An epigenetic switch involving NF-kappaB, Lin28, Let-7 MicroRNA, and IL6 links inflammation to cell transformation.

Inflammation is linked clinically and epidemiologically to cancer, and NF-kappaB appears to play a causative role, but the mechanisms are poorly understood. We show that transient activation of Src oncoprotein can mediate an epigenetic switch from immortalized breast cells to a stably transformed line that forms self-renewing mammospheres that contain cancer stem cells. Src activation triggers an inflammatory response mediated by NF-kappaB that directly activates Lin28 transcription and rapidly reduces let-7 microRNA levels. Let-7 directly inhibits IL6 expression, resulting in higher levels of IL6 than achieved by NF-kappaB activation. IL6-mediated activation of the STAT3 transcription factor is necessary for transformation, and IL6 activates NF-kappaB, thereby completing a positive feedback loop. This regulatory circuit operates in other cancer cells lines, and its transcriptional signature is found in human cancer tissues. Thus, inflammation activates a positive feedback loop that maintains the epigenetic transformed state for many generations in the absence of the inducing signal.

STAT3 activation of miR-21 and miR-181b-1 via PTEN and CYLD are part of the epigenetic switch linking inflammation to cancer.

A transient inflammatory signal can initiate an epigenetic switch from nontransformed to cancer cells via a positive feedback loop involving NF-kappaB, Lin28, let-7, and IL-6. We identify differentially regulated microRNAs important for this switch and putative transcription factor binding sites in their promoters. STAT3, a transcription factor activated by IL-6, directly activates miR-21 and miR-181b-1. Remarkably, transient expression of either microRNA induces the epigenetic switch. MiR-21 and miR-181b-1, respectively, inhibit PTEN and CYLD tumor suppressors, leading to increased NF-kappaB activity required to maintain the transformed state. These STAT3-mediated regulatory circuits are required for the transformed state in diverse cell lines and tumor growth in xenografts, and their transcriptional signatures are observed in colon adenocarcinomas. Thus, STAT3 is not only a downstream target of IL-6 but, with miR-21, miR-181b-1, PTEN, and CYLD, is part of the positive feedback loop that underlies the epigenetic switch that links inflammation to cancer.

Loss of miR-200 inhibition of Suz12 leads to polycomb-mediated repression required for the formation and maintenance of cancer stem cells.

In an inducible oncogenesis model, the miR-200 family is inhibited during CSC formation but not transformation, and inhibition of miR-200b increases CSC formation. Interestingly, miR-200b directly targets Suz12, a subunit of a polycomb repressor complex (PRC2). Loss of miR-200 during CSC formation increases Suz12 expression, Suz12 binding, H3-K27 trimethylation, and Polycomb-mediated repression of the E-cadherin gene. miR-200b expression or Suz12 depletion blocks the formation and maintenance of mammospheres, and in combination with chemotherapy suppresses tumor growth and prolongs remission in mouse xenografts. Conversely, ectopic expression of Suz12 in transformed cells is sufficient to generate CSCs. The miR-200b-Suz12-cadherin pathway is important for CSC growth and invasive ability in genetically distinct breast cancer cells, and its transcriptional signature is observed in metastatic breast tumors. The interaction between miR-200 and Suz12 is highly conserved, suggesting that it represents an ancient regulatory mechanism to control the growth and function of stem cells.

Metformin inhibits the inflammatory response associated with cellular transformation and cancer stem cell growth.

Metformin, the first-line drug for treating diabetes, inhibits cellular transformation and selectively kills cancer stem cells in breast cancer cell lines. In a Src-inducible model of cellular transformation, metformin inhibits the earliest known step in the process, activation of the inflammatory transcription factor NF-κB. Metformin strongly delays cellular transformation in a manner similar to that occurring upon a weaker inflammatory stimulus. Conversely, inhibition of transformation does not occur if metformin is added after the initial inflammatory stimulus. The antitransformation effect of metformin can be bypassed by overexpression of Lin28B or IL1ß, downstream targets of NF-κB. Metformin preferentially inhibits nuclear translocation of NF-κB and phosphorylation of STAT3 in cancer stem cells compared with non-stem cancer cells in the same population. The ability of metformin to block tumor growth and prolong remission in xenografts in combination with doxorubicin is associated with decreased function of the inflammatory feedback loop. Lastly, metformin-based combinatorial therapy is effective in xenografts involving inflammatory prostate and melanoma cell lines, whereas it is ineffective in noninflammatory cell lines from these lineages. Taken together, our observations suggest that metformin inhibits a signal transduction pathway that results in an inflammatory response. As metformin alters energy metabolism in diabetics, we speculate that metformin may block a metabolic stress response that stimulates the inflammatory pathway associated with a wide variety of cancers.

