Cancer genomics of lung cancer including malignant mesothelioma: A brief overview of current status and future prospects
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Jhanwar, Suresh C.↗
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Cancer genomics predicts disease relapse and therapeutic response to neoadjuvant chemotherapy of hormone sensitive breast cancers
Several studies provide insight into the landscape of breast cancer genomics with the genomic characterization of tumors offering exceptional opportunities in defining therapies tailored to the patient’s specific need. However, translating genomic data into personalized treatment regimens has been hampered partly due to uncertainties in deviating from guideline based clinical protocols. Here we report a genomic approach to predict favorable outcome to treatment responses thus enabling personalized medicine in the selection of specific treatment regimens. The genomic data were divided into a training set of N = 835 cases and a validation set consisting of 1315 hormone sensitive, 634 triple negative breast cancer (TNBC) and 1365 breast cancer patients with information on neoadjuvant chemotherapy responses. Patients were selected by the following criteria: estrogen receptor (ER) status, lymph node invasion, recurrence free survival. The k-means classification algorithm delineated clusters with low- and high- expression of genes related to recurrence of disease; a multivariate Cox’s proportional hazard model defined recurrence risk for disease. Classifier genes were validated by Immunohistochemistry (IHC) using tissue microarray sections containing both normal and cancerous tissues and by evaluating findings deposited in the human protein atlas repository. Based on the leave-on-out cross validation procedure of 4 independent data sets we identified 51-genes associated with disease relapse and selected 10, i.e. TOP2A, AURKA, CKS2, CCNB2, CDK1 SLC19A1, E2F8, E2F1, PRC1, KIF11 for in depth validation. Expression of the mechanistically linked disease regulated genes significantly correlated with recurrence free survival among ER-positive and triple negative breast cancer patients and was independent of age, tumor size, histological grade and node status. Importantly, the classifier genes predicted pathological complete responses to neoadjuvant chemotherapy (P < 0.001) with high expression of these genes being associated with an improved therapeutic response toward two different anthracycline-taxane regimens; thus, highlighting the prospective for precision medicine. Our study demonstrates the potential of classifier genes to predict risk for disease relapse and treatment response to chemotherapies. The classifier genes enable rational selection of patients who benefit best from a given chemotherapy thus providing the best possible care. The findings encourage independent clinical validation.
59 BASIC BIOLOGICAL SCIENCES↗
Experimental and pan-cancer genome analyses reveal widespread contribution of acrylamide exposure to carcinogenesis in humans
Humans are frequently exposed to acrylamide, a probable human carcinogen found in commonplace sources such as most heated starchy foods or tobacco smoke. Prior evidence has shown that acrylamide causes cancer in rodents, yet epidemiological studies conducted to date are limited and, thus far, have yielded inconclusive data on association of human cancers with acrylamide exposure. In this study, we experimentally identify a novel and unique mutational signature imprinted by acrylamide through the effects of its reactive metabolite glycidamide. We next show that the glycidamide mutational signature is found in a full one-third of approximately 1600 tumor genomes corresponding to 19 human tumor types from 14 organs. The highest enrichment of the glycidamide signature was observed in the cancers of the lung (88% of the interrogated tumors), liver (73%), kidney (>70%), bile duct (57%), cervix (50%), and, to a lesser extent, additional cancer types. Overall, our study reveals an unexpectedly extensive contribution of acrylamide-associated mutagenesis to human cancers.
60 APPLIED LIFE SCIENCES↗
Mathematical modelling the pathway of genomic instability in lung cancer
Genomic instability plays a significant role in lung cancer. Although substantial research has been conducted using both clinical and theoretical studies, it is still a hotly debated issue to whether genomic instability is necessary or whether genomic instability precedes oncogenes activation and tumor suppressor genes inactivation for lung cancer. In response to this issue, we come up with a mathematical model incorporating effects of genomic instability to investigate the genomic instability pathway of human lung cancer. The presented model are applied to match the incidence rate data of lung cancer from the Life Span Study cohort of the atomic bomb survivors in Nagasaki and Hiroshima and the Surveillance Epidemiology and End Results registry in the United States. Model results suggest that genomic instability is necessary in the tumorigenesis of lung cancer, and genomic instability has no significant impact on the net proliferation rate of cells by statistical criteria. By comparing the results of the LSS data to those of the SEER data, we conclude that the genomic instability pathway exhibits a sensitivity to radiation exposure, more intensive in male patients.
