Exploiting DNA Replication Stress as a Therapeutic Strategy for Breast Cancer

The expression patterns of different cell types and their interactions in the tumor microenvironment are predictive of breast cancer patient response to neoadjuvant chemotherapy

The tumor microenvironment (TME) is a complex ecosystem of diverse cell types whose interactions govern tumor growth and clinical outcome. While the TME's impact on immunotherapy has been extensively studied, its role in chemotherapy response remains less explored. To address this, we developed DECODEM (DEcoupling Cell-type-specific Outcomes using DEconvolution and Machine learning), a generic computational framework leveraging cellular deconvolution of bulk transcriptomics to associate the gene expression of individual cell types in the TME with clinical response. Employing DECODEM to analyze the gene expression of breast cancer (BC) patients treated with neoadjuvant chemotherapy, we find that the gene expression of specific immune cells (myeloid, plasmablasts, B-cells) and stromal cells (endothelial, normal epithelial, CAFs) are highly predictive of chemotherapy response, going beyond that of the malignant cells. These findings are further tested and validated in a single-cell cohort of triple negative breast cancer. To investigate the possible role of immune cell-cell interactions (CCIs) in mediating chemotherapy response, we extended DECODEM to DECODEMi to identify such CCIs, validated in single-cell data. Our findings highlight the importance of active pre-treatment immune infiltration for chemotherapy success. The tools developed here are made publicly available and are applicable for studying the role of the TME in mediating response from readily available bulk tumor expression in a wide range of cancer treatments and indications.

Cancer Mutations Converge on a Collection of Protein Assemblies to Predict Resistance to Replication Stress

Rapid proliferation is a hallmark of cancer associated with sensitivity to therapeutics that cause DNA replication stress (RS). Many tumors exhibit drug resistance, however, via molecular pathways that are incompletely understood. Here, we develop an ensemble of predictive models that elucidate how cancer mutations impact the response to common RS-inducing (RSi) agents. The models implement recent advances in deep learning to facilitate multidrug prediction and mechanistic interpretation. Initial studies in tumor cells identify 41 molecular assemblies that integrate alterations in hundreds of genes for accurate drug response prediction. These cover roles in transcription, repair, cell-cycle checkpoints, and growth signaling, of which 30 are shown by loss-of-function genetic screens to regulate drug sensitivity or replication restart. The model translates to cisplatin-treated cervical cancer patients, highlighting an RTK-JAK-STAT assembly governing resistance. This study defines a compendium of mechanisms by which mutations affect therapeutic responses, with implications for precision medicine.

SIGNIFICANCE

Zhao and colleagues use recent advances in machine learning to study the effects of tumor mutations on the response to common therapeutics that cause RS. The resulting predictive models integrate numerous genetic alterations distributed across a constellation of molecular assemblies, facilitating a quantitative and interpretable assessment of drug response. This article is featured in Selected Articles from This Issue, p. 384.

Key Proteins of Replication Stress Response and Cell Cycle Control as Cancer Therapy Targets

Replication stress (RS) is a characteristic state of cancer cells as they tend to exchange precision of replication for fast proliferation and increased genomic instability. To overcome the consequences of improper replication control, malignant cells frequently inactivate parts of their DNA damage response (DDR) pathways (the ATM-CHK2-p53 pathway), while relying on other pathways which help to maintain replication fork stability (ATR-CHK1). This creates a dependency on the remaining DDR pathways, vulnerability to further destabilization of replication and synthetic lethality of DDR inhibitors with common oncogenic alterations such as mutations of TP53, RB1, ATM, amplifications of MYC, CCNE1 and others. The response to RS is normally limited by coordination of cell cycle, transcription and replication. Inhibition of WEE1 and PKMYT1 kinases, which prevent unscheduled mitosis entry, leads to fragility of under-replicated sites. Recent evidence also shows that inhibition of Cyclin-dependent kinases (CDKs), such as CDK4/6, CDK2, CDK8/19 and CDK12/13 can contribute to RS through disruption of DNA repair and replication control. Here, we review the main causes of RS in cancers as well as main therapeutic targets-ATR, CHK1, PARP and their inhibitors.

Deoxyguanosine-Linked Bifunctional Inhibitor of SAMHD1 dNTPase Activity and Nucleic Acid Binding

