Polygenic Risk Scores Associated with Tumor Immune Infiltration in Common Cancers

Choi, Jung Yoon; Kim, Jung Sun; Sung, Hwa Jung; Chen, Yu-Wei; Chen, Zhishan; Wen, Wanqing; Shu, Xiao‐Ou; Guo, Xingyi

doi:10.3390/cancers14225571

Cited by 3 publications

(2 citation statements)

References 54 publications

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“…This demonstrates how alterations in the tumor’s immune microenvironment can account for a patient’s favorable response to a specific treatment. In addition, germline genetic factors are important modifiers in tumor immune microenvironment, cancer risk and immunotherapy response, which can be investigated by polygenic risk scores 6 , 7 .…”

Section: Introductionmentioning

confidence: 99%

Polygenic risk scores for autoimmune related diseases are significantly different in cancer exceptional responders

Chen,

Tan,

Saad Menezes

et al. 2024

npj Precis. Onc.

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A small number of cancer patients respond exceptionally well to therapies and survive significantly longer than patients with similar diagnoses. Profiling the germline genetic backgrounds of exceptional responder (ER) patients, with extreme survival times, can yield insights into the germline polymorphisms that influence response to therapy. As ERs showed a high incidence in autoimmune diseases, we hypothesized the differences in autoimmune disease risk could reflect the immune background of ERs and contribute to better cancer treatment responses. We analyzed the germline variants of 51 ERs using polygenic risk score (PRS) analysis. Compared to typical cancer patients, the ERs had significantly elevated PRSs for several autoimmune-related diseases: type 1 diabetes, hypothyroidism, and psoriasis. This indicates that an increased genetic predisposition towards these autoimmune diseases is more prevalent among the ERs. In contrast, ERs had significantly lower PRSs for developing inflammatory bowel disease. The left-skew of type 1 diabetes score was significant for exceptional responders. Variants on genes involved in the T1D PRS model associated with cancer drug response are more likely to co-occur with other variants among ERs. In conclusion, ERs exhibited different risks for autoimmune diseases compared to typical cancer patients, which suggests that changes in a patient’s immune set point or immune surveillance specificity could be a potential mechanistic link to their exceptional response. These findings expand upon previous research on immune checkpoint inhibitor-treated patients to include those who received chemotherapy or radiotherapy.

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Section: Introductionmentioning

confidence: 99%

Polygenic risk scores for autoimmune related diseases are significantly different in cancer exceptional responders

Chen,

Tan,

Saad Menezes

et al. 2024

npj Precis. Onc.

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show abstract

“…Interestingly, some studies have examined immune cell densities in association with the prognosis of PCa. For example, high levels of regulatory T cells, M1 macrophages and M2 macrophage infiltration were associated with biochemical recurrence ( Chang et al, 2022 ; Choi et al, 2022 ; Sfanos, 2022 ). Thus, novel approaches to using an immune scoring system for PCa stratification will provide new insights into prognostic prediction.…”

Section: Introductionmentioning

confidence: 99%

A novel lysosome-related gene signature coupled with gleason score for prognosis prediction in prostate cancer

Huang

Yang²,

Zhang³

et al. 2023

Front. Genet.

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Background: Prostate cancer (PCa) is highly heterogeneous, which makes it difficult to precisely distinguish the clinical stages and histological grades of tumor lesions, thereby leading to large amounts of under- and over-treatment. Thus, we expect the development of novel prediction approaches for the prevention of inadequate therapies. The emerging evidence demonstrates the pivotal role of lysosome-related mechanisms in the prognosis of PCa. In this study, we aimed to identify a lysosome-related prognostic predictor in PCa for future therapies.Methods: The PCa samples involved in this study were gathered from The Cancer Genome Atlas database (TCGA) (n = 552) and cBioPortal database (n = 82). During screening, we categorized PCa patients into two immune groups based on median ssGSEA scores. Then, the Gleason score and lysosome-related genes were included and screened out by using a univariate Cox regression analysis and the least absolute shrinkage and selection operation (LASSO) analysis. Following further analysis, the probability of progression free interval (PFI) was modeled by using unadjusted Kaplan–Meier estimation curves and a multivariable Cox regression analysis. A receiver operating characteristic (ROC) curve, nomogram and calibration curve were used to examine the predictive value of this model in discriminating progression events from non-events. The model was trained and repeatedly validated by creating a training set (n = 400), an internal validation set (n = 100) and an external validation (n = 82) from the cohort.Results: Following grouping by ssGSEA score, the Gleason score and two LRGs—neutrophil cytosolic factor 1 (NCF1) and gamma-interferon-inducible lysosomal thiol reductase (IFI30)—were screened out to differentiate patients with or without progression (1-year AUC = 0.787; 3-year AUC = 0.798; 5-year AUC = 0.772; 10-year AUC = 0.832). Patients with a higher risk showed poorer outcomes (p < 0.0001) and a higher cumulative hazard (p < 0.0001). Besides this, our risk model combined LRGs with the Gleason score and presented a more accurate prediction of PCa prognosis than the Gleason score alone. In three validation sets, our model still achieved high prediction rates.Conclusion: In conclusion, this novel lysosome-related gene signature, coupled with the Gleason score, works well in PCa for prognosis prediction.

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Germline polygenic risk scores are associated with immune gene expression signature and immune cell infiltration in breast cancer

Liu,

Peng,

Brorson

et al. 2024

The American Journal of Human Genetics

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Polygenic Risk Scores Associated with Tumor Immune Infiltration in Common Cancers

Cited by 3 publications

References 54 publications

Polygenic risk scores for autoimmune related diseases are significantly different in cancer exceptional responders

Polygenic risk scores for autoimmune related diseases are significantly different in cancer exceptional responders

A novel lysosome-related gene signature coupled with gleason score for prognosis prediction in prostate cancer

Germline polygenic risk scores are associated with immune gene expression signature and immune cell infiltration in breast cancer

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