (HR, 2.08, 95% CI, 1.43–3.01; I² 55.1%). For PFS, pleural effusion was a prognostic factor associated with a poor prognosis for patients with cancer (HR, 1.61, 95% CI, 1.28–2.03; I² 42.9%). We also observed that massive pleural effusion was a prognostic factor associated with a poorer prognosis compared to minimal pleural effusion. Pleural effusion had prognostic value in both OS and PFS of patients with cancer, except for patients with malignant pleural mesothelioma, regardless of whether the malignant effusion was confirmed histologically or cytologically. However, future evidence of other pleural effusion characteristics is still needed.

Impact of angiogenesis inhibitor eligibility on the prognosis of patients with non-small cell lung cancer harboring EGFR mutation

Background

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR‐TKIs) are currently the primary treatment option for patients with EGFR‐mutant non‐small cell lung cancer (NSCLC). However, the effect of EGFR‐TKIs are eventually weakened due to resistance, and there is also a differential efficacy based on EGFR mutation subtypes. The combination of angiogenesis inhibitor (AI) with EGFR‐TKI has shown better efficacy than EGFR‐TKI monotherapy, regardless of the mutation subtypes. Nevertheless, the effect of AI eligibility on overall survival (OS) and progression‐free survival (PFS) remains to be elucidated. Thus, we assessed this impact on patients with NSCLC harboring EGFR mutation.

Methods

In this study, the data for 450 patients with EGFR‐mutant NSCLC, who were treated with EGFR‐TKI monotherapy, were retrospectively analyzed for AI eligibility. The patients were categorized into AI‐eligible (AI fit) and ineligible groups (AI unfit).

Results

The median PFS of the AI fit group was 12.9 months, compared to 9.6 months in the unfit group (p = 0.007), and OS was also significantly longer in the AI fit group (median OS = 33.0 months) compared to that in the unfit group (18.5 months, p < 0.001). Multivariate analysis indicated that AI ineligibility was associated with shorter PFS and poor prognosis. Also, in the AI fit group, there was no significant difference in the PFS between EGFR L858R mutation and EGFR exon 19 deletion (median PFS = 11.5 months vs. 13.8 months; p = 0.17).

Conclusions

From our study, AI eligibility resulted in longer OS and PFS, and also had different effects on patients with EGFR L858R and exon 19 deletion. Since this selection bias may have affected previous clinical trial data on the efficacy of AI combination therapy, their results should be carefully considered henceforth.

Detection of the mesenchymal-to-epithelial transition of invasive non-small cell lung cancer cells by their membrane undulation spectra

A cancer cell changes its state from being epithelial- to mesenchymal-like in a dynamic manner during tumor progression. For example, it is well known that mesenchymal-to-epithelial transition (MET) is essential for cancer cells to regain the capability of seeding on and then invading secondary/tertiary regions. However, there is no fast yet reliable method for detecting this transition. Here, we showed that membrane undulation of invasive cancer cells could be used as a novel marker for MET detection, both in invasive model cell lines and repopulated circulating tumor cells (rCTCs) from non-small cell lung cancer (NSCLC) patients. Specifically, using atomic force microscopy (AFM), it was found that the surface oscillation spectra of different cancer cells, after undergoing MET, all exhibited two distinct peaks from 0.001 to 0.007 Hz that are absent in the spectra before MET. In addition, by adopting the long short-term memory (LSTM) based recurrent neural network learning algorithm, we showed that the positions of recorded membrane undulation peaks can be used to predict the occurrence of MET in invasive NSCLC cells with high accuracy (>90% for model cell lines and >80% for rCTCs when benchmarking against the conventional bio-marker vimentin). These findings demonstrate the potential of our approach in achieving rapid MET detection with a much reduced cell sample size as well as quantifying changes in the mesenchymal level of tumor cells.

Diagnostic and Predictive Values of 18F-FDG PET/CT Metabolic Parameters in EGFR-Mutated Advanced Lung Adenocarcinoma

Purpose

The clinical implications of the metabolic parameters of ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET/CT) in epidermal growth factor receptor (EGFR)-mutated lung cancer are not fully understood. The aim of this study was to evaluate the diagnostic and prognostic utility of the parameters in EGFR-mutated lung cancer patients.

Patients and Methods

We retrospectively enrolled 134 patients with advanced lung adenocarcinoma (72 EGFR-negative and 62 EGFR-positive). We evaluated the correlation between EGFR mutational status and the maximum standardized uptake value (SUVmax), as well as the associations between treatment outcomes in EGFR-mutated patients and various metabolic parameters of primary tumors. For the best predictive parameters, we calculated the metabolic tumor volume (MTV) and total lesion glycolysis (TLG) using two SUV cutoffs: 1.5 (MTV_1.5, TLG_1.5) and 2.5 (MTV_2.5, TLG_2.5).

