Epidermal Growth Factor Receptor Status Research Articles

Improved Prediction of Epidermal Growth Factor Receptor Status by Combined Radiomics of Primary Nonsmall-Cell Lung Cancer and Distant Metastasis.

This study aimed to investigate radiomics based on primary nonsmall-cell lung cancer (NSCLC) and distant metastases to predict epidermal growth factor receptor (EGFR) mutation status. A total of 290 patients (mean age, 58.21 ± 9.28) diagnosed with brain (BM, n = 150) or spinal bone metastasis (SM, n = 140) from primary NSCLC were enrolled as a primary cohort. An external validation cohort, consisting of 69 patients (mean age, 59.87 ± 7.23; BM, n = 36; SM, n = 33), was enrolled from another center. Thoracic computed tomography-based features were extracted from the primary tumor and peritumoral area and selected using the least absolute shrinkage and selection operator regression to build a radiomic signature (RS-primary). Contrast-enhanced magnetic resonance imaging-based features were calculated and selected from the BM and SM to build RS-BM and RS-SM, respectively. The RS-BM-Com and RS-SM-Com were developed by integrating the most important features from the primary tumor, BM, and SM. Six computed tomography-based features showed high association with EGFR mutation status: 3 from intratumoral and 3 from peritumoral areas. By combination of features from primary tumor and metastases, the developed RS-BM-Com and RS-SM-Com performed well with areas under curve in the training (RS-BM-Com vs RS-BM, 0.936 vs 0.885, P = 0.177; RS-SM-Com vs RS-SM, 0.929 vs 0.843, P = 0.003), internal validation (RS-BM-Com vs RS-BM, 0.920 vs 0.858, P = 0.492; RS-SM-Com vs RS-SM, 0.896 vs 0.859, P = 0.379), and external validation (RS-BM-Com vs RS-BM, 0.882 vs 0.805, P = 0.263; RS-SM-Com vs RS-SM, 0.865 vs 0.816, P = 0.312) cohorts. This study indicates that the accuracy of detecting EGFR mutations significantly enhanced in the presence of metastases in primary NSCLC. The established radiomic signatures from this approach may be useful as new predictors for patients with distant metastases.

The therapeutic potential of natural metabolites in targeting endocrine-independent HER-2-negative breast cancer.

Breast cancer (BC) is a heterogenous disease, with prognosis and treatment options depending on Estrogen, Progesterone receptor, and Human Epidermal Growth Factor Receptor-2 (HER-2) status. HER-2 negative, endocrine-independent BC presents a significant clinical challenge with limited treatment options. To date, promising strategies like immune checkpoint inhibitors have not yielded breakthroughs in patient prognosis. Despite being considered archaic, agents derived from natural sources, mainly plants, remain backbone of current treatment. In this context, we critically analyze novel naturally-derived drug candidates, elucidate their intricate mechanisms of action, and evaluate their pre-clinical in vitro and in vivo activity in endocrine-independent HER-2 negative BC. Since pre-clinical research success often does not directly correlate with drug approval, we focus on ongoing clinical trials to uncover current trends. Finally, we demonstrate the potential of combining cutting-edge technologies, such as antibody-drug conjugates or nanomedicine, with naturally-derived agents, offering new opportunities that utilize both traditional cytotoxic agents and new metabolites.

EfficientNet-Based System for Detecting EGFR-Mutant Status and Predicting Prognosis of Tyrosine Kinase Inhibitors in Patients with NSCLC

We aimed to develop and validate a deep learning-based system using pre-therapy computed tomography (CT) images to detect epidermal growth factor receptor (EGFR)-mutant status in patients with non-small cell lung cancer (NSCLC) and predict the prognosis of advanced-stage patients with EGFR mutations treated with EGFR tyrosine kinase inhibitors (TKI). This retrospective, multicenter study included 485 patients with NSCLC from four hospitals. Of them, 339 patients from three centers were included in the training dataset to develop an EfficientNetV2-L-based model (EME) for predicting EGFR-mutant status, and the remaining patients were assigned to an independent test dataset. EME semantic features were extracted to construct an EME-prognostic model to stratify the prognosis of EGFR-mutant NSCLC patients receiving EGFR-TKI. A comparison of EME and radiomics was conducted. Additionally, we included patients from The Cancer Genome Atlas lung adenocarcinoma dataset with both CT images and RNA sequencing data to explore the biological associations between EME score and EGFR-related biological processes. EME obtained an area under the curve (AUC) of 0.907 (95% CI 0.840–0.926) on the test dataset, superior to the radiomics model (P = 0.007). The EME and radiomics fusion model showed better (AUC, 0.941) but not significantly increased performance (P = 0.895) compared with EME. In prognostic stratification, the EME-prognostic model achieved the best performance (C-index, 0.711). Moreover, the EME-prognostic score showed strong associations with biological pathways related to EGFR expression and EGFR-TKI efficacy. EME demonstrated a non-invasive and biologically interpretable approach to predict EGFR status, stratify survival prognosis, and correlate biological pathways in patients with NSCLC.

