Predicting programmed death-ligand 1 (PD-L1) expression with fluorine-18 fluorodeoxyglucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) metabolic parameters in resectable non-small cell lung cancer.

BACKGROUND: Programmed death-ligand 1 (PD-L1) expression is a predictive biomarker for immunotherapy in non-small cell lung cancer (NSCLC). PD-L1 and glucose transporter 1 expression are closely associated, and studies demonstrate correlation of PD-L1 with glucose metabolism. AIM: The aim of this study was to investigate the association of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) metabolic parameters with PD-L1 expression in primary lung tumour and lymph node metastases in resected NSCLC. METHODS: We conducted a retrospective analysis of 210 patients with node-positive resectable stage IIB-IIIB NSCLC. PD-L1 tumour proportion score (TPS) was determined using the DAKO 22C3 immunohistochemical assay. Semi-automated techniques were used to analyse pre-operative [18F]FDG-PET/CT images to determine primary and nodal metabolic parameter scores (including max, mean, peak and peak adjusted for lean body mass standardised uptake values (SUV), metabolic tumour volume (MTV), total lesional glycolysis (TLG) and SUV heterogeneity index (HISUV)). RESULTS: Patients were predominantly male (57%), median age 70 years with non-squamous NSCLC (68%). A majority had negative primary tumour PD-L1 (TPS < 1%; 53%). Mean SUVmax, SUVmean, SUVpeak and SULpeak values were significantly higher (p < 0.05) in those with TPS ≥ 1% in primary tumour (n = 210) or lymph nodes (n = 91). However, ROC analysis demonstrated only moderate separability at the 1% PD-L1 TPS threshold (AUCs 0.58-0.73). There was no association of MTV, TLG and HISUV with PD-L1 TPS. CONCLUSION: This study demonstrated the association of SUV-based [18F]FDG-PET/CT metabolic parameters with PD-L1 expression in primary tumour or lymph node metastasis in resectable NSCLC, but with poor sensitivity and specificity for predicting PD-L1 positivity ≥ 1%. CLINICAL RELEVANCE STATEMENT: Whilst SUV-based fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography metabolic parameters may not predict programmed death-ligand 1 positivity ≥ 1% in the primary tumour and lymph nodes of resectable non-small cell lung cancer independently, there is a clear association which warrants further investigation in prospective studies. TRIAL REGISTRATION: Non-applicable KEY POINTS: • Programmed death-ligand 1 immunohistochemistry has a predictive role in non-small cell lung cancer immunotherapy; however, it is both heterogenous and dynamic. • SUV-based fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG-PET/CT) metabolic parameters were significantly higher in primary tumour or lymph node metastases with positive programmed death-ligand 1 expression. • These SUV-based parameters could potentially play an additive role along with other multi-modal biomarkers in selecting patients within a predictive nomogram.

Weakly supervised segmentation models as explainable radiological classifiers for lung tumour detection on CT images.

PURPOSE: Interpretability is essential for reliable convolutional neural network (CNN) image classifiers in radiological applications. We describe a weakly supervised segmentation model that learns to delineate the target object, trained with only image-level labels ("image contains object" or "image does not contain object"), presenting a different approach towards explainable object detectors for radiological imaging tasks. METHODS: A weakly supervised Unet architecture (WSUnet) was trained to learn lung tumour segmentation from image-level labelled data. WSUnet generates voxel probability maps with a Unet and then constructs an image-level prediction by global max-pooling, thereby facilitating image-level training. WSUnet's voxel-level predictions were compared to traditional model interpretation techniques (class activation mapping, integrated gradients and occlusion sensitivity) in CT data from three institutions (training/validation: n = 412; testing: n = 142). Methods were compared using voxel-level discrimination metrics and clinical value was assessed with a clinician preference survey on data from external institutions. RESULTS: Despite the absence of voxel-level labels in training, WSUnet's voxel-level predictions localised tumours precisely in both validation (precision: 0.77, 95% CI: [0.76-0.80]; dice: 0.43, 95% CI: [0.39-0.46]), and external testing (precision: 0.78, 95% CI: [0.76-0.81]; dice: 0.33, 95% CI: [0.32-0.35]). WSUnet's voxel-level discrimination outperformed the best comparator in validation (area under precision recall curve (AUPR): 0.55, 95% CI: [0.49-0.56] vs. 0.23, 95% CI: [0.21-0.25]) and testing (AUPR: 0.40, 95% CI: [0.38-0.41] vs. 0.36, 95% CI: [0.34-0.37]). Clinicians preferred WSUnet predictions in most instances (clinician preference rate: 0.72 95% CI: [0.68-0.77]). CONCLUSION: Weakly supervised segmentation is a viable approach by which explainable object detection models may be developed for medical imaging. CRITICAL RELEVANCE STATEMENT: WSUnet learns to segment images at voxel level, training only with image-level labels. A Unet backbone first generates a voxel-level probability map and then extracts the maximum voxel prediction as the image-level prediction. Thus, training uses only image-level annotations, reducing human workload. WSUnet's voxel-level predictions provide a causally verifiable explanation for its image-level prediction, improving interpretability. KEY POINTS: • Explainability and interpretability are essential for reliable medical image classifiers. • This study applies weakly supervised segmentation to generate explainable image classifiers. • The weakly supervised Unet inherently explains its image-level predictions at voxel level.