60 APPLIED LIFE SCIENCES↗
From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer
Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine learning approach to identify the cellular morphometric biomarkers (CMB) from digital images of hematoxylin and eosin (H&E) micrographs of orthotopic Trp53-null mammary tumors (n = 154) and to discover the corresponding cellular morphometric subtypes (CMS). Of the two CMS identified, CMS-2 was significantly associated with shorter survival (p = 0.0084). We then evaluated the learned CMB and corresponding CMS model in MMTV-Erbb2 transgenic mouse mammary tumors (n = 53) in which CMS-2 was significantly correlated with the presence of metastasis (p = 0.004). We next evaluated the mouse CMB and CMS model on The Cancer Genome Atlas breast cancer (TCGA-BRCA) cohort (n = 1017). Kaplan–Meier analysis showed significantly shorter overall survival (OS) of CMS-2 patients compared to CMS-1 patients (p = 0.024) and added significant prognostic value in multi-variable analysis of clinical and molecular factors, namely, age, pathological stage, and PAM50 molecular subtype. Thus, application of CMS to digital images of routine workflow H&E preparations can provide unbiased biological stratification to inform patient care.
60 APPLIED LIFE SCIENCES↗
Identification of important invasion and proliferation related genes in adrenocortical carcinoma
Adrenocortical carcinoma (ACC) is an end‐stage hormonal syndrome. Although profound attempts have been made to illuminate the pathogenesis, the molecular mechanisms of ACC remain to be clarified. To identify the important genes in the progression of ACC, microarray datasets GSE19775 was downloaded from the gene expression omnibus database. The differentially-expressed genes (DEGs) were identified, and pathway and GO enrichment analyses were performed. The protein–protein interaction (PPI) network was constructed and the module analysis was performed using the protein interaction network analysis and Cytoscape. Also constructed target genes–miRNA regulatory network and target genes–TF regulatory network. Correlation of the hub genes were analyzed in The Cancer Genome Atlas. The prognostic values of hub genes were further validated by online tool UALCAN. Mutation analysis was done by online tool CBio Cancer Genomics Portal. A total of 884 DEGs were identified, with 441 in up regulation and 443 in down regulation. Pathways in catecholamine biosynthesis, aldosterone synthesis and secretion, pyrimidine deoxyribonucleosides salvage and systemic lupus erythematosus were the most significantly enriched for DEGs (up and down regulated). Blood vessel morphogenesis and cell cycle phase transition were the most significantly enriched term in biological processes, while extracellular matrix and chromosome, centromeric region were in cellular component and heparin binding and protein dimerization activity were in molecular function. Among the PPI networks and its module, target genes–miRNA regulatory network and target genes–TF regulatory network, hub genes were YWHAZ, FN1, GRK5, VCAM1, GATA6, TXNIP, HSPA1A, and F11R. Hub genes such as YWHAZ, STAT1, ICAM1, SH3BP5, CD83, FN1, TK1, HIST1H1C, CABLES1, and MCM3 were associated with poor overall survival, while hub genes such as STAT1, ICAM1, CD83, FN1, TK1, HIST1H1C, and MCM3 were highly expressed in stage 4. In conclusion, DEGs and hub genes diagnosed in this study may deepen our understanding of molecular mechanisms underlying the progression of ACC, and provide important targets for diagnosis and treatment of ACC.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Chemoproteogenomic stratification of the missense variant cysteinome
Abstract Cancer genomes are rife with genetic variants; one key outcome of this variation is widespread gain-of-cysteine mutations. These acquired cysteines can be both driver mutations and sites targeted by precision therapies. However, despite their ubiquity, nearly all acquired cysteines remain unidentified via chemoproteomics; identification is a critical step to enable functional analysis, including assessment of potential druggability and susceptibility to oxidation. Here, we pair cysteine chemoproteomics—a technique that enables proteome-wide pinpointing of functional, redox sensitive, and potentially druggable residues—with genomics to reveal the hidden landscape of cysteine genetic variation. Our chemoproteogenomics platform integrates chemoproteomic, whole exome, and RNA-seq data, with a customized two-stage false discovery rate (FDR) error controlled proteomic search, which is further enhanced with a user-friendly FragPipe interface. Chemoproteogenomics analysis reveals that cysteine acquisition is a ubiquitous feature of both healthy and cancer genomes that is further elevated in the context of decreased DNA repair. Reference cysteines proximal to missense variants are also found to be pervasive, supporting heretofore untapped opportunities for variant-specific chemical probe development campaigns. As chemoproteogenomics is further distinguished by sample-matched combinatorial variant databases and is compatible with redox proteomics and small molecule screening, we expect widespread utility in guiding proteoform-specific biology and therapeutic discovery.