Correlation analysis of EGFR gene mutation abundance and the efficacy of targeted therapy with osimertinib in nonsmall cell lung cancer-a case control study.

In nonsmall cell lung cancer (NSCLC), epidermal growth factor receptor (EGFR) mutation is the primary cancer-causing mutation. But whether the practical effectiveness of EGFR tyrosine kinase inhibitors (TKIs) can be influenced by plasma EGFR mutation abundance when treating patients with advanced NSCLC remains unanswered. Therefore, this research was intended to reveal the connection between plasma EGFR mutation abundance and clinical outcomes in osimertinib-treated patients with advanced NSCLC. A total of 120 patients with advanced NSCLC were retrospectively analyzed, and 56 patients with EGFR-mutation-positive NSCLC receiving osimertinib first-line therapy were eventually screened and included. The baseline status and abundance of plasma EGFR in patients with NSCLC were detected by cSMART, and the ratio of 0.1 was the critical value. Imaging examinations were performed every 8-12 weeks for the assessment of tumor response. The relationship between baseline EGFR mutation abundance and clinical outcomes of TKI therapy was analyzed. The objective response rates (ORR) of EGFR-mutant patients in the high-/low-abundance groups were 69.2% and 40.0%, respectively. The high abundance group had an obviously higher ORR than the low abundance group (P = 0.029). A much longer median progression-free survival (mPFS) was demonstrated in patients with high mutation abundance than in patients with low abundance (11.2 months vs 7.1 months, P = 0.0133). As for the median overall survival (mOS), it showed the same trend as mPFS in patients from different groups (15.5 vs 10.7 months, P = 0.0028). The role of plasma mutation abundance as an independent prognostic factor for both PFS (hazard ratios [HR]: 0.30, P = 0.006) and OS (HR: 0.35, P = 0.004) was demonstrated by multivariate Cox regression analysis. There is a close connection between plasma EGFR mutation abundance and survival benefit in patients with NSCLC, which can be used for predicting the efficacy of EGFR-TKI targeted therapy. Our study is expected to provide a research basis for screening patients to whom the EGFR-TKI therapy is beneficial.

Resected EGFR-mutated non-small-cell lung cancers: incidence and outcomes in a European population (GFPC Exerpos Study).

Few epidemiological data are available on surgically treated Caucasian patients with non-small-cell lung cancers (NSCLCs) harboring epidermal growth factor receptor (EGFR) mutations. The main objective of this study was to describe, in the real-world setting, these patients' incidence, clinical, and tumoral characteristics. The participating centers included all consecutive localized non-squamous NSCLC patients undergoing surgery between January 2018 and December 2019 in France. EGFR status was determined retrospectively when not available before surgery. The study includes 1391 no squamous NSCLC patients from 16 centers; EGFR status was determined before surgery in 692 (49.7%) of the cases and conducted as part of the study for 699 (50.3%); 171 (12.3%) were EGFR mutated; median age: 70 (range: 36-88) years; female: 59.6%; never smokers: 75.7%; non-squamous histology 97.7%, programmed death ligand-1 expression 0%/1-49%/⩾50 in 60.5%/25.7%/13.8%, respectively. Surgery was predominantly lobectomy (81%) or segmentectomy (14.9%), with systematic lymph node dissection in 95.9%. Resection completeness was R0 for 97%. Post-surgery staging was as follows: IA: 52%, IB: 16%, IIA: 4%, IIB: 10%, IIIA: 16%, and IIIB: 0.05%; EGFR mutation exon was Del19/exon 21 (L858R)/20/18 in 37.4%/36.8%/14%, and 6.4% of cases, respectively; 31 (18%) patients received adjuvant treatment (chemotherapy: 93%, EGFR tyrosine kinase inhibitor: 0%, radiotherapy: 20%). After a median follow-up of 31 (95% confidence interval: 29.6-33.1) months, 45 (26%) patients relapsed: 11/45 (24%) locally and 34 (76%) with metastatic progression. Median disease-free survival (DFS) and overall survival were not reached and 3-year DFS was 60%. This real-world analysis provides the incidence and outcomes of resected EGFR-mutated NSCLCs in a European patient cohort.

End-to-end Prediction of EGFR Mutation Status with Denseformer.

