Perspectives on Immunotherapy of Metastatic Colorectal Cancer

Dai, Yongjiu; Zhao, Wenhu; Yue, Lei; Dai, Xinzheng; Ding, Rong; Wu, Fan; Gu, Jian; Qian, Xiaofeng

doi:10.3389/fonc.2021.659964

Cited by 24 publications

(15 citation statements)

References 139 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More recently, immune checkpoint inhibitors (ICIs), working by blocking immunoinhibitory signals and enabling patients to induce an anti-tumor action, have also proven active in the treatment of mCRC [ 36 ]. ICIs targeting PD-1 are in fact highly effective in a selected mCRC patient population whose tumors display dMMR or MSI-H [ 37 ].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis

Russo¹,

Lallo²,

Munnia³

et al. 2022

Cancers

View full text Add to dashboard Cite

Tailored treatments for metastatic colorectal cancer (mCRC) have not yet completely evolved due to the variety in response to drugs. Therefore, artificial intelligence has been recently used to develop prognostic and predictive models of treatment response (either activity/efficacy or toxicity) to aid in clinical decision making. In this systematic review, we have examined the ability of learning methods to predict response to chemotherapy alone or combined with targeted therapy in mCRC patients by targeting specific narrative publications in Medline up to April 2022 to identify appropriate original scientific articles. After the literature search, 26 original articles met inclusion and exclusion criteria and were included in the study. Our results show that all investigations conducted on this field have provided generally promising results in predicting the response to therapy or toxic side-effects. By a meta-analytic approach we found that the overall weighted means of the area under the receiver operating characteristic (ROC) curve (AUC) were 0.90, 95% C.I. 0.80–0.95 and 0.83, 95% C.I. 0.74–0.89 in training and validation sets, respectively, indicating a good classification performance in discriminating response vs. non-response. The calculation of overall HR indicates that learning models have strong ability to predict improved survival. Lastly, the delta-radiomics and the 74 gene signatures were able to discriminate response vs. non-response by correctly identifying up to 99% of mCRC patients who were responders and up to 100% of patients who were non-responders. Specifically, when we evaluated the predictive models with tests reaching 80% sensitivity (SE) and 90% specificity (SP), the delta radiomics showed an SE of 99% and an SP of 94% in the training set and an SE of 85% and SP of 92 in the test set, whereas for the 74 gene signatures the SE was 97.6% and the SP 100% in the training set.

show abstract

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis

Russo¹,

Lallo²,

Munnia³

et al. 2022

Cancers

View full text Add to dashboard Cite

show abstract

“…Among global cancer cases, colorectal cancer (CRC) is ranked third in incidence and second in mortality, with an estimated more than 1.9 million new cases and 935,000 deaths worldwide in 2020 [ 1 ]. In addition to the high morbidity and mortality in CRC, it appears to be difficult to further advance traditional treatment options, such as surgery, chemotherapy, and radiotherapy [ 2 ]. Hence, there is a need to develop new treatment methods to improve the poor prognosis in patients with CRC [ 3 , 4 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Role of Ezrin/Radixin/Moesin in the Surface Localization of Programmed Cell Death Ligand-1 in Human Colon Adenocarcinoma LS180 Cells

et al. 2021

View full text Add to dashboard Cite

Programmed cell death ligand-1 (PD-L1), an immune checkpoint protein highly expressed on the cell surface in various cancer cell types, binds to programmed cell death-1 (PD-1), leading to T-cell dysfunction and tumor survival. Despite clinical successes of PD-1/PD-L1 blockade therapies, patients with colorectal cancer (CRC) receive little benefit because most cases respond poorly. Because high PD-L1 expression is associated with immune evasion and poor prognosis in CRC patients, identifying potential modulators for the plasma membrane localization of PD-L1 may represent a novel therapeutic strategy for enhancing the efficacy of PD-1/PD-L1 blockade therapies. Here, we investigated whether PD-L1 expression in human colorectal adenocarcinoma cells (LS180) is affected by ezrin/radixin/moesin (ERM), functioning as scaffold proteins that crosslink plasma membrane proteins with the actin cytoskeleton. We observed colocalization of PD-L1 with all three ERM proteins in the plasma membrane and detected interactions involving PD-L1, the three ERM proteins, and the actin cytoskeleton. Furthermore, gene silencing of ezrin and radixin, but not of moesin, substantially decreased the expression of PD-L1 on the cell surface without affecting its mRNA level. Thus, in LS180 cells, ezrin and radixin may function as scaffold proteins mediating the plasma membrane localization of PD-L1, possibly by post-translational modification.

show abstract

“…Even worse, the majority (>85%) of CRC patients with microsatellite instability-low (MSI-L) are not eligible for this therapy. Immunotherapy in combination with other conventional treatments, such as chemotherapy, radiotherapy, and targeted therapy are currently being tested in order to overcome these obstacles and to encompass a broader CRC population with better efficacy ( 125 ).…”

Section: Therapeutic Implications By Targeting Tmementioning

confidence: 99%

Tumor Microenvironment Shapes Colorectal Cancer Progression, Metastasis, and Treatment Responses

Chen

2022

Front. Med.

View full text Add to dashboard Cite

Colorectal cancer (CRC) is one of the most devastating diseases that accounts for numerous deaths worldwide. Tumor cell-autonomous pathways, such as the oncogenic signaling activation, significantly contribute to CRC progression and metastasis. Recent accumulating evidence suggests that the CRC microenvironment also profoundly promotes or represses this process. As the roles of the tumor microenvironment (TME) in CRC progression and metastasis is gradually uncovered, the importance of these non-cell-autonomous signaling pathways is appreciated. However, we are still at the beginning of this TME function exploring process. In this review, we summarize the current understanding of the TME in CRC progression and metastasis by focusing on the gut microbiota and host cellular and non-cellular components. We also briefly discuss TME-remodeling therapies in CRC.

show abstract

Perspectives on Immunotherapy of Metastatic Colorectal Cancer

Cited by 24 publications

References 139 publications

Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis

Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis

Role of Ezrin/Radixin/Moesin in the Surface Localization of Programmed Cell Death Ligand-1 in Human Colon Adenocarcinoma LS180 Cells

Tumor Microenvironment Shapes Colorectal Cancer Progression, Metastasis, and Treatment Responses

Contact Info

Product

Resources

About