Tumor infiltrating lymphocytes in lung cancer: a new prognostic parameter

Reynders, Kobe; Ruysscher, Dirk De

doi:10.21037/jtd.2016.07.75

Cited by 27 publications

(18 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, tracer accumulation is attributed to T-cell infiltration into the tumor, yet tumor cells do not display PD-1 expression. The process of tumor infiltration by lymphocytes has been extensively documented and this type of study may provide additional data regarding the process [32]. Using PBL mice injected with 89 Zr-Df-IgG, we verified that the accumulation of our novel tracer was highly specific and not due to off-target accumulation (Fig.…”

Section: Discussionsupporting

confidence: 61%

89Zr-labeled nivolumab for imaging of T-cell infiltration in a humanized murine model of lung cancer

England

Jiang

Ehlerding

et al. 2017

Eur J Nucl Med Mol Imaging

107

View full text Add to dashboard Cite

show abstract

Section: Discussionsupporting

confidence: 61%

89Zr-labeled nivolumab for imaging of T-cell infiltration in a humanized murine model of lung cancer

England

Jiang

Ehlerding

et al. 2017

Eur J Nucl Med Mol Imaging

107

View full text Add to dashboard Cite

show abstract

“…In our study, TIL density was found to be correlated with a peritumoral Gabor feature from the first annular ring. Previous studies have reported an overexpression of TILs in patients who have responded to immunotherapy (59)(60)(61). Gabor features from outside the nodule had a higher expression in adenocarcinomas as compared with granulomas: H&E images showed densely packed TILs and tumor-associated macrophages (20).…”

Section: Discussionmentioning

confidence: 86%

Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in Non–Small Cell Lung Cancer

Khorrami

Prasanna

Gupta

et al. 2020

Cancer Immunology Research

220

184

View full text Add to dashboard Cite

No predictive biomarkers can robustly identify patients with non-small cell lung cancer (NSCLC) who will benefit from immune checkpoint inhibitor (ICI) therapies. Here, in a machine learning setting, we compared changes ("delta") in the radiomic texture (DelRADx) of CT patterns both within and outside tumor nodules before and after two to three cycles of ICI therapy. We found that DelRADx patterns could predict response to ICI therapy and overall survival (OS) for patients with NSCLC. We retrospectively analyzed data acquired from 139 patients with NSCLC at two institutions, who were divided into a discovery set (D 1 ¼ 50) and two independent validation sets (D 2 ¼ 62, D 3 ¼ 27). Intranodular and perinodular texture descriptors were extracted, and the relative differences were computed. A linear discriminant analysis (LDA) classifier was trained with 8 Del-RADx features to predict RECIST-derived response. Association of delta-radiomic risk score (DRS) with OS was determined. The association of DelRADx features with tumor-infiltrating lymphocyte (TIL) density on the diagnostic biopsies (n ¼ 36) was also evaluated. The LDA classifier yielded an AUC of 0.88 AE 0.08 in distinguishing responders from nonresponders in D 1 , and 0.85 and 0.81 in D 2 and D 3. DRS was associated with OS [HR: 1.64; 95% confidence interval (CI), 1.22-2.21; P ¼ 0.0011; C-index ¼ 0.72). Peritumoral Gabor features were associated with the density of TILs on diagnostic biopsy samples. Our results show that DelRADx could be used to identify early functional responses in patients with NSCLC.

show abstract

“…Increased tumour-infiltrating lymphocytes and a higher CD4 + :CD8 + T cell ratio are associated with a favourable prognosis and survival 219,220 . Forkhead box P3 (FOXP3) + regulatory T (T reg ) cells and intratumoural cyclooxygenase 2 (COX2) expression were associated with worse recurrence-free survival in node-negative non-small-cell lung cancer (NSCLC) 221 .…”

Section: Fig 1 |mentioning

confidence: 99%

The lung microenvironment: an important regulator of tumour growth and metastasis

et al. 2018

View full text Add to dashboard Cite

Lung cancer is a major global health problem, as it is the leading cause of cancer-related deaths worldwide. Major advances in the identification of key mutational alterations have led to the development of molecularly targeted therapies, whose efficacy has been limited by emergence of resistance mechanisms. US Food and Drug Administration (FDA)-approved therapies targeting angiogenesis and more recently immune checkpoints have reinvigorated enthusiasm in elucidating the prognostic and pathophysiological roles of the tumour microenvironment in lung cancer. In this Review, we highlight recent advances and emerging concepts for how the tumour-reprogrammed lung microenvironment promotes both primary lung tumours and lung metastasis from extrapulmonary neoplasms by contributing to inflammation, angiogenesis, immune modulation and response to therapies. We also discuss the potential of understanding tumour microenvironmental processes to identify biomarkers of clinical utility and to develop novel targeted therapies against lung cancer.

show abstract

Tumor infiltrating lymphocytes in lung cancer: a new prognostic parameter

Cited by 27 publications

References 20 publications

89Zr-labeled nivolumab for imaging of T-cell infiltration in a humanized murine model of lung cancer

89Zr-labeled nivolumab for imaging of T-cell infiltration in a humanized murine model of lung cancer

Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in Non–Small Cell Lung Cancer

The lung microenvironment: an important regulator of tumour growth and metastasis

Contact Info

Product

Resources

About