Accurate genotyping of the epidermal growth factor receptor (EGFR) is critical for the treatment planning of lung adenocarcinoma. Currently, clinical identification of EGFR genotyping highly relies on biopsy and sequence testing which is invasive and complicated. Recent advancements in the integration of computed tomography (CT) imagery with deep learning techniques have yielded a non-invasive and straightforward way for identifying EGFR profiles. However, there are still many limitations for further exploration: 1) most of these methods still require physicians to annotate tumor boundaries, which are time-consuming and prone to subjective errors; 2) most of the existing methods are simply borrowed from computer vision field which does not sufficiently exploit the multi-level features for final prediction. To solve these problems, we propose a Denseformer framework to identify EGFR mutation status in a real end-to-end fashion directly from 3D lung CT images. Specifically, we take the 3D whole-lung CT images as the input of the neural network model without manually labeling the lung nodules. This is inspired by the medical report that the mutational status of EGFR is associated not only with the local tumor nodules but also with the microenvironment surrounded by the whole lung. Besides, we design a novel Denseformer network to fully explore the distinctive information across the different level features. The Denseformer is a novel network architecture that combines the advantages of both convolutional neural network (CNN) and Transformer. Denseformer directly learns from the 3D whole-lung CT images, which preserves the spatial location information in the CT images. To further improve the model performance, we designed a combined Transformer module. This module employs the Transformer Encoder to globally integrate the information of different levels and layers and use them as the basis for the final prediction. The proposed model has been tested on a lung adenocarcinoma dataset collected at the Affiliated Hospital of Zunyi Medical University. Extensive experiments demonstrated the proposed method can effectively extract meaningful features from 3D CT images to make accurate predictions. Compared with other state-of-the-art methods, Denseformer achieves the best performance among current methods using deep learning to predict EGFR mutation status based on a single modality of CT images.

Hormone Receptors and HER2 Status of Patients with Breast Cancer in a Tertiary Center of Nepal: A Descriptive Cross-Sectional Study

Introduction: The second most prevalent cancer among women in Nepal is breast cancer. The assessment of human epidermal growth factor receptor-2 (HER2), progesterone receptor (PR), and estrogen receptor (ER) status in patients with breast cancer is currently regarded as standard practice because of its prognostic and predictive value. This study aims to find the incidence of Hormone receptor and HER2 status in patients with breast cancer. Methods: This was a descriptive observational cross-sectional study that assessed the immunohistochemistry markers of different histological types of breast cancer patients who visited a tertiary center in Nepal. Retrospective data from August 1, 2022, to July 30, 2023, were gathered from computer records of all the patients diagnosed with breast cancer who visited the Tribhuvan University Teaching Hospital (TUTH). SPSS version 26.0 was used for statistical analysis. Results: A total of 102 patients with breast cancer were included. The mean age of the patients was 50.51±12.08 years. Only one patient was male. The analysis showed that 62 (60.78%) of total patients had ER/PR positive breast cancer and 40 (39.2%) were HER2 positive with a higher number among Janajati and the age group 41-60 years. Similarly, the incidence of triple-negative breast cancer was 21 (20.59%) of all patients. Conclusion: The majority of breast cancer patients in our study were ER/PR positive, followed by HER2-positive and triple-negative cases. A higher prevalence was observed among the Janajati ethnic group and those aged 41-60 years.

Neoadjuvant pyrotinib plus trastuzumab and chemotherapy for HER2-positive breast cancer: a prospective cohort study

BackgroundThis prospective study aims to investigate the efficacy and safety of pyrotinib (P) combined with 4 cycles of epirubicin and cyclophosphamide followed by 4 cycles of taxane and trastuzumab (P + EC-TH) regimen as neoadjuvant therapy for human epidermal growth factor receptor 2 (HER2) positive breast cancer and to investigate the predictive value of p53, p63, and epidermal growth factor receptor (EGFR) status for neoadjuvant efficacy.MethodsA total of 138 HER2-positive breast cancer patients who received neoadjuvant therapy and underwent surgery were included. Case group: 55 patients received P + EC-TH regimen. Control group: 83 patients received EC-TH regimen. The chi-square test, Fisher’s exact test, and logistic regression analysis were applied. The primary endpoint was total pathologic complete response (tpCR), and the secondary endpoints were breast pathologic complete response (bpCR), overall response rate (ORR), and adverse events (AEs).ResultsIn the case group, the tpCR rate was 63.64% (35/55), the bpCR rate was 69.09% (38/55), and the ORR was 100.00% (55/55). In the control group, the tpCR rate was 39.76% (33/83), the bpCR rate was 44.58% (37/83), and the ORR was 95.18% (79/83). The case group had significantly higher tpCR and bpCR rates than those of the control group (P < 0.05), but there was no significant difference in ORR (P > 0.05). The tpCR was associated with the status of estrogen receptor (ER), progesterone receptor (PR), and androgen receptor (AR), and the patients with any negative ER, PR, AR, or combined, were more likely to achieve tpCR than those with positive results (P < 0.05). The p53-positive patients were more likely to achieve tpCR and bpCR than p53-negative patients (P < 0.05). The incidence of hypokalemia and diarrhea in the case group was higher than that in the control group (P < 0.05). The AEs developed were all manageable, and no treatment-related death occurred.ConclusionThe efficacy and safety of the P + EC-TH regimen were verified by this study. The HER2-positive breast cancer patients treated with the EC-TH neoadjuvant regimen were more likely to achieve tpCR or bpCR if pyrotinib was administered simultaneously.