Sterile alpha motif histidine-aspartate domain protein 1 (SAMHD1) is a deoxynucleotide triphosphohydrolase that exists in monomeric, dimeric, and tetrameric forms. It is activated by GTP binding to an A1 allosteric site on each monomer subunit, which induces dimerization, a prerequisite for dNTP-induced tetramerization. SAMHD1 is a validated drug target stemming from its inactivation of many anticancer nucleoside drugs leading to drug resistance. The enzyme also possesses a single-strand nucleic acid binding function that promotes RNA and DNA homeostasis by several mechanisms. To discover small molecule inhibitors of SAMHD1, we screened a custom ∼69 000-compound library for dNTPase inhibitors. Surprisingly, this effort yielded no viable hits and indicated that exceptional barriers for discovery of small molecule inhibitors existed. We then took a rational fragment-based inhibitor design approach using a deoxyguanosine (dG) A1 site targeting fragment. A targeted chemical library was synthesized by coupling a 5'-phosphoryl propylamine dG fragment (dGpC3NH2) to 376 carboxylic acids (RCOOH). Direct screening of the products (dGpC3NHCO-R) yielded nine initial hits, one of which (R = 3-(3'-bromo-[1,1'-biphenyl]), 5a) was investigated extensively. Amide 5a is a competitive inhibitor against GTP binding to the A1 site and induces inactive dimers that are deficient in tetramerization. Surprisingly, 5a also prevented ssDNA and ssRNA binding, demonstrating that the dNTPase and nucleic acid binding functions of SAMHD1 can be disrupted by a single small molecule. A structure of the SAMHD1-5a complex indicates that the biphenyl fragment impedes a conformational change in the C-terminal lobe that is required for tetramerization.

Cytosolic DNA accumulation promotes breast cancer immunogenicity via a STING-independent pathway

BACKGROUND

Immune checkpoint blockade (ICB) has revolutionized cancer treatment. However, ICB alone has demonstrated only benefit in a small subset of patients with breast cancer. Recent studies have shown that agents targeting DNA damage response improve the efficacy of ICB and promote cytosolic DNA accumulation. However, recent clinical trials have shown that these agents are associated with hematological toxicities. More effective therapeutic strategies are urgently needed.

METHODS

Primary triple negative breast cancer tumors were stained for cytosolic single-stranded DNA (ssDNA) using multiplex immunohistochemical staining. To increase cytosolic ssDNA, we genetically silenced TREX1. The role of tumor cytosolic ssDNA in promoting tumor immunogenicity and antitumor immune response was evaluated using murine breast cancer models.

RESULTS

We found the tumorous cytosolic ssDNA is associated with tumor-infiltrating lymphocyte in patients with triple negative breast cancer. TREX1 deficiency triggered a STING-independent innate immune response via DDX3X. Cytosolic ssDNA accumulation in tumors due to TREX1 deletion is sufficient to drastically improve the efficacy of ICB. We further identified a cytosolic ssDNA inducer CEP-701, which sensitized breast tumors to ICB without the toxicities associated with inhibiting DNA damage response.

CONCLUSIONS

This work demonstrated that cytosolic ssDNA accumulation promotes breast cancer immunogenicity and may be a novel therapeutic strategy to improve the efficacy of ICB with minimal toxicities.

Integrative bioinformatics analysis of WDHD1: a potential biomarker for pan-cancer prognosis, diagnosis, and immunotherapy

BACKGROUND

Although WD repeat and high-mobility group box DNA binding protein 1 (WDHD1) played an essential role in DNA replication, chromosome stability, and DNA damage repair, the panoramic picture of WDHD1 in human tumors remains unclear. Hence, this study aims to comprehensively characterize WDHD1 across 33 human cancers.

METHODS

Based on publicly available databases such as TCGA, GTEx, and HPA, we used a bioinformatics approach to systematically explore the genomic features and biological functions of WDHD1 in pan-cancer.

RESULTS

WDHD1 mRNA levels were significantly increased in more than 20 types of tumor tissues. Elevated WDHD1 expression was associated with significantly shorter overall survival (OS) in 10 tumors. Furthermore, in uterine corpus endometrial carcinoma (UCEC) and liver hepatocellular carcinoma (LIHC), WDHD1 expression was significantly associated with higher histological grades and pathological stages. In addition, WDHD1 had a high diagnostic value among 16 tumors (area under the ROC curve [AUC] > 0.9). Functional enrichment analyses suggested that WDHD1 probably participated in many oncogenic pathways such as E2F and MYC targets (false discovery rate [FDR] < 0.05), and it was involved in the processes of DNA replication and DNA damage repair (p.adjust < 0.05). WDHD1 expression also correlated with the half-maximal inhibitory concentrations (IC50) of rapamycin (4 out of 10 cancers) and paclitaxel (10 out of 10 cancers). Overall, WDHD1 was negatively associated with immune cell infiltration and might promote tumor immune escape. Our analysis of genomic alterations suggested that WDHD1 was altered in 1.5% of pan-cancer cohorts and the "mutation" was the predominant type of alteration. Finally, through correlation analysis, we found that WDHD1 might be closely associated with tumor heterogeneity, tumor stemness, mismatch repair (MMR), and RNA methylation modification, which were all processes associated with the tumor progression.

CONCLUSIONS

Our pan-cancer analysis of WDHD1 provides valuable insights into the genomic characterization and biological functions of WDHD1 in human cancers and offers some theoretical support for the future use of WDHD1-targeted therapies, immunotherapies, and chemotherapeutic combinations for the management of tumors.