Inducible formation of breast cancer stem cells and their dynamic equilibrium with non-stem cancer cells via IL6 secretion.

Tumors are often heterogeneous, being composed of multiple cell types with different phenotypic and molecular properties. Cancer stem-like cells (CSCs) are a highly tumorigenic cell type found in developmentally diverse tumors or cancer cell lines, and they are often resistant to standard chemotherapeutic drugs. The origins of CSCs and their relationships to nonstem cancer cells (NSCCs) are poorly understood. In an inducible breast oncogenesis model, CSCs are generated from nontransformed cells at a specific time during the transformation process, but CSC formation is not required for transformation. MicroRNA profiles indicate that CSCs and NSCCs are related, but different cell types arising from a common nontransformed population. Interestingly, medium from the transformed population stimulates NSCCs to become CSCs, and conversion of NSCCs to CSCs occurs in mouse xenografts. Furthermore, IL6 is sufficient to convert NSCCs to CSCs in genetically different breast cell lines, human breast tumors, and a prostate cell line. Thus, breast and prostate CSCs and NSCCs do not represent distinct epigenetic states, and these CSCs do not behave as or arise from classic stem cells. Instead, tumor heterogeneity involves a dynamic equilibrium between CSCs and NSCCs mediated by IL6 and activation of the inflammatory feedback loop required for oncogenesis. This dynamic equilibrium provides an additional rationale for combining conventional chemotherapy with metformin, which selectively inhibits CSCs.

Maveropepimut-S, a DPX-Based Immune-Educating Therapy, Shows Promising and Durable Clinical Benefit in Patients with Recurrent Ovarian Cancer, a Phase II Trial.

PURPOSE: Patients with platinum-resistant ovarian cancer respond poorly to existing therapies. Hence there is a need for more effective treatments. PATIENTS AND METHODS: The DeCidE1 trial is a multicenter, randomized, open-label, single-arm phase II study to evaluate the safety and effectiveness of maveropepimut-S with cyclophosphamide in patients with recurrent ovarian cancer. Median follow-up for evaluable subjects was 4.4 months. Data were collected from March 2019 to June 2021. Subjects received two injections of 0.25 mL maveropepimut-S 3 weeks apart, followed by one 0.1-mL doses, every 8 weeks up to progression. Oral cyclophosphamide, 50 mg twice daily, was administered in repeating weekly on and off cycles. RESULTS: Twenty-two patients were enrolled. Median age was 58 years (38-78 years). Among the evaluable population, the objective response rate (ORR) was 21% [90% confidence interval (CI), 7.5%-41.9%], with a disease control rate (DCR) of 63% (90% CI, 41.8%-81.3%), including 4 (21%) patients with partial responses, 8 (42%) stable disease, and 7 (37%) progressive disease. The ORRs were consistent across subgroups based on platinum sensitivity, and DCR was higher in the platinum-resistant subpopulation. Four SD patients maintained clinical benefit up to 25 months. Most treatment-related adverse events (TRAE) were grade 1 and 2 (87% of unique events). Most common AEs were injection site reactions. Eight subjects reported grade 3 and no grade 4 AEs. Survivin-specific T-cell responses were observed in treated patients with clinical benefit. CONCLUSIONS: Maveropepimut-S with intermittent low-dose cyclophosphamide is well-tolerated, with clinical benefit for patients with recurrent ovarian cancer. Observed responses are irrespective of the platinum status.

Reverse Translating Molecular Determinants of Anti-Programmed Death 1 Immunotherapy Response in Mouse Syngeneic Tumor Models.