Dual-targeting compounds possessing enhanced anticancer activity via microtubule disruption and histone deacetylase inhibition

Dual-targeting anticancer agents 4–29 are designed by combining the structural features of purine-type microtubule-disrupting compounds and HDAC inhibitors. A library of the conjugate compounds connected by appropriate linkers was synthesized and found to possess HDACs inhibitory activity and render microtubule fragmentation by activating katanin, a microtubule-severing protein. Among various zinc-binding groups, hydroxamic acid shows the highest inhibitory activity of Class I HDACs, which was also reconfirmed by three-dimensional quantitative structure-activity relationship (3D-QSAR) pharmacophore prediction. The purine–hydroxamate conjugates exhibit enhanced cytotoxicity against MDA-MB231 breast cancer cells, H1975 lung cancer cells, and various clinical isolated non-small-cell lung cancer cells with different epidermal growth factor receptor (EGFR) status. Pyridyl substituents could be used to replace the C2 and N9 phenyl moieties in the purine-type scaffold, which can help to improve the solubility under physiological conditions, thus increasing cytotoxicity. In mice treated with the purine–hydroxamate conjugates, the tumor growth rate was significantly reduced without causing toxic effects. Our study demonstrates the potential of the dual-targeting purine–hydroxamate compounds for cancer monotherapy.

Real-World Data on Second-Line Therapy with Ramucirumab for Metastatic Gastric Cancer: A Two-Center Study on Romanian Population.

(1) Background: Following the results of RAINBOW and REGARD trials, ramucirumab was approved as the standard second-line treatment for patients with advanced or metastatic gastric or gastroesophageal junction (GEJ) cancer, alone or in combination with paclitaxel. The present study aimed to evaluate the efficacy and safety of ramucirumab in the Romanian population during every-day clinical practice. (2) Methods: A two-center, retrospective, observational study evaluated patients with metastatic gastric and GEJ cancer treated with ramucirumab monotherapy or associated with paclitaxel. The patients were treated between 2018 and 2022 in two Romanian centers as follows: 18 patients underwent treatment with ramucirumab monotherapy, while 51 received the combined treatment regimen. Study endpoints included median progression-free survival (PFS), median overall survival (OS), and the evaluation of treatment-induced adverse events (AEs). (3) Results: In the study cohort (n = 69), the most frequent treatment-induced AE in the ramucirumab plus paclitaxel arm was hematological toxicity; the most common AE for patients treated with ramucirumab monotherapy was fatigue and headache. Overall, the median PFS was 4.7 months (95% CI: 3.4-5.9 months) and median OS was 18.23 months (95% CI: 15.6-20.7 months). PFS was correlated with the number of treatment cycle administrations, Eastern Cooperative Oncology Group performance status at treatment initiation, and metastatic site (visceral vs. peritoneal). OS was correlated with the number of treatment cycles administered and human epidermal growth factor receptor-2 status. (4) Conclusions: The results support the previously described toxicity profile for ramucirumab monotherapy or associated with paclitaxel and demonstrated a relatively superior median PFS.

BIOM-24. PREDICTION OF DISTANT RECURRENCE IN GLIOBLASTOMA PATIENTS TREATED WITH STANDARD THERAPY

Abstract BACKGROUND Infiltrative growth is a hallmark of glioblastoma (GBM) and is a major factor in therapeutic failure. We aimed to identify clinical and molecular factors associated with distance recurrence in glioblastoma patients treated with standard therapy (radiotherapy with concomitant and adjuvant temozolomide). METHODS Two prospective cohorts of consecutive, non-selected GBM patients administered standard therapy as primary treatment between year 2005-2016 (Cohort 1) and 2016-2021 (Cohort 2) at Rigshospitalet, Copenhagen were included. Distant recurrence was defined as a new contrast-enhancing tumor &amp;gt; 2 cm from the gross tumor volume. Clinical and molecular factors were screened for association with time to distant recurrence using univariate Cox regression analysis. The final model was generated employing multivariate analysis. RESULTS Cohort 1 and 2 included 628 and 395 patients, respectively. Out of the recurrence pattern evaluable patients, distant recurrence was observed in 117 patients (23%) in Cohort 1 and 73 patients (22%) in Cohort 2. PRELIMINARY RESULTS In Cohort 1, multivariate analysis showed that corticosteroid use, age, multifocal disease, ECOG performance status, and degree of tumor resection were not associated (p &amp;gt; 0.10) with distant recurrence. Two factors were independently associated with a higher likelihood of distant recurrence, namely non-methylated promoter of the MGMT gene (HR = 1.93; 95% CI:1.27-2.95; p = 0.002) and positive expression of Epidermal Growth Factor Receptor (EGFR) (HR = 3.70; 95% CI: 1.61-8.33; p = 0.002). In Cohort 2, the EGFR status was not available but the association of non-methylated MGMT with distant recurrence was validated (HR = 2.67; 95% CI: 1.62-4.42; p = 0.0001). CONCLUSION Non-methylated MGMT and positive EGFR expression were independent predictors of distant recurrence. Non-methylated MGMT was validated in Cohort 2 and can be used for risk stratification and to enrich clinical trials aiming at improved local or distant tumor control.

