[200 Shengxin literatures] 96 joint biomarkers of immune checkpoint inhibitor response in advanced solid tumors

One 、 The article information

English title ：Genome and Transcriptome Biomarkers of Response to Immune Checkpoint Inhibitors in Advanced Solid Tumors

Chinese title ： Genomic and transcriptome biomarkers of immune checkpoint inhibitor response in advanced solid tumors

Periodical ：《Clin Cancer Res》

Influencing factors : 12.531 Time of publication : 2021 Jan 1

research field ： Solid tumor ; Immunosuppressants

Two 、 Literature review

problem ： Immune checkpoint inhibitors （ICI） Completely changed the treatment of solid tumors . However , For patients with advanced solid tumors , It is difficult to determine patient specificity .

Method ： Using genome-wide and transcriptome analysis （WGTA）, adopt BC Cancer Personalized tumor genomics project , from 98 Fresh tumor biopsies were characterized in a heterogeneous pan cancer cohort of patients with metastatic pretreatment disease .

Conclusion ： Tumor mutation load independent of mismatch repair status is the most predictive marker of progression time , But immune related CD8 T Cells and M1-M2 Macrophage ratio score is more predictive of overall survival .

3、 ... and 、 experimental result

1. high TMB It is related to the long duration of treatment

from 98 Of patients 20 Analyze tumor samples of different tumor types .

These two methods produce a strong correlation TMB value .

DCB Of patients overall TMB Not significantly higher than NCB In patients with .TMB Yes OS Is less predictive , And use the same TMB threshold , Exome derived counts are more effective than genomes .

2. The prediction of immune cell expression profile is right ICIs Reaction

Composition of tumor microenvironment , Will affect the patient's understanding of ICIs Reaction . The expression profile of immune cells varies according to the type of tumor .CD8 T cells ,M0 Macrophages and neutrophils have the highest variability . Cholangiocarcinoma shows the highest expression level of immune cells . And cholangiocarcinoma , Melanoma of skin （SKCM） and HNSCCs in CD8 T The expression level of cells is the highest .

DCB in CD8 T The median cell score is NCB More than twice that , Although the overall difference is not significant . Higher CD8 T Cell scores are associated with progression and overall survival .

M1 Macrophages have anti-tumor characteristics , contrary ,M2 Macrophages are thought to have the opposite effect ,M1 / M2 The proportion of macrophages has prognostic value in cancer .DCB and NCB Between patients M1-M2 Score difference ratio CD8 T Cell score is more obvious . And CD8 The scores are similar , high M1-M2 Macrophage scores were correlated with longer TTP and OS relevant .

3.CD274 The relationship between gene expression and response and survival is poor

CD274 The expression of is highest in lymphoma and thymic carcinoma . Lung cancer , Cholangiocarcinoma and SKCM It also shows CD274 High expression of . stay DCB in ,CD274 The median expression did not increase significantly .CD274 Patients with high expression TTP longer , But there is no difference in overall survival .

Although high CD274 expression , But it may not be the most responsive biomarker in the pan cancer environment .

4. Joint biomarker improvement ICI Prediction of reaction

Yes TMB,CD8 T Cell score ,M1-M2 Scoring and CD274 The expression level and some cancer factors were multivariable Cox Proportional risk model . high CD8 T Cell score and TMB Most predictable TTP.M1-M2 Score for OS The most effective prediction .

have DCB The sample ratio of has NCB Of the samples have more positive markers , But does not include CD274（ Lack of predictive value ）. Samples with more positive markers significantly improved TTP and OS.

5.ICI The landscape of resistance gene changes

Antigen presentation and JAK / STAT Genetic changes in signaling pathways are ICI Resistance mechanism .

DCB Group and NCB There is no difference in the proportion of changing samples between groups . However, all samples with biallelic changes belong to NCB Group , But there was no statistical significance . stay WGTA Before that ICIs Progress on 16 Among the patients , Biallelic loss exists only in previously shown DCB Of patients .

a NSCLC The patient is in WGTA On the basis of , Accept ICIs（dMMR, high TMB,CD8 T Cells and M1-M2 The score is high CD274 expression ）. No, DCB. After the treatment begins 135 The second biopsy of the growing supraclavicular mass was performed on day , Results show JAK1 and HLA-A There are biallelic frameshift mutations , Take another biopsy before treatment （ The liver ） None of them were found , This may represent right ICIs The mechanism of acquired drug resistance , Or exist ICI Drug resistant subclones of treatment choice , This highlights the importance of analyzing metastatic lesions .

Four 、 Conclusion

1. Exome and genome derived TMB There is a strong relationship between counts , There is little difference in the predicted value , by WGTA Its applicability in clinical trials provides further support .
2. The immune related markers are emphasized ICI The basic predictive value of the response .
3. It is generalized cancer ICI Treated tumors provide WTGA Data sets , And prove to include high TMB,CD8 Expression and M1-M2 The combination of biomarkers including macrophage scores can be predicted ICIs Upper TTP and OS.