Targeting the programmed death 1/programmed death ligand 1 (PD-1/PD-L1) pathway with immunotherapy has revolutionized the treatment of many cancers. Somatic tumor mutational burden (TMB) and T-cell-inflamed gene expression profile (GEP) are clinically validated pan-tumor genomic biomarkers that can predict responsiveness to anti-PD-1/PD-L1 monotherapy in many tumor types. We analyzed the association between these biomarkers and the efficacy of PD-1 inhibitor in 11 commonly used preclinical syngeneic tumor mouse models using murinized rat anti-mouse PD-1 DX400 antibody muDX400, a surrogate for pembrolizumab. Response to muDX400 treatment was broadly classified into three categories: highly responsive, partially responsive, and intrinsically resistant to therapy. Molecular and cellular profiling validated differences in immune cell infiltration and activation in the tumor microenvironment of muDX400-responsive tumors. Baseline and on-treatment genomic analysis showed an association between TMB, murine T-cell-inflamed gene expression profile (murine-GEP), and response to muDX400 treatment. We extended our analysis to investigate a canonical set of cancer and immune biology-related gene signatures, including signatures of angiogenesis, myeloid-derived suppressor cells, and stromal/epithelial-to-mesenchymal transition/TGFß biology previously shown to be inversely associated with the clinical efficacy of immune checkpoint blockade. Finally, we evaluated the association between murine-GEP and preclinical efficacy with standard-of-care chemotherapy or antiangiogenic agents that previously demonstrated promising clinical activity, in combination with muDX400. Our profiling studies begin to elucidate the underlying biological mechanisms of response and resistance to PD-1/PD-L1 blockade represented by these models, thereby providing insight into which models are most appropriate for the evaluation of orthogonal combination strategies.

Differential analysis for high density tiling microarray data.

BACKGROUND: High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an in-vivo system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program. RESULTS: We have proposed a novel approach, based on a piece-wise function - to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias. CONCLUSION: The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value < 0.003; it is most significant at the 5' end of genes, at a p-value < 10-13. The prototype R code has been made available as supplementary material [see Additional file 1].

Distinct mechanisms for repression of RNA polymerase III transcription by the retinoblastoma tumor suppressor protein.

The retinoblastoma (RB) protein represses global RNA polymerase III transcription of genes that encode nontranslated RNAs, potentially to control cell growth. However, RNA polymerase III-transcribed genes exhibit diverse promoter structures and factor requirements for transcription, and a universal mechanism explaining global repression is uncertain. We show that RB represses different classes of RNA polymerase III-transcribed genes via distinct mechanisms. Repression of human U6 snRNA (class 3) gene transcription occurs through stable promoter occupancy by RB, whereas repression of adenovirus VAI (class 2) gene transcription occurs in the absence of detectable RB-promoter association. Endogenous RB binds to a human U6 snRNA gene in both normal and cancer cells that maintain functional RB but not in HeLa cells whose RB function is disrupted by the papillomavirus E7 protein. Both U6 promoter association and transcriptional repression require the A/B pocket domain and C region of RB. These regions of RB contribute to U6 promoter targeting through numerous interactions with components of the U6 general transcription machinery, including SNAP(C) and TFIIIB. Importantly, RB also concurrently occupies a U6 promoter with RNA polymerase III during repression. These observations suggest a novel mechanism for RB function wherein RB can repress U6 transcription at critical steps subsequent to RNA polymerase III recruitment.

Rank-statistics based enrichment-site prediction algorithm developed for chromatin immunoprecipitation on chip experiments.