Osimertinib as a Potential Targeted Therapy for Non-Small Cell Lung Carcinoma (NSCLC) Patients with EGFR Exon 20 T790M

BACKGROUND: Emergence of drug resistance due to epidermal growth factor receptor (EGFR) Exon 20 T790M poses a challenge in the effective management of non-small cell lung carcinoma (NSCLC). Significant breakthrough in the management of NSCLC with a specific genetic alteration causes substantial condition improvement in patients whose cancer progressed after first-generation tyrosine kinase inhibitor treatment and who developed tumors with EGFR Exon 20 T790M mutation. The present study analyzed a cohort of NSCLC patients and investigated the incidence of the EGFR Exon 20 T790M status with Osimertinib therapy, along with its impact on survival rates.METHODS: This was a retrospective cohort study on 22 NSCLC subjects who were genetically examined for EGFR status from plasmic cell free total nucleic acid. Subjects with EGFR Exon 20 T790M mutation were treated with/without Osimertinib. Demographic and clinical data were descriptively summarized, and the differences of each variable and correlation between survival rate and EGFR Exon 20 T790M were analyzed.RESULTS: Subjects with (n=13) and without (n=9) EGFR Exon 20 T790M had survival rates of 10.77±2.45 and 4.78±1.48, respectively (p=0.000). Based on 1-year survival status of subjects with EGFR Exon 20 T790M, there were 3 Osimertinib-treated survivors and 2 Osimertinib-treated non-survivors. Eight subjects with EGFR Exon 20 T790M and without Osimertinib treatment did not survive (p=0.001).CONCLUSION: Since the treatment of Osimertinib demonstrated a noteworthy survival rate among NSCLC subjects with EGFR Exon 20 T790M, thus Osimertinib could be suggested as a potential targeted therapy for NSCLC subjects with EGFR Exon 20 T790M.KEYWORDS: non-small cell lung carcinoma, EGFR, Exon 20, T790M, osimertinib

The Effect of Clinical (Anatomical) and Prognostic Stage Groups on Survival in Patients Diagnosed with Breast Cancer: MULTI-Center Study Results, TROD Breast Cancer Study Group

The American Joint Committee on Cancer (AJCC) anatomic stage groups have arguably been the most powerful method in predicting breast cancer outcomes. In the present study, we aimed to determine the differences between anatomical stage and clinical prognostic stage groups, which were obtained by adding biological markers such as histologic tumor grade, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 status to patients diagnosed with breast cancer, the rate of change in stage, and the effect of stage change on survival. The study protocol was sent to all radiation oncology centers in Türkiye. Four centers enrolled their patients to the study. A total of 1470 stage I-III breast cancer patients with complete information on biological markers (histologic tumor grade, hormone receptor, and c-erb B2 receptor status), haven't been treated with neoadjuvant therapy were included to the study and evaluated retrospectively. The 8th edition of AJCC consolidated biological markers in to clinical prognostic stage groups. Kaplan-Meier curves were used to estimate survival. The log-rank test was used to compare the difference between groups. The Cox proportional-hazards regression model was used to determine the association between anatomic-prognostic stage, disease-free survival (DFS), and overall survival (OS). The median follow-up time was 82 (6-237) months. Median age of the patients was 52 years (20-88) and 865 cases (58.8%) were in the postmenopausal period. The axillary lymph node status was negative (N0) in 765 patients (52.1%). Tumor grade was grade I in 200 patients (13.6%), grade II in 812 patients (55.2%) and grade III in 452 patients (30.7%). Estrogen receptor status was positive in 1247 patients (84.8%), PR status was positive in 1178 patients and Her2-neu status was positive in 207 patients (14.1%). A stage change has been identified in a total of 777 patients (52.9%). Compared with the anatomic stage groups, application of the clinical prognostic stage groups assigned 46.4% cases lower and 6.5% cases higher stage. Five- and ten-year OS and DFS rates of the patients are 73.7%, 44.3% and 91.9%, 86.3% respectively. Age (p<0.001), tumor grade (p<0.001), ER status (p<0.001), PR status (p<0.001), cerbB2 receptor status (p = 0.025) were found to be statistically significant variables in multivariable analysis for OS. For DFS, multivariable analysis showed that age (p = 0.027), tumor grade (p = 0.005), anatomical stage (p<0.001) and assigned to higher stage (p = .001) were statistically significant variables. Hormone receptors and c-erb B2 receptor status are independent variables which impact OS and DFS in our patient group which is mostly consisted of early-stage cases according to anatomical stage. In prognostic staging, upstaging stands out as an independent prognostic factor for DFS. The 8th edition of AJCC prognostic stage groups determines the prognosis much better in our patient cohort.

