The effect of pain on survival in non-small cell lung cancer (NSCLC) patients with bone metastases receiving chemotherapy

2008 ◽  
Vol 26 (15_suppl) ◽  
pp. 20666-20666
Author(s):  
K. Yoh ◽  
K. Kubota ◽  
H. Ohmatsu ◽  
K. Goto ◽  
S. Niho ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Bone Metastases ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Nsclc Patients

RB1 mutation had influenced on bone metastases in advanced treatment-naïve lung cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e21668-e21668
Author(s):  
Chengzhi Zhou ◽  
Ying Xu ◽  
Xinqing Lin ◽  
Fei Wang ◽  
Huojin Deng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Bone Metastases ◽  
Cell Lung Cancer ◽  
Suppressor Gene ◽  
Small Cell ◽  
Small Cell Lung ◽  
Treatment Naïve ◽  
Cancer Types ◽  
Nsclc Patients

e21668 Background: RB1 is one of the most vital cancer suppressor genes in various cancer types. RB1 mutation always occurs in treatment-naïve small cell lung cancer (SCLC) patients or in resistance to EGFR TKI therapy of non-small cell lung cancer (NSCLC) patients. However, we observed a group of clinical NSCLC patients, and found that RB1 mutations also occurred in treatment-naïve patients. Methods: RB1 is one of the most vital cancer suppressor genes in various cancer types. RB1 mutation always occurs in treatment-naïve small cell lung cancer (SCLC) patients or in resistance to EGFR TKI therapy of non-small cell lung cancer (NSCLC) patients. However, we observed a group of clinical NSCLC patients, and found that RB1 mutations also occurred in treatment-naïve patients. Results: Nonsense and frame-shift mutations were the major pathogenic mutations found in RB1 gene, which predicted RB1 protein-deficient in these mutational patients. Furthermore, we found these RB1 mutation patients had TP53 mutations at the same time. Patients with RB1 mutation had a higher smoking prevalence than patients who had wildtype RB1 genes (P < 0.0001). Gene testing showed RB1 mutations patients also developed EGFR driver mutations, while the mutation frequency was significantly lower than RB1 wildtype patients ( P = 0.0368). Eight RB1 mutated patients diagnosed with actionable EGFR mutations, including exon 19 del, L858R, L861Q, G719S and S768I, while no patients diagnosed with EGFR exon 20 insertion. 10 (62.5%, 10/16) patients in RB1 mutated group, and 25(32.1%, 25/78) patients with RB1 wildtype had bone metastases. The proportion of bone metastases in patients with RB1 mutation was significantly increased than others ( P = 0.0216). Conclusions: This study demonstrates that the function of tumor suppressor gene RB1 in advanced stage of NSCLC. From the results, we considered RB1 mutation had influence on bone metastases. Although loss-of-function mutations in tumor suppressor gene (TSG) RB1 always had no targets therapeutic drugs, it also suggested that some other clinically treatment can be performed as soon as possible.

scholarly journals An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhangheng Huang ◽  
Chuan Hu ◽  
Changxing Chi ◽  
Zhe Jiang ◽  
Yuexin Tong ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Lung Cancer ◽  
Survival Rate ◽  
Small Cell Lung Cancer ◽  
Bone Metastases ◽  
Cell Lung Cancer ◽  
Predictive Models ◽  
Small Cell ◽  
Small Cell Lung ◽  
Nsclc Patients

Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall survival for these patients is usually perishing. However, a model with high accuracy for predicting the survival of NSCLC with BM is still lacking. Here, we aimed to establish a model based on artificial intelligence for predicting the 1-year survival rate of NSCLC with BM by using extreme gradient boosting (XGBoost), a large-scale machine learning algorithm. We selected NSCLC patients with BM between 2010 and 2015 from the Surveillance, Epidemiology, and End Results database. In total, 5973 cases were enrolled and divided into the training (n=4183) and validation (n=1790) sets. XGBoost, random forest, support vector machine, and logistic algorithms were used to generate predictive models. Receiver operating characteristic curves were used to evaluate and compare the predictive performance of each model. The parameters including tumor size, age, race, sex, primary site, histological subtype, grade, laterality, T stage, N stage, surgery, radiotherapy, chemotherapy, distant metastases to other sites (lung, brain, and liver), and marital status were selected to construct all predictive models. The XGBoost model had a better performance in both training and validation sets as compared with other models in terms of accuracy. Our data suggested that the XGBoost model is the most precise and personalized tool for predicting the 1-year survival rate for NSCLC patients with BM. This model can help the clinicians to design more rational and effective therapeutic strategies.

scholarly journals Biomarkers and Gene Signatures to Predict Durable Response to Pembrolizumab in Non-Small Cell Lung Cancer

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3828
Author(s):  
Anello Marcello Poma ◽  
Rossella Bruno ◽  
Iacopo Pietrini ◽  
Greta Alì ◽  
Giulia Pasquini ◽  
...  
Keyword(s):  
Lung Cancer ◽  
T Cells ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Immune Cell ◽  
Small Cell ◽  
Small Cell Lung ◽  
First Line ◽  
Durable Response ◽  
Nsclc Patients

