scholarly journals Deep Learning Predicts Underlying Features on Pathology Images with Therapeutic Relevance for Breast and Gastric Cancer

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3687
Author(s):  
Renan Valieris ◽  
Lucas Amaro ◽  
Cynthia Aparecida Bueno de Toledo Osório ◽  
Adriana Passos Bueno ◽  
Rafael Andres Rosales Mitrowsky ◽  
...  

DNA repair deficiency (DRD) is an important driver of carcinogenesis and an efficient target for anti-tumor therapies to improve patient survival. Thus, detection of DRD in tumors is paramount. Currently, determination of DRD in tumors is dependent on wet-lab assays. Here we describe an efficient machine learning algorithm which can predict DRD from histopathological images. The utility of this algorithm is demonstrated with data obtained from 1445 cancer patients. Our method performs rather well when trained on breast cancer specimens with homologous recombination deficiency (HRD), AUC (area under curve) = 0.80. Results for an independent breast cancer cohort achieved an AUC = 0.70. The utility of our method was further shown by considering the detection of mismatch repair deficiency (MMRD) in gastric cancer, yielding an AUC = 0.81. Our results demonstrate the capacity of our learning-base system as a low-cost tool for DRD detection.

2021 ◽  
Author(s):  
Volkan Turan ◽  
Matteo Lambertini ◽  
Dong-Yun Lee ◽  
Erica T Wang ◽  
Florian Clatot ◽  
...  

AbstractPurposeTo determine whether germline BRCA pathogenic variants (gBRCA) are associated with decreased ovarian reserve.Materials and MethodsAn individual patient-data meta-analysis was performed using 5 datasets on 828 evaluable women who were tested for gBRCA. Of those, 250 carried gBRCA while 578 had tested negative and served as controls. Of the women with gBRCA, four centers studied those affected with breast cancer (n=161) and one studied unaffected individuals (n=89). The data were adjusted for the center, age, body mass index, smoking and oral contraceptive pill use before the final analysis. Anti-mullerian hormone (AMH) levels in affected women were drawn before pre-systemic therapy.ResultsMean ages of women with vs. without gBRCA1/2 (34.1± 4.9 vs. 34.3± 4.8 years; p=0.48), and with gBRCA1 vs gBRCA2 (33.7± 4.9 vs. 34.6± 4.8 years; p=0.16) were similar. After the adjustments, women with gBRCA1/2 had significantly lower AMH levels compared to controls (23% lower; 95% CI: 4-38%, p=0.02). When the adjusted analysis was limited to affected women (157 with gBRCA vs. 524 without, after exclusions), the difference persisted (25% lower; CI: 9-38%, p=0.003). The serum AMH levels were lower in women with gBRCA1 (33% lower; CI: 12-49%, p=0.004) but not gBRCA2 compared to controls (7% lower; CI: 31% lower to 26% higher, p=0.64).ConclusionsYoung women with gBRCA pathogenic variants, particularly of those affected and with gBRCA1, have lower serum AMH levels compared to controls. They may need to be preferentially counselled about the possibility of shortened reproductive lifespan due to diminished ovarian reserve.ContextKey objectiveDNA repair deficiency is emerging as a joint mechanism for breast cancer and reproductive aging. Recent studies showed that ovarian reserve maybe lower in women with BRCA pathogenic variants (gBRCA) due to DNA repair deficiency. However, clinical studies using the most sensitive serum ovarian reserve marker Anti-Mullerian-Hormone (AMH) provided mixed results. Given the heterogeneity of the data from clinical studies, we performed an individual patient data (IPD) meta-analysis to determine if gBRCA are associated with lower ovarian reserve.Knowledge generatedgBRCA are associated with diminished ovarian reserve, as determined by serum AMH and this association is restricted to gBRCA1. This finding is firmer for affected women as this IPD meta-analysis predominantly studied those with breast cancer.RelevanceWomen with gBRCA may have shortened reproductive life span due to diminished ovarian reserve and should be proactively counseled for fertility preservation especially if faced with chemotherapy or delaying childbearing.


2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Elaine Gilmore ◽  
Nuala McCabe ◽  
Richard D. Kennedy ◽  
Eileen E. Parkes

Historically the development of anticancer treatments has been focused on their effect on tumor cells alone. However, newer treatments have shifted attention to targets on immune cells, resulting in dramatic responses. The effect of DNA repair deficiency on the microenvironment remains an area of key interest. Moreover, established therapies such as DNA damaging treatments such as chemotherapy and PARP inhibitors further modify the tumor microenvironment. Here we describe DNA repair pathways in breast cancer and activation of innate immune pathways in DNA repair deficiency, in particular, the STING (STimulator of INterferon Genes) pathway. Breast tumors with DNA repair deficiency are associated with upregulation of immune checkpoints including PD-L1 (Programmed Death Ligand-1) and may represent a target population for single agent or combination immunotherapy treatment.


2022 ◽  
Vol 12 ◽  
Author(s):  
Xiaorui Han ◽  
Wuteng Cao ◽  
Lei Wu ◽  
Changhong Liang

BackgroundThe immune microenvironment of tumors provides information on prognosis and prediction. A prior validation of the immunoscore for breast cancer (ISBC) was made on the basis of a systematic assessment of immune landscapes extrapolated from a large number of neoplastic transcripts. Our goal was to develop a non-invasive radiomics-based ISBC predictive factor.MethodsImmunocell fractions of 22 different categories were evaluated using CIBERSORT on the basis of a large, open breast cancer cohort derived from comprehensive information on gene expression. The ISBC was constructed using the LASSO Cox regression model derived from the Immunocell type scores, with 479 quantified features in the intratumoral and peritumoral regions as observed from DCE-MRI. A radiomics signature [radiomics ImmunoScore (RIS)] was developed for the prediction of ISBC using a random forest machine-learning algorithm, and we further evaluated its relationship with prognosis.ResultsAn ISBC consisting of seven different immune cells was established through the use of a LASSO model. Multivariate analyses showed that the ISBC was an independent risk factor in prognosis (HR=2.42, with a 95% CI of 1.49–3.93; P<0.01). A radiomic signature of 21 features of the ISBC was then exploited and validated (the areas under the curve [AUC] were 0.899 and 0.815). We uncovered statistical associations between the RIS signature with recurrence-free and overall survival rates (both P<0.05).ConclusionsThe RIS is a valuable instrument with which to assess the immunoscore, and offers important implications for the prognosis of breast cancer.


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