BACKGROUND: High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. Tiling arrays are increasingly used in chromatin immunoprecipitation (IP) experiments (ChIP on chip). ChIP on chip facilitates the generation of genome-wide maps of in-vivo interactions between DNA-associated proteins including transcription factors and DNA. Analysis of the hybridization of an immunoprecipitated sample to a tiling array facilitates the identification of ChIP-enriched segments of the genome. These enriched segments are putative targets of antibody assayable regulatory elements. The enrichment response is not ubiquitous across the genome. Typically 5 to 10% of tiled probes manifest some significant enrichment. Depending upon the factor being studied, this response can drop to less than 1%. The detection and assessment of significance for interactions that emanate from non-canonical and/or un-annotated regions of the genome is especially challenging. This is the motivation behind the proposed algorithm. RESULTS: We have proposed a novel rank and replicate statistics-based methodology for identifying and ascribing statistical confidence to regions of ChIP-enrichment. The algorithm is optimized for identification of sites that manifest low levels of enrichment but are true positives, as validated by alternative biochemical experiments. Although the method is described here in the context of ChIP on chip experiments, it can be generalized to any treatment-control experimental design. The results of the algorithm show a high degree of concordance with independent biochemical validation methods. The sensitivity and specificity of the algorithm have been characterized via quantitative PCR and independent computational approaches. CONCLUSION: The algorithm ranks all enrichment sites based on their intra-replicate ranks and inter-replicate rank consistency. Following the ranking, the method allows segmentation of sites based on a meta p-value, a composite array signal enrichment criterion, or a composite of these two measures. The sensitivities obtained subsequent to the segmentation of data using a meta p-value of 10-5, an array signal enrichment of 0.2 and a composite of these two values are 88%, 87% and 95%, respectively.

MCL1 and BCL-xL levels in solid tumors are predictive of dinaciclib-induced apoptosis.

Dinaciclib is a potent CDK1, 2, 5 and 9 inhibitor being developed for the treatment of cancer. Additional understanding of antitumor mechanisms and identification of predictive biomarkers are important for its clinical development. Here we demonstrate that while dinaciclib can effectively block cell cycle progression, in vitro and in vivo studies, coupled with mouse and human pharmacokinetics, support a model whereby induction of apoptosis is a main mechanism of dinaciclib's antitumor effect and relevant to the clinical duration of exposure. This was further underscored by kinetics of dinaciclib-induced downregulation of the antiapoptotic BCL2 family member MCL1 and correlation of sensitivity with the MCL1-to-BCL-xL mRNA ratio or MCL1 amplification in solid tumor models in vitro and in vivo. This MCL1-dependent apoptotic mechanism was additionally supported by synergy with the BCL2, BCL-xL and BCL-w inhibitor navitoclax (ABT-263). These results provide the rationale for investigating MCL1 and BCL-xL as predictive biomarkers for dinaciclib antitumor response and testing combinations with BCL2 family member inhibitors.

Preclinical evaluation of the WEE1 inhibitor MK-1775 as single-agent anticancer therapy.

Inhibition of the DNA damage checkpoint kinase WEE1 potentiates genotoxic chemotherapies by abrogating cell-cycle arrest and proper DNA repair. However, WEE1 is also essential for unperturbed cell division in the absence of extrinsic insult. Here, we investigate the anticancer potential of a WEE1 inhibitor, independent of chemotherapy, and explore a possible cellular context underlying sensitivity to WEE1 inhibition. We show that MK-1775, a potent and selective ATP-competitive inhibitor of WEE1, is cytotoxic across a broad panel of tumor cell lines and induces DNA double-strand breaks. MK-1775-induced DNA damage occurs without added chemotherapy or radiation in S-phase cells and relies on active DNA replication. At tolerated doses, MK-1775 treatment leads to xenograft tumor growth inhibition or regression. To begin addressing potential response markers for MK-1775 monotherapy, we focused on PKMYT1, a kinase functionally related to WEE1. Knockdown of PKMYT1 lowers the EC(50) of MK-1775 by five-fold but has no effect on the cell-based response to other cytotoxic drugs. In addition, knockdown of PKMYT1 increases markers of DNA damage, γH2AX and pCHK1(S345), induced by MK-1775. In a post hoc analysis of 305 cell lines treated with MK-1775, we found that expression of PKMYT1 was below average in 73% of the 33 most sensitive cell lines. Our findings provide rationale for WEE1 inhibition as a potent anticancer therapy independent of a genotoxic partner and suggest that low PKMYT1 expression could serve as an enrichment biomarker for MK-1775 sensitivity.

Metformin decreases the dose of chemotherapy for prolonging tumor remission in mouse xenografts involving multiple cancer cell types.

