bluuebunny/crossref_metadata_2025_split huggingface dataset:
JMJD6 Is a Druggable Oxygenase That Regulates AR-V7 Expression in Prostate Cancer
Authors: Paschalis Alec , Welti Jonathan , Neeb Antje J. , Yuan Wei , Figueiredo Ines , Pereira Rita , Ferreira Ana , Riisnaes Ruth , Rodrigues Daniel Nava , Jiménez-Vacas Juan M. , Kim Soojin , Uo Takuma , Micco Patrizio Di , Tumber Anthony , Islam Md. Saiful , Moesser Marc A. , Abboud Martine , Kawamura Akane , Gurel Bora , Christova Rossitza , Gil Veronica S. , Buroni Lorenzo , Crespo Mateus , Miranda Susana , Lambros Maryou B. , Carreira Suzanne , Tunariu Nina , Alimonti Andrea , Al-Lazikani Bissan , Schofield Christopher J. , Plymate Stephen R. , Sharp Adam , de Bono Johann S. 
Published: February 2021

Abstract

Endocrine resistance (EnR) in advanced prostate cancer is fatal. EnR can be mediated by androgen receptor (AR) splice variants, with AR splice variant 7 (AR-V7) arguably the most clinically important variant. In this study, we determined proteins key to generating AR-V7, validated our findings using clinical samples, and studied splicing regulatory mechanisms in prostate cancer models. Triangulation studies identified JMJD6 as a key regulator of AR-V7, as evidenced by its upregulation with in vitro EnR, its downregulation alongside AR-V7 by bromodomain inhibition, and its identification as a top hit of a targeted siRNA screen of spliceosome-related genes. JMJD6 protein levels increased (P &lt; 0.001) with castration resistance and were associated with higher AR-V7 levels and shorter survival (P = 0.048). JMJD6 knockdown reduced prostate cancer cell growth, AR-V7 levels, and recruitment of U2AF65 to AR pre-mRNA. Mutagenesis studies suggested that JMJD6 activity is key to the generation of AR-V7, with the catalytic machinery residing within a druggable pocket. Taken together, these data highlight the relationship between JMJD6 and AR-V7 in advanced prostate cancer and support further evaluation of JMJD6 as a therapeutic target in this disease.

Significance:
This study identifies JMJD6 as being critical for the generation of AR-V7 in prostate cancer, where it may serve as a tractable target for therapeutic intervention.
MEK Inhibition Remodels the Immune Landscape of Mutant KRAS Tumors to Overcome Resistance to PARP and Immune Checkpoint Inhibitors
Authors: Yang Bin , Li Xi , Fu Yu , Guo Ensong , Ye Youqiong , Li Fuxia , Liu Si , Xiao Rourou , Liu Chen , Lu Funian , Huang Jia , Qin Tianyu , Han Leng , Peng Guang , Mills Gordon B. , Sun Chaoyang , Chen Gang 
Published: February 2021

Abstract

Mutant KRAS tumors are associated with poor outcomes, at least in part, due to decreased therapeutic sensitivity. Here, we show that KRAS mutations are associated with resistance to monotherapy and combination therapy with PARP inhibitors (PARPi) and immune checkpoint blockade with anti–PD-L1 antibodies. In mutant KRAS tumors, inhibition of KRAS signaling with MEK inhibitors (MEKi) triggered and amplified PARPi-induced DNA damage, cytosolic double-stranded DNA accumulation, STING pathway activation, and CD8+ T-cell recruitment. Moreover, MEKi decreased myeloid-derived suppressor cell infiltration, in part, by inhibiting IL6 and GMCSF production. Importantly, addition of MEKi to PARPi and anti–PD-L1 resulted in marked tumor inhibition in immunocompetent mutant KRAS tumor models. This study provides the underlying mechanistic data to support evaluation of PARPi, MEKi, and anti–PD-L1 combination in clinical trials of mutant KRAS tumors.

