Back

Blood immunomap for prediction of responses to aPD1 immunotherapy in metastatic non-small cell lung cancer

Semitekolou, M.; Paschalidis, N.; Lo Tartaro, D.; Tsitsopoulou, A.; Stamou, P.; Mavroudis, A.; Markaki, E.; Varveri, A.; Morianos, I.; Lavigne, M.; Fotsitzoudis, C.; Magkouta, S.; Dede, K.; Kalomenidis, I.; Samitas, K.; Potaris, K.; Cossarizza, A.; Mavroudis, D.; De Biasi, S.; Verginis, P.

2024-08-28 oncology
10.1101/2024.08.27.24312529 medRxiv
Show abstract

Immune checkpoint inhibitor immunotherapy has revolutionized the treatment of non-small cell lung cancer (NSCLC). Despite the immense success, still a significant proportion of patients do not develop durable responses, allowing disease progression accompanied by high mortality rates. Therefore, there is an imperative need for identification of reliable non-invasive predictive biomarkers to guide therapeutic decisions. Herein, we constructed a blood immunomap in NSCLC patients with metastatic disease, using a high-dimensional mass cytometry approach. Assessment of clinical responses to aPD1 immunotherapy revealed, among others, a significant expansion of CD8+PD-L1+ T cells in individuals not responding to immunotherapy. Of interest, CD8+PD-L1+ T cells were enriched in tumor biopsies and bronchoalveolar lavage of NSCLC individuals at early stages of disease as well as in pleural infusions of individuals with thoracic malignancies. Transcriptomic analysis revealed that CD8+PD-L1+ T cells exhibited a regulatory/exhausted phenotype, while various transcripts associated with the overall survival of NSCLC individuals, were mapped. Overall, our findings define an immunomap in the early stage and advanced NSCLC patients and identify immune-related events which may benefit the quest for identification of predictive biomarkers of immunotherapy responses.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Cancer Cell
38 papers in training set
Top 0.1%
26.4%
2
Nature Communications
4913 papers in training set
Top 25%
7.0%
3
Journal of Hematology & Oncology
10 papers in training set
Top 0.1%
5.0%
4
iScience
1063 papers in training set
Top 3%
4.0%
5
Cell Reports
1338 papers in training set
Top 14%
3.7%
6
Theranostics
33 papers in training set
Top 0.2%
3.7%
7
Frontiers in Immunology
586 papers in training set
Top 2%
3.7%
50% of probability mass above
8
Cancer Immunology Research
34 papers in training set
Top 0.1%
3.3%
9
eLife
5422 papers in training set
Top 29%
3.1%
10
Journal of Clinical Investigation
164 papers in training set
Top 1%
2.9%
11
Cell Reports Medicine
140 papers in training set
Top 2%
2.8%
12
Journal for ImmunoTherapy of Cancer
64 papers in training set
Top 0.5%
1.9%
13
Signal Transduction and Targeted Therapy
29 papers in training set
Top 0.5%
1.9%
14
Cancer Letters
32 papers in training set
Top 0.3%
1.5%
15
Molecular Cancer
14 papers in training set
Top 0.4%
1.5%
16
Journal of Experimental & Clinical Cancer Research
25 papers in training set
Top 0.1%
1.3%
17
Cell Genomics
162 papers in training set
Top 5%
1.0%
18
Scientific Reports
3102 papers in training set
Top 70%
0.9%
19
Clinical and Translational Medicine
30 papers in training set
Top 0.7%
0.9%
20
EMBO Molecular Medicine
85 papers in training set
Top 3%
0.9%
21
European Journal of Cancer
10 papers in training set
Top 0.4%
0.8%
22
Clinical Cancer Research
58 papers in training set
Top 2%
0.8%
23
Cancers
200 papers in training set
Top 4%
0.8%
24
JNCI: Journal of the National Cancer Institute
16 papers in training set
Top 0.7%
0.8%
25
Cell Discovery
54 papers in training set
Top 5%
0.8%
26
Cancer Immunology, Immunotherapy
11 papers in training set
Top 0.3%
0.8%
27
PLOS ONE
4510 papers in training set
Top 67%
0.8%
28
Frontiers in Oncology
95 papers in training set
Top 4%
0.7%
29
Journal of Translational Medicine
46 papers in training set
Top 3%
0.7%
30
Cancer Research Communications
46 papers in training set
Top 1%
0.7%