Metformin, the first-line drug for treating diabetes, selectively kills the chemotherapy resistant subpopulation of cancer stem cells (CSC) in genetically distinct types of breast cancer cell lines. In mouse xenografts, injection of metformin and the chemotherapeutic drug doxorubicin near the tumor is more effective than either drug alone in blocking tumor growth and preventing relapse. Here, we show that metformin is equally effective when given orally together with paclitaxel, carboplatin, and doxorubicin, indicating that metformin works together with a variety of standard chemotherapeutic agents. In addition, metformin has comparable effects on tumor regression and preventing relapse when combined with a four-fold reduced dose of doxorubicin that is not effective as a monotherapy. Finally, the combination of metformin and doxorubicin prevents relapse in xenografts generated with prostate and lung cancer cell lines. These observations provide further evidence for the CSC hypothesis for cancer relapse, an experimental rationale for using metformin as part of combinatorial therapy in a variety of clinical settings, and for reducing the chemotherapy dose in cancer patients.

A transcriptional signature and common gene networks link cancer with lipid metabolism and diverse human diseases.

Transcriptional profiling of two isogenic models of transformation identifies a gene signature linking cancer with inflammatory and metabolic diseases. In accord with this common transcriptional program, many drugs used for treatment of diabetes and cardiovascular diseases inhibit transformation and tumor growth. Unexpectedly, lipid metabolism genes are important for transformation and are upregulated in cancer tissues. As in atherosclerosis, oxidized LDL and its receptor OLR1 activate the inflammatory pathway through NF-kappaB, leading to transformation. OLR1 is important for maintaining the transformed state in developmentally diverse cancer cell lines and for tumor growth, suggesting a molecular connection between cancer and atherosclerosis. We suggest that the interplay between this common transcriptional program and cell-type-specific factors gives rise to phenotypically disparate human diseases.

Metformin selectively targets cancer stem cells, and acts together with chemotherapy to block tumor growth and prolong remission.

The cancer stem cell hypothesis suggests that, unlike most cancer cells within a tumor, cancer stem cells resist chemotherapeutic drugs and can regenerate the various cell types in the tumor, thereby causing relapse of the disease. Thus, drugs that selectively target cancer stem cells offer great promise for cancer treatment, particularly in combination with chemotherapy. Here, we show that low doses of metformin, a standard drug for diabetes, inhibits cellular transformation and selectively kills cancer stem cells in four genetically different types of breast cancer. The combination of metformin and a well-defined chemotherapeutic agent, doxorubicin, kills both cancer stem cells and non-stem cancer cells in culture. Furthermore, this combinatorial therapy reduces tumor mass and prevents relapse much more effectively than either drug alone in a xenograft mouse model. Mice seem to remain tumor-free for at least 2 months after combinatorial therapy with metformin and doxorubicin is ended. These results provide further evidence supporting the cancer stem cell hypothesis, and they provide a rationale and experimental basis for using the combination of metformin and chemotherapeutic drugs to improve treatment of patients with breast (and possibly other) cancers.

The small nuclear RNA-activating protein 190 Myb DNA binding domain stimulates TATA box-binding protein-TATA box recognition.

Human U6 small nuclear RNA (snRNA) gene transcription by RNA polymerase III requires cooperative promoter binding involving the snRNA-activating protein complex (SNAP(c)) and the TATA-box binding protein (TBP). To investigate the role of SNAP(c) for TBP function at U6 promoters, TBP recruitment assays were performed using full-length TBP and a mini-SNAP(c) containing SNAP43, SNAP50, and a truncated SNAP190. Mini-SNAP(c) efficiently recruits TBP to the U6 TATA box, and two SNAP(c) subunits, SNAP43 and SNAP190, directly interact with the TBP DNA binding domain. Truncated SNAP190 containing only the Myb DNA binding domain is sufficient for TBP recruitment to the TATA box. Therefore, the SNAP190 Myb domain functions both to specifically recognize the proximal sequence element present in the core promoters of human snRNA genes and to stimulate TBP recognition of the neighboring TATA box present in human U6 snRNA promoters. The SNAP190 Myb domain also stimulates complex assembly with TBP and Brf2, a subunit of a snRNA-specific TFIIIB complex. Thus, interactions between the DNA binding domains of SNAP190 and TBP at juxtaposed promoter elements define the assembly of a RNA polymerase III-specific preinitiation complex.