Desai, Heta (ORCID:0000000343621707)↗
Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor
Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues.
59 BASIC BIOLOGICAL SCIENCES↗
Clinical potential of mass spectrometry-based proteogenomics
Cancer genomics research aims to advance personalized oncology by finding and targeting genetic alterations associated with cancers. In genome-driven oncology, treatments are selected for individual patients based on the genomic sequence of their tumor. This personalized oncology approach has prolonged survival for subsets of cancer patients. However, many patients do not respond to the predicted therapies based on genomic profiles of their tumors. Recent studies pairing genomic and proteomic analyses in the same tumors have shown that the proteome encodes novel information that is not discerned through genomic analysis alone. This has led to the concept of “proteogenomics,” in which both types of data are leveraged for a more complete view of tumor biology that may more effectively match cancer patients to efficacious treatments. Technological advances in methods for quantifying proteins, including targeted mass spectrometry, have opened a path for the clinical translation of proteogenomic findings into clinical research. We discuss the added value of a combined proteogenomics approach over the current genome-centric approach in characterizing human cancers, and summarize current efforts to incorporate targeted proteomic measurements based on multiple reaction monitoring mass spectrometry (MRM) into the clinical laboratory to facilitate clinical proteogenomics.
Zhang, Bing↗
Structural variant analysis of a cancer reference cell line sample using multiple sequencing technologies
The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples. We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy. A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods.
59 BASIC BIOLOGICAL SCIENCES↗
Downregulated miR-1247-5p associates with poor prognosis and facilitates tumor cell growth via DVL1/Wnt/β-catenin signaling in breast cancer
The abnormal expression of microRNAs is a key hallmark of breast cancer. Nevertheless, the biological roles of miR-1247-5p in breast cancer remain unknown. In this study, we revealed that miR-1247-5p expression was markedly decreased in breast cancer. It was a valuable diagnostic biomarker for breast cancer with the area under the curve of more than 0.80. Reduced miR-1247-5p expression was significantly correlated with patient age, tumor size, and poor prognosis in The Cancer Genome Atlas cohort including 839 breast cancer patients. Multivariate Cox regression analysis demonstrated that miR-1247-5p was an independent prognostic indicator for overall survival (hazard radio [HR] = 1.683, 95% confidence interval [CI] = 1.087–2.606, p = 0.020) and recurrence-free survival (HR = 2.496, 95% CI = 1.576–3.951, p < 0.001). Moreover, functional studies showed that overexpression of miR-1247-5p inhibited proliferation and induced apoptosis in breast cancer cells. Bioinformatics analysis and mechanistic investigations revealed that Dishevelled 1 (DVL1) was a direct target of miR-1247-5p. Inhibition of DVL1 by miR-1247-5p resulted in the suppression of Wnt/β-catenin signaling, whereas overexpression of DVL1 abrogated the miR-1247-5p-mediated effect. These data reveal that miR-1247-5p, as an oncosuppressor in breast cancer, may be a promising prognostic biomarker and therapeutic target.
60 APPLIED LIFE SCIENCES↗
EEPD1 evolved a unique DNA clamping dimer protecting reversed replication forks
Exonuclease/endonuclease/phosphatase (EEP)-fold hydrolases are canonically monomeric phosphodiesterases exemplified by APE1, DNase I, and TDP2 nucleases. While EEP family domain containing protein 1 (EEPD1) acts in DNA stress responses, its proposed nuclease activities are enigmatic. Here, we integrate hybrid structural methods, evolution, biochemistry, cancer genomics, plus molecular and cell biology to define EEPD1 structure, assembly, and function at stalled DNA replication forks. Results imply EEPD1 surprisingly requires both unique EEP domain dimer and distinctive tandem Helix-hairpin-Helix [(HhH) 2 ] domains to clamp double-stranded (ds) DNA at reversed DNA replication forks for fork protection. Small-angle X-ray Scattering (SAXS), crystal, and cryo-EM structures unveil an unprecedented tryptophan handshake dimer, conserved interface di-Trp-Pro pocket, and adjustable “wrist” enabling an open-closed conformational switch. EEPD1 dimer cooperatively binds complex dsDNA replication fork intermediates but alone lacks nuclease activity due to loss of key EEP catalytic residues during Metazoan evolution and atmospheric oxygen buildup. Instead, EEPD1 prevents nucleolytic degradation of reversed replication forks by MRE11. Furthermore, cancer bioinformatics support oxidative damage-dependent EEPD1 association as a significant modulator of overall patient survival. Collective findings uncover unexpected EEP dimer and fork protection function in clamping, not cleaving, reversed replication forks for metazoan oxidative stress responses controlling genome stability and cancer outcomes.