Significance:
This study provides key insights into the potential for using MEKi combined with PARPi and anti–PD-L1 for the treatment of all mutant KRAS tumors.
Time-Dependent Effects of Oral Contraceptive Use on Breast, Ovarian, and Endometrial Cancers
Authors: Karlsson Torgny , Johansson Therese , Höglund Julia , Ek Weronica E. , Johansson Åsa 
Published: February 2021

Abstract

Oral contraceptive use has been suggested to influence the risk of breast, ovarian, and endometrial cancer. The purpose of this study is to clarify the time-dependent effects between long-term oral contraceptive use and cancer risk. We performed an observational study in 256,661 women from UK Biobank, born between 1939 and 1970. Information on cancer diagnoses were collected from self-reported data and from national registers until March 2019. Cumulative risk of cancer over the timespan of the study, as measured by the OR, and instantaneous risk, as measured by the HR, were assessed using Logistic and Cox regression analyses, respectively. The odds were lower among ever users, compared with never users, for ovarian cancer [OR = 0.72; 95% confidence interval (CI), 0.65–0.81] and endometrial cancer (OR = 0.68; 95% CI, 0.62–0.75), an association that was stronger with longer use (P &lt; 0.001). Increased odds were seen for breast cancer in women when limiting the follow-up to 55 years of age (OR = 1.10; 95% CI, 1.03–1.17), but not for the full timespan. We only found a higher HR for breast cancer in former users immediately (≤2 years) after discontinued oral contraceptive use (HR = 1.55; 95% CI, 1.06–2.28), whereas the protective association for ovarian and endometrial cancer remained significant up to 35 years after last use of oral contraceptives. Given the body of evidence presented in our study, we argue that oral contraceptives can dramatically reduce women's risk of ovarian and endometrial cancer, whereas their effect on lifetime risk of breast cancer is limited.

Significance:
These results enable women and physicians to make more informed decisions considering oral contraceptive use, thus constituting an important step toward personalized medicine.
Tet2 Inactivation Enhances the Antitumor Activity of Tumor-Infiltrating Lymphocytes
Authors: Lee Minjung , Li Jianfang , Li Jia , Fang Shaohai , Zhang Joanna , Vo Anh Tran Tram , Han Wei , Zeng Hongxiang , Isgandarova Sevinj , Martinez-Moczygemba Margarita , Zhou Yubin , Sun Deqiang , Huang Yun 
Published: February 2021

Abstract

Inactivation of tumor-infiltrating lymphocytes (TIL) is one of the mechanisms mitigating antitumor immunity during tumor onset and progression. Epigenetic abnormalities are regarded as a major culprit contributing to the dysfunction of TILs within tumor microenvironments. In this study, we used a murine model of melanoma to discover that Tet2 inactivation significantly enhances the antitumor activity of TILs with an efficacy comparable to immune checkpoint inhibition imposed by anti-PD-L1 treatment. Single-cell RNA-sequencing analysis suggested that Tet2-deficient TILs exhibit effector-like features. Transcriptomic and ATAC-sequencing analysis showed that Tet2 ablation reshapes chromatin accessibility and favors binding of transcription factors geared toward CD8+ T-cell activation. Furthermore, the ETS family of transcription factors contributed to augmented CD8+ T-cell function following Tet2 depletion. Overall, our study establishes that Tet2 constitutes one of the epigenetic barriers that account for dysfunction of TILs and that Tet2 inactivation could promote antitumor immunity to suppress tumor growth.

Significance:
This study suggests that ablation of TET2+ from TILs could promote their antitumor function by reshaping chromatin accessibility for key transcription factors and enhancing the transcription of genes essential for antitumor activity.
Spatiotemporal Heterogeneity across Metastases and Organ-Specific Response Informs Drug Efficacy and Patient Survival in Colorectal Cancer
Authors: Zhou Jiawei , Li Quefeng , Cao Yanguang 
Published: February 2021

Abstract

The sum of target lesions is routinely used to evaluate patient objective responses to treatment in the RECIST criteria, but it fails to address response heterogeneity across metastases. This study argues that spatiotemporal heterogeneity across metastases and organ-specific response is informative for drug efficacy and patient survival. We analyzed the longitudinal data of 11,404 metastatic lesions in 2,802 colorectal cancer patients from five phase III clinical trials. Initially, a metric Gower distance was applied to quantify response heterogeneity across metastases. Next, the spatiotemporal response heterogeneity across anatomic sites, therapies, and KRAS mutation status was assessed and examined for its association with drug efficacy and long-term patient survival. The response of metastatic lesions broadly differed across anatomic sites and therapies. About 60% of patients had at least one lesion respond contrarily from total tumor size. High interlesion heterogeneity was associated with shorter progression-free survival and overall survival. Targeted therapies (bevacizumab or panitumumab) combined with standard chemotherapy reduced interlesion heterogeneity and elicited more favorable effects from liver lesions (P &lt; 0.001) than chemotherapy alone. Moreover, the favorable responses in liver metastases (&gt; 30% shrinkage) were associated with extended patient overall survival (P &lt; 0.001), in contrast to lesions in the lungs and lymph nodes. Altogether, the spatiotemporal response heterogeneity across metastases informed drug efficacy and patient survival, which could improve the current methods for treatment evaluation and patient prognosis.