CT-based non-invasive identification of the most common gene mutation status in patients with non-small cell lung cancer.

Epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) are mutually exclusive, and they are two important genes that are most prone to mutation in patients with non-small cell lung cancer. This retrospective study investigated the ability of radiomics to predict the mutation status of EGFR and KRAS in patients with non-small cell lung cancer (NSCLC) and guide precision medicine. Computed tomography images of 1045 NSCLC patients from five different institutions were collected, and 1204 imaging features were extracted. In the training set (EGFR: 678, KRAS: 246), Max-Relevance and Min-Redundancy and least absolute shrinkage and selection operator logistic regression were used to screen radiomics features. The combination of selected radiomics features and clinical factors was used to establish the combined models in identifying EGFR and KRAS mutation status, respectively, through stepwise logistic regression. Then, on two independent external validation sets (EGFR: 203/164, KRAS: 123/95), the performance of each model was evaluated separately, and then the overall performance of predicting the two mutation states was calculated. In the EGFR and KRAS groups, radiomics signatures comprised 14 and 10 radiomics features, respectively. They were mutually exclusive between the tumors with positive EGFR mutation and those with positive KRAS mutation in imaging phenotype. For the EGFR group, the area under the curve (AUC) of the combined model in the two validation sets was 0.871 (95% CI: 0.821-0.926) and 0.861 (95% CI: 0.802-0.911), respectively, whereas the AUC of the combined model in the two validation sets was 0.798 (95% CI: 0.739-0.850) and 0.778 (95% CI: 0.735-0.821), respectively, for the KRAS group. Considering both EGFR and KRAS, the overall precision, recall, and F1-score of the combined model in the two validation sets were 0.704, 0.844, and 0.768, as well as 0.754, 0.693, and 0.722, respectively. Our study demonstrates the potential of radiomics in the non-invasive identification of EGFR and KRAS mutation status, which may guide patients with non-small cell lung cancer to choose the most appropriate personalized treatment. This method can be used when biopsy will bring unacceptable risk to patients with NSCLC.

Deep learning based automated epidermal growth factor receptor and anaplastic lymphoma kinase status prediction of brain metastasis in non-small cell lung cancer.

The aim of this study was to investigate the feasibility of developing a deep learning (DL) algorithm for classifying brain metastases from non-small cell lung cancer (NSCLC) into epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK) rearrangement groups and to compare the accuracy with classification based on semantic features on imaging. Data set of 117 patients was analysed from 2014 to 2018 out of which 33 patients were EGFR positive, 43 patients were ALK positive and 41 patients were negative for either mutation. Convolutional neural network (CNN) architecture efficient net was used to study the accuracy of classification using T1 weighted (T1W) magnetic resonance imaging (MRI) sequence, T2 weighted (T2W) MRI sequence, T1W post contrast (T1post) MRI sequence, fluid attenuated inversion recovery (FLAIR) MRI sequences. The dataset was divided into 80% training and 20% testing. The associations between mutation status and semantic features, specifically sex, smoking history, EGFR mutation and ALK rearrangement status, extracranial metastasis, performance status and imaging variables of brain metastasis were analysed using descriptive analysis [chi-square test (χ2)], univariate and multivariate logistic regression analysis assuming 95% confidence interval (CI). In this study of 117 patients, the analysis by semantic method showed 79.2% of the patients belonged to ALK positive were non-smokers as compared to double negative groups (P = 0.03). There was a 10-fold increase in ALK positivity as compared to EGFR positivity in ring enhancing lesions patients (P = 0.015) and there was also a 6.4-fold increase in ALK positivity as compared to double negative groups in meningeal involvement patients (P = 0.004). Using CNN Efficient Net DL model, the study achieved 76% accuracy in classifying ALK rearrangement and EGFR mutations without manual segmentation of metastatic lesions. Analysis of the manually segmented dataset resulted in improved accuracy of 89% through this model. Both semantic features and DL model showed comparable accuracy in classifying EGFR mutation and ALK rearrangement. Both methods can be clinically used to predict mutation status while biopsy or genetic testing is undertaken.

Using Radiomics to Differentiate Brain Metastases From Lung Cancer Versus Breast Cancer, Including Predicting Epidermal Growth Factor Receptor and human Epidermal Growth Factor Receptor 2 Status.