Shen, Runze [Univ. of Texas, Houston, TX (United S↗
Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects
Prostate cancer (PCa) brings huge public health burden in men. A growing number of conventional observational studies report associations of multiple circulating proteins with PCa risk. However, the existing findings may be subject to incoherent biases of conventional epidemiologic studies. To better characterize their associations, herein, we evaluated associations of genetically predicted concentrations of plasma proteins with PCa risk. In this study, we developed comprehensive genetic prediction models for protein levels in plasma. After testing 1308 proteins in 79 194 cases and 61 112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL, 24 proteins showed significant associations with PCa risk, including 16 previously reported proteins and eight novel proteins. Of them, 14 proteins showed negative associations and 10 showed positive associations with PCa risk. For 18 of the identified proteins, potential functional somatic changes of encoding genes were detected in PCa patients in The Cancer Genome Atlas (TCGA). Genes encoding these proteins were significantly involved in cancer-related pathways. We further identified drugs targeting the identified proteins, which may serve as candidates for drug repurposing for treating PCa. In conclusion, this study identifies novel protein biomarker candidates for PCa risk, which may provide new perspectives on the etiology of PCa and improve its therapeutic strategies.
59 BASIC BIOLOGICAL SCIENCES↗
LRP4 promotes proliferation, migration, and invasion in papillary thyroid cancer
Dysregulation of cell proliferation and death is considered the foundation of the malignant biological characteristics of cancer. In this study, we conducted a comprehensive analysis of a massively parallel whole transcriptome resequencing of paired papillary thyroid cancer and normal thyroid tissues from 19 patients. In addition, we found that LRP4, a member of the low-density lipoprotein receptor-related protein family, is significantly overexpressed in thyroid carcinoma. We demonstrated through quantitative real-time polymerase chain reaction (qRT-PCR) that LRP4 is upregulated in papillary thyroid cancer (PTC) tissues. This observation was also consistent with data analyzed from The Cancer Genome Atlas (TCGA) cohort. Thus, the biological role of LRP4 in the thyroid cancer in the present study was investigated using the PTC cell lines TPC1, BCPAP and KTC-1. In these cell lines, the mRNA level of LRP4 was higher than normal thyroid cancer cell named HTORI3. In vitro experiments demonstrated that LRP4 downregulation significantly inhibited the colony formation, proliferation, migration, and invasion of the three PTC cell lines. Knockdown of LRP4 by small interfering RNA (siRNA) in those cell lines decreased the protein expression of N-cadherin, Enhancer of zeste homolog 2 (EZH2), and Zinc finger E-box-binding home-box 1 (ZEB1). Furthermore, LRP4 knockdown significantly reduced the levels of phosphorylated PI3K in the PTC cell lines. In conclusion, the present study indicated that LRP4 is a gene associated with PTC and might become a potential therapeutic target.
60 APPLIED LIFE SCIENCES↗
ACBD3 is up-regulated in gastric cancer and promotes cell cycle G1-to-S transition in an AKT-dependent manner
Highlights: • ACBD3 is up-regulated in gastric cancer. • ACBD3 regulates cell-cycle of gastric cancer in an AKT-dependent manner. It has been reported that ACBD3 is closely related to the malignant process of cells, but its role in gastric cancer has not been elucidated. This study aims to investigate the expression and function of ACBD3 in human gastric cancer. The Cancer Genome Atlas (TCGA) database were selected to analyze mRNA levels of ACBD3 in gastric cancer tissues and normal gastric epithelial tissues. qPCR and Western blot were conducted to detect the expression of ACBD3 in two normal gastric epithelial cell lines and five gastric cancer cell lines which were cultured in our laboratory. To exclude differences in individual background between different patients, we further detected the expression of ACBD3 in 8 pairs of malignant/non-malignant clinical gastric tissues. Through the establishment of stable cells, in vitro cell experiments and in vivo xenotransplantation models in mice, the role of ACBD3 in the proliferation of gastric cancer cells has been further explored. AKT inhibitors were used to deeply explore the molecular regulation mechanism of ACBD3. The results showed that the elevated ACBD3 in gastric cancer tissue were positively correlated with the clinical grade and prognosis of gastric cancer. In terms of molecular function, we found that ACBD3 can enhance the production and growth of gastric cancer cells. At the same time, the activation of AKT kinase played an important role in ACBD3's promotion of G1-to-S transition. The experiments generally indicate that ACBD3 is expected to become a potential diagnostic molecule or therapeutic target for gastric cancer.