HER3 expression and MEK activation in non-small-cell lung carcinoma.

AIM: We explore HER3 expression in lung adenocarcinoma (adeno-NSCLC) and identify potential mechanisms of HER3 expression. MATERIALS & METHODS: Tumor samples from 45 patients with adeno-NSCLC were analyzed. HER3 and HER2 expression were identified using immunohistochemistry and bioinformatic interrogation of The Cancer Genome Atlas (TCGA). RESULTS: HER3 was highly expressed in 42.2% of cases. ERBB3 copy number did not account for HER3 overexpression. Bioinformatic analysis of TCGA demonstrated that MEK activity score (a surrogate of functional signaling) did not correlate with HER3 ligands. ERBB3 RNA expression levels were significantly correlated with MEK activity after adjusting for EGFR expression. CONCLUSION: HER3 expression is common and is a potential therapeutic target by virtue of frequent overexpression and functional downstream signaling.

Outcomes of systemic therapy for advanced triple-negative breast cancer: A single centre experience.

BACKGROUND: Prognosis is worse for advanced triple-negative breast cancer (aTNBC) compared to other disease subtypes. Trials describe treatment outcomes in single specified lines of therapy; but few data describe treatment outcomes across the whole treatment pathway, which is critical in determining when patients should be referred for trials and to inform discussion. We evaluated treatment outcomes for aTNBC (overall response rate [ORR], median progression-free survival [mPFS] and median overall survival [mOS]) in patients treated largely outside of clinical trials. METHODS: We retrospectively identified 268 patients diagnosed with aTNBC from 01/12/2011 to 30/11/2016 from our electronic records and recorded patients' and tumour characteristics and treatment outcomes. Chi-squared/Fishers exact test and Kaplan-Meier statistical methods were utilised. RESULTS: 186 patients treated with ≥1 line of systemic treatment were eligible and had median age of 55 (range 26-91). 53.8% had ECOG Performance Status 0 and 69.9% visceral involvement. 38.6% had disease-free interval (DFI)≤12 months following surgery or adjuvant chemotherapy completion and 14.0% had de-novo advanced disease. 11.4% carried a BRCA mutation. 64.5% received two lines of therapy, 37.6% three and 21.5% four. ORR and mPFS were 43.9% and 3.7 months for first-line therapy, 40.2% and 3.5 months for second-line, 28.8% and 2.5 months for third-line and 25.0% and 2.1 months for fourth-line. In first line, DFI>12 months was associated with higher ORR and longer PFS compared DFI ≤12 months. CONCLUSIONS: The observed response rates are consistent with literature. However, PFS is short, and early consideration of clinical trials can be justified in these patients.

New developments in metastatic prostate cancer therapy.

Metastatic prostate cancer is still commonly a lethal condition. The concept that 'men with prostate cancer die with rather than of their cancer' has been shown to be false. It is estimated that 10-20% of men in the UK present with locally advanced disease. Median overall survival remains only 3.5 years for men presenting with metastatic disease. The use of LHRH analogues to achieve medical castration has become the gold standard for both locally advanced prostate cancer, combined with radiotherapy, and metastatic disease. Androgen deprivation therapy (ADT) is the standard first-line treatment for advanced disease resulting in improvements in symptoms, radiological findings and PSA levels. Ultimately the majority of men with advanced prostate cancer will develop resistance to ADT Docetaxel is the standard first-line therapy recommended by international guidelines for patients with symptomatic metastatic castrate refractory prostate cancer who are suitable candidates for chemotherapy. More than 90% of patients with castrate refractory prostate cancer have bone metastases. Radium-223 dichloride is a novel alpha-emitting radiopharmaceutical agent, which mimics calcium and therefore targets bone metastases. It is indicated in patients with metastatic castrate refractory prostate cancer who have symptomatic bone metastases without visceral metastases.

Vitamin D deficiency in pregnancy - still a public health issue.

The objectives of this study were to quantify the prevalence of vitamin D insufficiency and deficiency in pregnancy, explore associated risk factors and discuss the public health implications. The study used retrospective analysis of randomly selected data. This is the first report on serum vitamin D levels in an unselected multi-ethnic population of pregnant women collected between April 2008 and March 2009. Women with sufficient stored serum were randomly selected from among all women who delivered between April 2008 and March 2009. Serum vitamin D levels were determined using liquid chromatography coupled to tandem mass spectrometry. Vitamin D levels were analysed with respect to ethnicity (marking skin tone), calendar quartile, body mass index (BMI), trimester and parity. Deficiency was defined as <25 nmol L(-1) , insufficiency 25-75 nmol L(-1) and adequacy >75 nmol L(-1) . Three hundred and forty-six women were included and represented the total population regarding skin tone, quartile, BMI, gestation and parity. Overall, 18% [95% confidence interval (CI): 15-23%] of sample women had adequate vitamin D levels; 36% were deficient, 45% insufficient. Among women with dark skin, only 8% (95% CI: 5-12%) had adequate levels compared with 43% (95% CI: 33-53%) of those with light skin. Obese women were found have significantly lower vitamin D levels than non-obese women. Vitamin D deficiency and insufficiency are prevalent year-round among pregnant women in North West London, especially those with darker skin. Existing supplementation guidelines should be supported; however, other measures are required to improve status among all women.