Significance:
These findings support the modification of RECIST criteria to include individual lesion response to improve assessments of drug efficacy.
G9a Inhibition Enhances Checkpoint Inhibitor Blockade Response in Melanoma
Authors: Kelly Gregory M. , Al-Ejeh Fares , McCuaig Robert , Casciello Francesco , Ahmad Kamal Nabilah , Ferguson Blake , Pritchard Antonia L. , Ali Sayed , Silva Ines P. , Wilmott James S. , Long Georgina V. , Scolyer Richard A. , Rao Sudha , Hayward Nicholas K. , Gannon Frank , Lee Jason S. 
Published: February 2021

AbstractPurpose:G9a histone methyltransferase exerts oncogenic effects in several tumor types and its inhibition promotes anticancer effects. However, the impact on checkpoint inhibitor blockade response and the utility of G9a or its target genes as a biomarker is poorly studied. We aimed to examine whether G9a inhibition can augment the efficacy of checkpoint inhibitor blockade and whether LC3B, a G9a target gene, can predict treatment response.Experimental Design:Clinical potential of LC3B as a biomarker of checkpoint inhibitor blockade was assessed using patient samples including tumor biopsies and circulating tumor cells from liquid biopsies. Efficacy of G9a inhibition to enhance checkpoint inhibitor blockade was examined using a mouse model.Results:Patients with melanoma who responded to checkpoint inhibitor blockade were associated with not only a higher level of tumor LC3B but also a higher proportion of cells expressing LC3B. A higher expression of MAP1LC3B or LC3B protein was associated with longer survival and lower incidence of acquired resistance to checkpoint inhibitor blockade, suggesting LC3B as a potential predictive biomarker. We demonstrate that G9a histone methyltransferase inhibition is able to not only robustly induce LC3B level to augment the efficacy of checkpoint inhibitor blockade, but also induces melanoma cell death.Conclusions:Checkpoint inhibitor blockade response is limited to a subset of the patient population. These results have implications for the development of LC3B as a predictive biomarker of checkpoint inhibitor blockade to guide patient selection, as well as G9a inhibition as a strategy to extend the proportion of patients responding to immunotherapy.
Abstract PS18-16: The complete estrogen receptor antagonist OP-1250 shrinks tumors in xenograft models and has favorable preclinical pharmacokinetic attributes
Authors: Hodges-Gallagher Leslie , Sun Richard , Myles David C , Klein Pamela M , Zujewski Jo Anne , Harmon Cyrus L , Kushner Peter J 
Published: February 2021

Abstract
Antiestrogens are widely used to treat ER+, HER2- breast cancer however these may produce estrogen-like agonist effects in a cell and gene-specific manner. Furthermore, this partial agonism has been implicated in the development of tumor resistance. In contrast, a complete ER antagonist lacks agonist activity in all tissues. Given the high risk of recurrence in ER+ patients treated with endocrine therapies, we hypothesize that drugs that completely antagonize ER-mediated signaling will have a clinical advantage in treating resistant tumors, particularly in tumors for which the ER has acquired mutations conferring estrogen-independent growth.
We previously identified OP-1250 in our laboratory as a complete antagonist and degrader of wild type and mutant ERalpha in breast and uterus cells. Here we explore the pharmacokinetic properties of orally administered OP-1250 and its ability to shrink breast tumors from xenograft models expressing both wild type and mutant estrogen receptors. Orally administered OP-1250 produced high and stable levels in multiple species, suggesting that once daily dosing may be sufficient to produce excellent drug exposure in patients. OP-1250 shrank ER+ tumors in multiple patient-derived tumor xenografts in mice at daily doses of 3 mg/kg, including in tumors expressing the Y537S allele of ERalpha that confers estrogen-independent growth and tumor resistance. Furthermore, OP-1250 accumulated within tumor specimens, indicating excellent target penetration was achieved with low daily doses.
These preclinical studies indicate that OP-1250 has the potential to be a best-in-class antiestrogen due to its ability to complete antagonize ER, potent efficacy in shrinking tumors, and robust drug exposure. A Phase 1/2 dose escalation and expansion study in patients with ER+, HER2- metastatic or advanced BC previously treated with an endocrine therapy will be initiated this year.
Citation Format: Leslie Hodges-Gallagher, Richard Sun, David C Myles, Pamela M Klein, Jo Anne Zujewski, Cyrus L Harmon, Peter J Kushner. The complete estrogen receptor antagonist OP-1250 shrinks tumors in xenograft models and has favorable preclinical pharmacokinetic attributes [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS18-16.
Abstract PS6-40: Clinical risk criteria and recurrence index for distant recurrence for patients with early stage luminal breast cancer
Authors: Cheng Skye Hung-Chun , Liu Liang-Chih , Tseng Ling-Ming , Chang Chuan-Hsun , Huang Chiun-Sheng , Liang Ji-An , Hsu Yu-Chen , Hsieh Chia-Ming , Wei Jun-Ru 
Published: February 2021