60 APPLIED LIFE SCIENCES↗
Molecular subtyping reveals immune alterations in IDH wild‐type lower‐grade diffuse glioma
Abstract Isocitrate dehydrogenase ( IDH ) wild‐type diffuse lower‐grade glioma (LGG) is usually associated with poor outcome, but there have been disputes over its clinical outcome and classification. We present here a robust gene expression‐based molecular classification of IDH wild‐type diffuse LGG into two subtypes with distinct biological and clinical features. A discovery cohort of 49 IDH wild‐type diffuse LGGs from the Chinese Glioma Genome Atlas (CGGA) was subjected to clustering and function analysis. Seventy‐three tumors from The Cancer Genome Atlas (TCGA) were used to validate our findings. Consensus clustering of transcriptional data uncovered concordant classification of two robust and prognostically significant subtypes of IDH wild‐type LGG. Subtype 1, associated with poorer outcomes, was characterized by significantly higher immune and cytolytic scores, M2 macrophages, and up‐regulation of immune exhaustion markers, while Subtype 2, which had elevated lymphocytes and plasma cells, showed relatively favorable survival. Somatic alteration analysis revealed that Subtype 1 showed more frequently deleted regions, such as the locus of CDKN2A / CDKN2B , DMRTA1 , C9orf53 , and MTAP . Furthermore, we developed and validated a five‐gene signature for better application of this acquired stratification. Our data demonstrate the biological and prognostic heterogeneity within IDH wild‐type diffuse LGGs and deepen our molecular understandi‐g of this tumor entity. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Wu, Fan↗
Monocarboxylate transporters in breast cancer and adipose tissue are novel biomarkers and potential therapeutic targets
Monocarboxylate transporters (MCTs) are transmembrane proteins that control the lactate metabolism and associated with poor prognosis in solid tumours including breast cancer (BC). This study aimed to evaluate the clinical and prognostic value of MCTs used by immunohistochemistry and quantum dots-based fluorescent imaging technique in BC and surrounding stroma with emphasis on the interaction between tumour and stroma. Moreover, the data from The Cancer Genome Atlas (TCGA) was analyzed to evaluate the association between MCTs mRNA expression and prognosis of breast cancer patients. Our study found that MCT1 overexpression was observed in hormone receptor-negative and high-proliferation subtypes. High expression of MCT1 and MCT4 in tumour tissues was associated with poor patient outcome; further the correlation between MCT1 expression and poor prognosis in breast cancer was further strengthened when combined with MCT4 overexpression in the adjacent adipose tissue. These results demonstrate that MCTs tend to play a role in the aggressive BC subtypes through the dynamic interaction between breast cancer cells and adipocytes, and developing therapeutics to block this interaction will be a promising strategy in cancer therapy.
60 APPLIED LIFE SCIENCES↗
ERα is a negative regulator of PD-L1 gene transcription in breast cancer
Highlights: • PD-L1 mRNA level is much lower in ERα-positive breast cancer cell lines. • E2 treatment inhibits PD-L1 gene transcription in ERα-positive MCF7 cells. • Ectopic expression of ERα down-regulates PD-L1 gene expression in ERα-negative MDA-MB-231 cells. • ERα expression is negatively correlated with PD-L1 expression in ERα-positive breast cancer. The programmed death-ligand 1 (PD-L1) expression by tumors results in potent antitumor immune suppression through binding to programmed death-1 (PD-1) on T cells and subsequent inhibition of T cells activity. Although recent pathological studies have shown that PD-L1 is actively expressed in certain ERα-negative breast cancer, little is known about whether ER signaling regulates PD-L1 gene expression. Here, we investigated the relationship between ERα and PD-L1 in breast cancer. Analysis of Comprehensive Cell Line Encyclopedia (CCLE) data showed that the average mRNA level of PD-L1 in ERα-positive breast cancer cell lines was significantly lower than that in ERα-negative breast cancer cell lines. E2 treatment inhibited PD-L1 mRNA expression in hormone-depleted ERα-positive MCF7 cells. Moreover, ectopic expression of ERα in triple-negative MDA-MB-231 cells reduced PD-L1 mRNA and protein expression. Consistently, analysis of The Cancer Genome Atlas (TCGA) data revealed an inverse correlation between ERα and PD-L1 expression in ERα-positive breast cancer. Taken together, our results identify ERα as a negative regulator of PD-L1 gene transcription in breast cancer cells, suggesting that ERα loss-of-function may facilitate the immune evasion of breast cancer cells via up-regulation of PD-L1.
60 APPLIED LIFE SCIENCES↗