The artificial intelligence and machine learning in lung cancer immunotherapy

Q Gao, L Yang, M Lu, R Jin, H Ye, T Ma - Journal of Hematology & …, 2023 - Springer
Since the past decades, more lung cancer patients have been experiencing lasting benefits
from immunotherapy. It is imperative to accurately and intelligently select appropriate …

Tumor infiltrating lymphocytes across breast cancer subtypes: current issues for biomarker assessment

C Valenza, B Taurelli Salimbeni, C Santoro, D Trapani… - Cancers, 2023 - mdpi.com
Simple Summary Tumor-infiltrating lymphocytes (TILs) are immune cells that can be
involved in the anti-tumor response and are presently viewed as a promising, inexpensive …

Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions

W Lotter, MJ Hassett, N Schultz, KL Kehl, EM Van Allen… - Cancer Discovery, 2024 - AACR
Artificial intelligence (AI) in oncology is advancing beyond algorithm development to
integration into clinical practice. This review describes the current state of the field, with a …

Artificial intelligence: illuminating the depths of the tumor microenvironment

T Xie, A Huang, H Yan, X Ju, L Xiang… - Journal of Translational …, 2024 - Springer
Artificial intelligence (AI) can acquire characteristics that are not yet known to humans
through extensive learning, enabling to handle large amounts of pathology image data …

Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma …

E Chatziioannou, J Roßner, TN Aung, DL Rimm… - …, 2023 - thelancet.com
Background Recent advances in digital pathology have enabled accurate and standardised
enumeration of tumour-infiltrating lymphocytes (TILs). Here, we aim to evaluate TILs as a …

Clinical and Molecular Features of Long-term Response to Immune Checkpoint Inhibitors in Patients with Advanced Non–Small Cell Lung Cancer

R Thummalapalli, B Ricciuti, C Bandlamudi… - Clinical Cancer …, 2023 - AACR
Purpose: We sought to identify features of patients with advanced non–small cell lung
cancer (NSCLC) who achieve long-term response (LTR) to immune checkpoint inhibitors …

Biomarkers for immune checkpoint inhibitor response in NSCLC: current developments and applicability

K Tostes, AP Siqueira, RM Reis, LF Leal… - International Journal of …, 2023 - mdpi.com
Lung cancer has the highest mortality rate among all cancer types, resulting in over 1.8
million deaths annually. Immunotherapy utilizing immune checkpoint inhibitors (ICIs) has …

Obesity-dependent selection of driver mutations in cancer

C Tang, VJ Castillon, M Waters, C Fong, T Park… - Nature Genetics, 2024 - nature.com
Obesity is a risk factor for cancer, but whether obesity is linked to specific genomic subtypes
of cancer is unknown. We examined the relationship between obesity and tumor genotype in …

Cancer biomarkers: Emerging trends and clinical implications for personalized treatment

A Passaro, M Al Bakir, EG Hamilton, M Diehn, F André… - Cell, 2024 - cell.com
The integration of cancer biomarkers into oncology has revolutionized cancer treatment,
yielding remarkable advancements in cancer therapeutics and the prognosis of cancer …

Deep pathomics: A new image-based tool for predicting response to treatment in stage III non-small cell lung cancer

L Nibid, C Greco, E Cordelli, G Sabarese, M Fiore… - Plos one, 2023 - journals.plos.org
Despite the advantages offered by personalized treatments, there is presently no way to
predict response to chemoradiotherapy in patients with non-small cell lung cancer (NSCLC) …