Abstract
Background:Clinical risk criteria (CRC) has been used in two well-known gene-expression trials (TAILORX and MINDACT) to predict the risk of distant recurrence (DR). The definition of clinical low-risk patients was (1) node-negative associated with (grade 1 with tumor ≤3cm, grade 2 with tumor≤2cm, or grade 3 with tumor ≤1cm) and N1 with grade 1 and tumor ≤2cm. Recurrence Index for distant recurrence (RI-DR) is a clinical-genomic model, based on genomic profiling derived from Asian women. The primary purpose of this study is to access the clinical utility of RI-DR and CRC in Asian breast cancer patients.
Methods:A total of 208 patients (N0 70.2%, N1 29.8%) with luminal-like breast cancer were enrolled in a retrospective study across Taiwan medical centers. Kaplan-Meier method was used to calculate the survival rates and the log rank test was applied for the survival difference between two or more independent groups. The primary endpoint was the recurrence-free interval (RFI).
Results:With a median follow-up of 49.05 [IQR 29.72-71.96], the 5-year RFI was significantly poorer in the high-risk group than the low-risk group (87.2% [95% CI, 80.0-95.0] versus 95.2% [89.75-100] by the RI-DR, p = 0.011; and 86.9% [79.8-94.6] versus 97.0% [92.9-100] by the clinical risk, p = 0.03). Combined the CRC and RI-DR together, clinical high (CH) and RI-DR high (RH)had the poorest 5-year RFI (85.2%, [76.6-94.8]); clinical low (CL) and RI-DR low (RL) had the best 5-year RFI (98.0% [94.08, 100]). Among CL-risk patients, RL group has a trend towards less recurrence than RH group (1/66 [1.51%] versus 2/19 [10.52%], p= 0.15). Similar trend was observed in CH-risk patients (RL: 2/41 (4.88%) versus RH: 12/82 [14.63%], p = 0.17) (Table 1).
Conclusions:The present study provides robust evidences that clinical-risk criteria and RI-DR testing could partition patients into good and poor prognosis in early-stage luminal breast cancer. RI-DR has a trend to identify low- and high-risk patients if clinical risk criteria have been applied in clinical practice.
Analyses of Clinical Risk Criteria and Recurrence Index TogetherNo. of PatientsNo. of Events5-year RFI % (95% CI)Log rank, P valueClinical-Clinical-HighRI-DR high821285.20 [76.55, 94.81]0.17RI-DR low41291.30 [80.15, 100]Clinical-LowRI-DR high19294.12 [83.57, 100]0.15RI-DR low66197.96 [94.08, 100]
Citation Format: Skye Hung-Chun Cheng, Liang-Chih Liu, Ling-Ming Tseng, Chuan-Hsun Chang, Chiun-Sheng Huang, Ji-An Liang, Yu-Chen Hsu, Chia-Ming Hsieh, Jun-Ru Wei. Clinical risk criteria and recurrence index for distant recurrence for patients with early stage luminal breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS6-40.
Abstract PS6-49: Intratumoral cytotoxic t-lymphocyte numbers and chemokine predict long-term survival of triple-negative breast cancer independently of tumor mutational burden
Authors: Katsuta Eriko , Yan Li , Opyrchal Mateusz , Kalinski Pawel , Takabe Kazuaki 
Published: February 2021