We evaluated the feasibility of using multiregional radiomics to identify brain metastasis (BM) originating from lung adenocarcinoma (LA) and breast cancer (BC) and assess the epidermal growth factor receptor (EGFR) mutation and human epidermal growth factor receptor 2 (HER2) status. Our experiment included 160 patients with BM originating from LA (n = 70), BC (n = 67), and other tumor types (n = 23), between November 2017 and December 2021. All patients underwent contrast-enhanced T1- and T2-weighted magnetic resonance imaging (MRI) scans. A total of 1967 quantitative MRI features were calculated from the tumoral active area and peritumoral edema area and selected using least absolute shrinkage and selection operator regression with 5-fold cross-validation. We constructed radiomic signatures (RSs) based on the most predictive features for preoperative assessment of the metastatic origins, EGFR mutation, and HER2 status. Prediction performance of the constructed RSs was evaluated based on the receiver operating characteristic curve analysis. The developed multiregion RSs generated good area under the receiver operating characteristic curve (AUC) for identifying the LA and BC origin in the training (AUCs, RS-LA vs RS-BC, 0.767 vs 0.898) and validation (AUCs, RS-LA vs RS-BC, 0.778 and 0.843) cohort and for predicting the EGFR and HER2 status in the training (AUCs, RS-EGFR vs RS-HER2, 0.837 vs 0.894) and validation (AUCs, RS-EGFR vs RS-HER2, 0.729 vs 0.784) cohorts. Our results revealed associations between brain MRI-based radiomics and their metastatic origins, EGFR mutations, and HER2 status. The developed multiregion combined RSs may be considered noninvasive predictive markers for planning early treatment for BM patients.

Tumor-liver interface in MRI of liver metastasis enables prediction of EGFR mutation in patients with lung cancer: A proof-of-concept study.

Preoperative prediction of the epidermal growth factor receptor (EGFR) status in non-small-cell lung cancer (NSCLC) patients with liver metastasis (LM) may have potential clinical values for assisting in treatment decision-making. To explore the value of tumor-liver interface (TLI)-based magnetic resonance imaging (MRI) radiomics for detecting the EGFR mutation in NSCLC patients with LM. This retrospective study included 123 and 44 patients from hospital 1 (between Feb. 2018 and Dec. 2021) and hospital 2 (between Nov. 2015 and Aug. 2022), respectively. The patients received contrast-enhanced T1-weighted (CET1) and T2-weighted (T2W) liver MRI scans before treatment. Radiomics features were extracted from MRI images of TLI and the whole tumor region, separately. The least absolute shrinkage and selection operator (LASSO) regression was used to screen the features and establish radiomics signatures (RSs) based on TLI (RS-TLI) and the whole tumor (RS-W). The RSs were evaluated by the receiver operating characteristic (ROC) curve analysis. A total of 5 and 6 features were identified highly correlated with the EGFR mutation status from TLI and the whole tumor, respectively. The RS-TLI showed better prediction performance than RS-W in the training (AUCs, RS-TLI vs. RS-W, 0.842vs. 0.797), internal validation (AUCs, RS-TLI vs. RS-W, 0.771vs. 0.676) and external validation (AUCs, RS-TLI vs. RS-W, 0.733vs. 0.679) cohort. Our study demonstrated that TLI-based radiomics can improve prediction performance of the EGFR mutation in lung cancer patients with LM. The established multi-parametric MRI radiomics models may be used as new markers that can potentially assist in personalized treatment planning.

Efficacy of post‑mastectomy radiotherapy in patients with T1‑2N1 breast cancer aged ≤35years or with a positive HER‑2 status.

Post-mastectomy radiotherapy (PMRT) is highly recommended for patients with breast cancer with one to three positive nodes; however, there remains some controversy regarding its use. The present retrospective study aimed to explore which patients may be able to avoid PMRT and its associated side effects. A total of 728 patients with T1-2N1 breast cancer who were treated with or without PMRT were included in the present study. The results suggested that PMRT significantly decreased the locoregional recurrence rate (LRR) [hazard ratio (HR)=5.602, 95% confidence interval (CI)=3.139-9.998, P<0.01; 3-year LRR: 4 vs. 17%] and improved overall survival (OS) (HR=0.651, 95% CI=0.437-0.971, P=0.03; 3-year OS: 91 vs. 87%) for patients with T1-2N1 breast cancer. By contrast, PMRT had no significant effect on the distant metastasis (DM) rate (HR=0.691, 95% CI=0.468-1.019, P=0.06; 3-year DM: 10 vs. 15%). Further stratified analysis revealed that PMRT did not reduce the LRR and DM, or improve OS in patients aged ≤35 years or in those with a positive human epidermal growth factor receptor-2 (HER-2) status. The analysis of 438 patients treated with PMRT revealed that patients aged ≤35 years or those with a positive HER-2 status were more likely to experience local recurrence even following PMRT. Thus, the benefits of using PMRT in patients with T1-2N1 breast cancer who are aged ≤35 years or in those with a positive HER-2 status need to be carefully considered. Further studies are required to confirm whether this patient group may be exempted from PMRT.