Results

Mean SUVmax was lower for EGFR-mutated tumors compared with EGFR wild-type (6.11 vs 10.41, p < 0.001) tumors. Low SUVmax was significantly associated with positive EGFR mutation (odds ratio = 1.74). Multivariate analysis for survival demonstrated that high MTV_1.5, TLG_1.5, MTV_2.5, and TLG_2.5 were independently associated with shorter progression-free survival (PFS) and overall survival (OS), and the highest hazard ratios were found in TLG_1.5 (3.26 for PFS and 4.62 for OS).

Conclusion

SUVmax may be predictive for EGFR mutational status, and MTV and TLG of primary tumors may be promising prognostic parameters; ¹⁸F-FDG PET/CT has potential utility for the risk stratification of EGFR-mutated patients treated with targeted therapy.

A Radiomics nomogram for predicting bone metastasis in newly diagnosed prostate cancer patients

PURPOSE

To establish and validate a radiomics nomogram for predicting bone metastasis (BM) in patients with newly diagnosed prostate cancer (PCa).

METHOD

One-hundred and sixteen patients (training cohort: n = 81; validation cohort: n = 35) who underwent prostate MR imaging and confirmed by pathology with newly diagnosed PCa from January 2014 to January 2019 were enrolled. Radiomic features were extracted from diffusion-weighted, axial T2-weighted fat suppression, and dynamic contrast-enhanced T1-weighted MRI of each patient. Dimension reduction, feature selection, and radiomics feature construction were performed using the least absolute shrinkage and selection operator (LASSO) regression. Combined with independent clinical risk factors, a multivariate logistic regression model was used to establish a radiomics nomogram. Nomogram calibration and discrimination were evaluated in training cohort and verified in the validation cohort. Finally, the clinical usefulness of the nomogram was estimated through decision curve analysis (DCA).

RESULTS

Radiomics signature consisting of 12 selected features was significantly correlated with bone status (P < 0.001 for both training and validation sets). The radiomics nomogram combined a radiomics signature from multiparametric MR images with independent clinic risk factors. The model showed good discrimination and calibration in the training cohort (AUC 0.93, 95% CI, 0.86 to 0.99) and the validation cohort (AUC 0.92, 95% CI, 0.84 to 0.99). DCA also demonstrated the clinical use of the radiomics model.

CONCLUSION

The radiomics nomogram, which incorporates the multiparametric MRI-based radiomics signature and clinical risk factors, can be conveniently used to promote individualized prediction of BM in patients with newly diagnosed PCa.

[Lung Adenocarcinomas with Pulmonary Miliary Metastases: A Case Report and Literature Review]

BACKGROUND

Lung adenocarcinoma with miliary metastasis in both lungs is easily misdiagnosed. The aim of this study is to investigate the clinical features of lung adenocarcinoma with miliary metastases in both lungs and to improve the clinician's understanding of the disease.

METHODS

The clinical manifestation, radiology and pathology were analyzed in one patient with miliary intrapulmonary carcinomatosis in Affiliated Hospital of Zunyi Medical University. A review of literature was performed with "miliary intrapulmonary carcinomatosis", "lung cancer miliary", "pulmonary nodule, lung cancer" and "EGFR miliary" as key words in PubMed, Wangfang datebase and CNKI.

RESULTS

The patient was a 52 year-old woman with a history of productive cough for 2 months, which aggraveted with shortness of breath for 1 month. Her computed tomography of chest showed diffuse military nodules distributed at bilateral lungs. Computed tomography (CT)-guided needle biopsy of the left lung revealed lung adenocarcinoma and epidermal growth factor receptor (EGFR) exon 21 L858R mutation. The patient was treated with gefitinib 250 mg per day. The chest CT was reviewed several times during this period, which shows the double lung nodules were reduced. The patient is generally in good condition and her symptoms have improved. By literature review, we found relevant 7 Chinese articles and 56 English articles, a total of 16 cases have been reported. 17 patients were lung adenocarcinoma, 2 patients did not describe whether to detect EGFR gene mutations, 1 patient did not have EGFR gene mutation; 10 patients were EGFR exon 19 deletion, 1 patient was ALK positive, 1 patient was EGFR exon 21L858R mutation, 2 patients were EGFR exon 20 insertion.

CONCLUSIONS

Lung adenocarcinoma with miliary metastasis in both lungs is a rare phenomenon. We should pay attention to the performance to avoid misdiagnosis. Most of the adenocarcinoma subtypes have EGFR mutations, and EGFR-tyrosine kinase inhibitors (EGFR-TKIs) are the preferred treatment choice for this type of patients.