Abstract
Background: Cytotoxic T-lymphocyte (CTL) infiltration into tumor is a positive prognostic factor in breast cancer. While high tumor mutation burden (TMB) is also considered as a predictor of tumor immunogenicity and response to immunotherapy. Triple-negative breast cancer (TNBC) has a higher TMB and accumulates more CTLs compared to other breast cancer subtypes. CTLs are identified by CD8 surface marker, which is encoded by CD8A gene. Granzyme B (GZMB) is a serine protease that is secreted by activated CTLs to induce apoptosis of the target cells. Chemokines, such as CXCL10 and CCL5 are key to the selective attraction of activated CTLs into tumors, as shown in multiple cancers. However, it remains unknown whether tumor infiltrating functional CTLs levels correlate with improved patient survival and are independent of TMB. In order to investigate it, we developed Functional Hotness Score (FHS) combining gene expressions of markers and attractants of activated CTL. Methods: Utilizing publicly available breast cancer cohorts, we established Functional Hotness Score (FHS), based on gene expression levels of CTL and chemokine markers in bulk tumors. The associations of FHS and breast cancer patient prognosis as well as distinct immunity markers were analyzed. Results: CD8, GZMB and CXCL10 combination resulted in the best prediction of the breas cancer patient prognosis. Thus, we established FHS based on the expression levels of these three genes. Breast cancer patients with the high-FHS tumors showed significantly better survival. FHS was lower in the metastatic breast cancers. Among breast cancer subtypes, triple-negative breast cancer (TNBC) showed the highest FHS. FHS predicted patient survival in hormone receptor (HR)-negative, especially TNBC, but not in HR-positive breast cancer. The high-FHS TNBCs showed not only higher CD8+ T cell infiltration, but also enhanced broader type-1 anti-cancer immunity. The patients with the high-FHS tumors showed better prognosis not only in high-TMB tumors but also in low-TMB TNBCs. The combination of high-TMB with high-FHS identified a unique subset of patients who do not recur over time. Conclusions: TNBCs with high-FHS based on the expression levels of CD8A, GZMB and CXCL10 showed improved prognosis with higher anti-cancer immunity regardless of TMB. FHS constitutes an independent prognostic marker of survival, particularly robust when combined with TMB in TNBCs.
Citation Format: Eriko Katsuta, Li Yan, Mateusz Opyrchal, Pawel Kalinski, Kazuaki Takabe. Intratumoral cytotoxic t-lymphocyte numbers and chemokine predict long-term survival of triple-negative breast cancer independently of tumor mutational burden [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS6-49.
Abstract PS8-38: Development of random forest classifier method to predict breast cancer mortality among early stage breast cancer patients
Authors: Chandler Arwen 
Published: February 2021

Abstract
Background: Among women diagnosed with early stage breast cancer, breast cancer mortality was conditional on the onset of distant recurrence. Gene expression profiling (GEP) tests (e.g., Oncotype Dx) have been commonly used to determine the risk level of distant recurrence, but its predictive ability is often questioned. The objective of this study aims to explore the potential of random forest machine learning to predict the risk of breast cancer mortality.Method: 63,104 patients with node-negative early stage breast cancer in the SEER-GHI dataset were randomly sampled into two groups, for the purpose of training and testing the model where each group consisted of 67% and 33% of all patients, respectively. The patient characteristics and tumor features in the study included age, tumor size, grade, chemotherapy use, Oncotype DX test recurrence score, and more. Further feature selection in the construction of the predictive model was conducted via the Boruta algorithm. As the dataset is highly imbalanced with only a very small percentage of samples being fatal, Synthetic Minority Over-Sampling Technique (SMOTE) was employed to address this issue. A cross-validated grid search finds the best combination of hyper-parameters to improve the model’s performance.Results: The mean and standard deviation of follow-up duration in the cohort of patients were 32.4 and 14.3 months, respectively. Of 37,043 patients, there were 158 breast cancer deaths. Within up to a 59-month follow-up period, the breast cancer specific mortality rate was 0.43%. Based on the limited available data, the outcome of the random forest classifier method in predicting breast cancer mortality shows sensitivity 0.712, specificity 0.773, overall accuracy 0.773, and AUC (area under ROC curve) 0.742.
Conclusion: The use of the random forest ML algorithm to predict breast cancer mortality is promising when the hyper-parameters are fine-tuned. However, the model's positive predictive value is highly associated with sufficient data sources.
Citation Format: Arwen Chandler. Development of random forest classifier method to predict breast cancer mortality among early stage breast cancer patients [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS8-38.