HER2-low breast cancer brain metastases: Incidence and treatment implications.

2035 Background: Brain metastases (BrM) are a major cause of morbidity and mortality among women with breast cancer (BC). Central nervous system (CNS)-penetrating systemic therapies for patients with HER2-negative BrM are lacking; this is particularly problematic for patients with triple negative disease (TNBC) who have a high likelihood of developing BrM. Given CNS activity of trastuzumab deruxtecan, efficacy for patients with HER2-low BrM is of interest. Methods: A retrospective study of two cohorts of patients who underwent surgery for BC BrM at Sunnybrook Health Sciences Centre between 1999-2013 and 2008-2018 were identified. Estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2 (HER2) status were assessed based on 2018 ASCO/CAP guidelines. HER2-zero was defined as immunohistochemistry (IHC) 0; HER2-low was defined as IHC 1+ or IHC 2+ with fluorescence in situ hybridization (FISH) negative status. HER2-positive was defined as IHC 3+ or IHC 2+ with positive FISH. Clinicopathological features were recorded. We also assessed the prognostic association between extent of HER2 expression and i) brain-specific progression free survival (bsPFS), as well as ii) overall survival (OS). Results: Out of 137 patients with resected BrM, tissue for HER2 assessment was available in 74.5% (n=102) of cases. In this cohort, the median age at BrM diagnosis was 53.5 (range, 32-85). 18.6% (n=19) had leptomeningeal disease and 68.6% (n=70) had extracranial disease. 53% (n=54) of the BrM were HER2-positive; 29.4% (n=30) were HER2-low and 17.6% (n=18) had HER2-zero status. Among BrM that were triple negative based on ASCO/CAP guidelines, 14 out of 22 cases (63.6%) were re-classified as being HER2-low. 15/25 (60%) BrM that were hormone receptor positive/HER2 negative (HR+/HER2-) based on ASCO/CAP guidelines were re-classified as being HER2-low. In total, 51 patients had matched primary breast and BrM tissue available; results of HER2 status when categorized as HER2-zero, HER2-low and HER2-positive were concordant in 82.3% (n= 42/51) of cases (Cohen’s kappa 0.58, p=0.0719). In 7 cases, the primary breast tissue was HER2-zero whereas the BrM was either HER2-low (n=5) or HER2-positive (n=2). In only one case (2%), expression of HER2 was lower in the BrM (HER2-low) compared to the primary BC (HER2-positive). Median time from primary BC to the development of BrM was 35 months (IQR, 14-69) in the overall cohort; patients with HER2-zero BrM had a numerically longer time to development of BrM (45.8 months), compared to those with HER2-low (35 months) and HER2-positive (35 months) BrM (p=0.948). There was no significant association between HER2-zero, HER2-low and HER2-positive status in BrM and either bsPFS or OS. Conclusions: Among patients with surgically resected BrM, a high proportion of those with metastatic TNBC and HR+/HER2-negative disease have “HER2-low” BrM with potential to benefit from HER2-targeted therapy.

The Utility of Quantitative Parameters of Shear-Wave Elastography to Predict Prognostic Histologic Features of Breast Cancer.

In this study, we aimed to investigate the correlation of stiffness values of shear-wave elastography (SWE) and histopathological prognostic factors in patients with breast cancer. Between January 2021 and June 2022, SWE images of 138 core-biopsy proven breast cancer lesions from 132 patients were retrospectively reviewed. Histopathogic prognostic factors, including tumor size, histologic grade, histologic type, hormone receptor positivity, human epidermal growth factor receptor (HER2) status, immunohistochemical subtype and Ki-67 index were documented. Elasticity values including mean and maximum elasticity ( Emean and Emax ) and lesion-to-fat ratio ( Eratio ) were recorded. The association between histopathological prognostic factors and elasticity values were assessed using Mann-Whitney U and Kruskal-Wallis test, and multiple linear regression analysis. Tumor size, histological grade, and Ki-67 index were significantly associated with the Eratio ( P < 0.05). Larger tumor size and higher Ki-67 index also showed significantly higher Emean and Emax values ( P < 0.05). However, hormone receptor positivity, HER2 status, and immunohistochemical subtype were not significantly associated with elasticity values ( P > 0.05). Multivariate logistic regression analysis revealed that tumor size was significantly associated with Emean , Emax , and Eratio values ( P < 0.05). A high Ki-67 index was also significantly associated with high Eratio values. Larger tumor size and higher Ki-67 index are independently associated with high Eratio values. Preoperative SWE may improve the performance of conventional ultrasound in predicting prognosis and treatment planning.