Pembrolizumab has been approved as first-line treatment for advanced Non-small cell lung cancer (NSCLC) patients with tumors expressing PD-L1 and in the absence of other targetable alterations. However, not all patients that meet these criteria have a durable benefit. In this monocentric study, we aimed at refining the selection of patients based on the expression of immune genes. Forty-six consecutive advanced NSCLC patients treated with pembrolizumab in first-line setting were enrolled. The expression levels of 770 genes involved in the regulation of the immune system was analysed by the nanoString system. PD-L1 expression was evaluated by immunohistochemistry. Patients with durable clinical benefit had a greater infiltration of cytotoxic cells, exhausted CD8, B-cells, CD45, T-cells, CD8 T-cells and NK cells. Immune cell scores such as CD8 T-cell and NK cell were good predictors of durable response with an AUC of 0.82. Among the immune cell markers, XCL1/2 showed the better performance in predicting durable benefit to pembrolizumab, with an AUC of 0.85. Additionally, CD8A, CD8B and EOMES showed a high specificity (>0.86) in identifying patients with a good response to treatment. In the same series, PD-L1 expression levels had an AUC of 0.61. The characterization of tumor microenvironment, even with the use of single markers, can improve patients’ selection for pembrolizumab treatment.

scholarly journals Circulating Biomarkers of Response and Toxicity of Immunotherapy in Advanced Non-Small Cell Lung Cancer (NSCLC): A Comprehensive Review

Cancers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1794
Author(s):  
Alice Indini ◽  
Erika Rijavec ◽  
Francesco Grossi
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Liquid Biopsy ◽  
Cytotoxic T Lymphocyte ◽  
Checkpoint Inhibitors ◽  
Small Cell ◽  
Circulating Biomarkers ◽  
Small Cell Lung ◽  
Nsclc Patients

Immune checkpoint inhibitors (ICIs) targeting the programmed cell death (PD)-1 protein and its ligand, PD-L1, and cytotoxic T-lymphocyte-associated antigen (CTLA)-4, have revolutionized the management of patients with advanced non-small cell lung cancer (NSCLC). Unfortunately, only a small portion of NSCLC patients respond to these agents. Furthermore, although immunotherapy is usually well tolerated, some patients experience severe immune-related adverse events (irAEs). Liquid biopsy is a non-invasive diagnostic procedure involving the isolation of circulating biomarkers, such as circulating tumor cells (CTC), cell-free DNA (cfDNA), and microRNAs (miRNAs). Thanks to recent advances in technologies, such as next-generation sequencing (NGS) and digital polymerase chain reaction (dPCR), liquid biopsy has become a useful tool to provide baseline information on the tumor, and to monitor response to treatments. This review highlights the potential role of liquid biomarkers in the selection of NSCLC patients who could respond to immunotherapy, and in the identification of patients who are most likely to experience irAEs, in order to guide improvements in care.

scholarly journals 1318P Association between soluble PD-L1 and prognosis of non-small cell lung cancer (NSCLC) patients treated with immunotherapy

2020 ◽  
Vol 31 ◽  
pp. S851
Author(s):  
C. Dellepiane ◽  
S. Coco ◽  
M.G. Dal Bello ◽  
G. Rossi ◽  
E. Rijavec ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Nsclc Patients

scholarly journals Molecular profile of KRAS G12C-mutant colorectal and non-small-cell lung cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Luiz Henrique Araujo ◽  
Bianca Mendes Souza ◽  
Laura Rabelo Leite ◽  
Sabrina A. F. Parma ◽  
Natália P. Lopes ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Driver Mutations ◽  
Molecular Profile ◽  
Common Mutation ◽  
Small Cell Lung ◽  
The South ◽  
Nsclc Patients

Abstract Background KRAS is the most frequently mutated oncogene in cancer, however efforts to develop targeted therapies have been largely unsuccessful. Recently, two small-molecule inhibitors, AMG 510 and MRTX849, have shown promising activity in KRAS G12C-mutant solid tumors. The current study aims to assess the molecular profile of KRAS G12C in colorectal (CRC) and non-small-cell lung cancer (NSCLC) tested in a clinical certified laboratory. Methods CRC and NSCLC samples submitted for KRAS testing between 2017 and 2019 were reviewed. CRC samples were tested for KRAS and NRAS by pyrosequencing, while NSCLC samples were submitted to next generation sequencing of KRAS, NRAS, EGFR, and BRAF. Results The dataset comprised 4897 CRC and 4686 NSCLC samples. Among CRC samples, KRAS was mutated in 2354 (48.1%). Most frequent codon 12 mutations were G12D in 731 samples (14.9%) and G12V in 522 (10.7%), followed by G12C in 167 (3.4%). KRAS mutations were more frequent in females than males (p = 0.003), however this difference was exclusive of non-G12C mutants (p < 0.001). KRAS mutation frequency was lower in the South and North regions (p = 0.003), but again KRAS G12C did not differ significantly (p = 0.80). In NSCLC, KRAS mutations were found in 1004 samples (21.4%). As opposed to CRC samples, G12C was the most common mutation in KRAS, in 346 cases (7.4%). The frequency of KRAS G12C was higher in the South and Southeast regions (p = 0.012), and lower in patients younger than 50 years (p < 0.001). KRAS G12C mutations were largely mutually exclusive with other driver mutations; only 11 NSCLC (3.2%) and 1 CRC (0.6%) cases had relevant co-mutations. Conclusions KRAS G12C presents in frequencies higher than several other driver mutations, and may represent a large volume of patients in absolute numbers. KRAS testing should be considered in all CRC and NSCLC patients, independently of clinical or demographic characteristics.

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