Clonal populations of a human TNBC model display significant functional heterogeneity and divergent growth dynamics in distinct contexts

Single-cell transcriptome analysis reveals dynamic changes of the preclinical A549 cancer models, and the mechanism of dacomitinib

The in vitro A549 cells, and A549 xenografts in nude mouse, were two commonly used models for anti-cancer drug discovery. However, the biological and molecular characteristics of these two classic models, and also the dynamic transcriptome changes after dacomitinib exposure remains elusive. We performed single-cell RNA sequencing to define the transcriptome profile at single-cell resolution, and processed tumor samples for bulk RNA and protein analysis to validate the differently expressed genes. Transcriptome profiling revealed that the in vitro A549 cells are heterogeneous. The minimal subpopulation of the in vitro A549 cells, which were characterized by the signature of response to unfolded protein, became the overriding subpopulation of the xenografts. The EGFR non-activating A549 cells were resistant to dacomitinib in vitro, while A549 xenografts were comparatively sensitive as EGFR-activating HCC827 xenografts. Dacomitinib inhibited MAPK signaling pathway, and increased the immune response in the A549 xenografts. A phagocytosis checkpoint stanniocalcin-1 (STC1) was significantly inhibited in dacomitinib-treated xenografts. So here our study gives the first insight of the heterogeneity of the two classic models, and the translational potential of dacomitinib being used into a broader patient population rather than EGFR common activating mutation.

Phenotypic heterogeneity drives differential disease outcome in a mouse model of triple negative breast cancer

The triple negative breast cancer (TNBC) subtype is one of the most aggressive forms of breast cancer that has poor clinical outcome and is an unmet clinical challenge. Accumulating evidence suggests that intratumoral heterogeneity or the presence of phenotypically distinct cell populations within a tumor play a crucial role in chemoresistance, tumor progression and metastasis. An increased understanding of the molecular regulators of intratumoral heterogeneity is crucial to the development of effective therapeutic strategies in TNBC. To this end, we used an unbiased approach to identify a molecular mediator of intratumoral heterogeneity in breast cancer by isolating two tumor cell populations (T1 and T2) from the 4T1 TNBC model. Phenotypic characterization revealed that the cells are different in terms of their morphology, proliferation and self-renewal ability in vitro as well as primary tumor formation and metastatic potential in vivo. Bioinformatic analysis followed by Kaplan Meier survival analysis in TNBC patients identified Metastasis associated colon cancer 1 (Macc1) as one of the top candidate genes mediating the aggressive phenotype in the T1 tumor cells. The role of Macc1 in regulating the proliferative phenotype was validated and taken forward in a therapeutic context with Lovastatin, a small molecule transcriptional inhibitor of Macc1 to target the T1 cell population. This study increases our understanding of the molecular underpinnings of intratumoral heterogeneity in breast cancer that is critical to improve the treatment of women currently living with the highly aggressive TNBC subtype.

Diverse clonal fates emerge upon drug treatment of homogeneous cancer cells

Even among genetically identical cancer cells, resistance to therapy frequently emerges from a small subset of those cells1-7. Molecular differences in rare individual cells in the initial population enable certain cells to become resistant to therapy7-9; however, comparatively little is known about the variability in the resistance outcomes. Here we develop and apply FateMap, a framework that combines DNA barcoding with single-cell RNA sequencing, to reveal the fates of hundreds of thousands of clones exposed to anti-cancer therapies. We show that resistant clones emerging from single-cell-derived cancer cells adopt molecularly, morphologically and functionally distinct resistant types. These resistant types are largely predetermined by molecular differences between cells before drug addition and not by extrinsic factors. Changes in the dose and type of drug can switch the resistant type of an initial cell, resulting in the generation and elimination of certain resistant types. Samples from patients show evidence for the existence of these resistant types in a clinical context. We observed diversity in resistant types across several single-cell-derived cancer cell lines and cell types treated with a variety of drugs. The diversity of resistant types as a result of the variability in intrinsic cell states may be a generic feature of responses to external cues.

Molecular Characterization and Landscape of Breast cancer Models from a multi-omics Perspective

Breast cancer is well-known to be a highly heterogenous disease. This facet of cancer makes finding a research model that mirrors the disparate intrinsic features challenging. With advances in multi-omics technologies, establishing parallels between the various models and human tumors is increasingly intricate. Here we review the various model systems and their relation to primary breast tumors using available omics data platforms. Among the research models reviewed here, breast cancer cell lines have the least resemblance to human tumors since they have accumulated many mutations and copy number alterations during their long use. Moreover, individual proteomic and metabolomic profiles do not overlap with the molecular landscape of breast cancer. Interestingly, omics analysis revealed that the initial subtype classification of some breast cancer cell lines was inappropriate. In cell lines the major subtypes are all well represented and share some features with primary tumors. In contrast, patient-derived xenografts (PDX) and patient-derived organoids (PDO) are superior in mirroring human breast cancers at many levels, making them suitable models for drug screening and molecular analysis. While patient derived organoids are spread across luminal, basal- and normal-like subtypes, the PDX samples were initially largely basal but other subtypes have been increasingly described. Murine models offer heterogenous tumor landscapes, inter and intra-model heterogeneity, and give rise to tumors of different phenotypes and histology. Murine models have a reduced mutational burden compared to human breast cancer but share some transcriptomic resemblance, and representation of many breast cancer subtypes can be found among the variety subtypes. To date, while mammospheres and three- dimensional cultures lack comprehensive omics data, these are excellent models for the study of stem cells, cell fate decision and differentiation, and have also been used for drug screening. Therefore, this review explores the molecular landscapes and characterization of breast cancer research models by comparing recent published multi-omics data and analysis.

RNA m6A reader IGF2BP3 promotes metastasis of triple-negative breast cancer via SLIT2 repression

Triple-negative breast cancer (TNBC) is a group of fatal malignancies characterized by high metastatic capacity, the underlying mechanisms of which remain largely elusive. We have found here that insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3) is highly expressed in TNBC and correlates clinically with distant metastasis-free survival of TNBC patients. IGF2BP3 promotes the migration and invasion capabilities of TNBC cells dependent upon cellular RNA N6-methyladenosine (m6A) modification. Mechanistically, IGF2BP3 binds to and destabilizes m6A-methylated mRNA of the extracellular matrix glycoprotein, SLIT2, impairs its downstream signaling via the cognate receptor ROBO1, and consequently triggers the activation of canonical PI3K/AKT and MEK/ERK pathways. The IGF2BP3/SLIT2 axis is critically involved in the regulation of TNBC metastasis in vivo. These findings shed light into the regulatory network of distant metastasis of breast cancer and provide rationale for targeting the m6A machinery in the treatment of TNBC.

Integrins and Epithelial-Mesenchymal Cooperation in the Tumor Microenvironment of Muscle-Invasive Lethal Cancers

Muscle-invasive lethal carcinomas traverse into and through this specialized biophysical and growth factor enriched microenvironment. We will highlight cancers that originate in organs surrounded by smooth muscle, which presents a barrier to dissemination, including prostate, bladder, esophageal, gastric, and colorectal cancers. We propose that the heterogeneity of cell-cell and cell-ECM adhesion receptors is an important driver of aggressive tumor networks with functional consequences for progression. Phenotype heterogeneity of the tumor provides a biophysical advantage for tumor network invasion through the tensile muscle and survival of the tumor network. We hypothesize that a functional epithelial-mesenchymal cooperation (EMC)exists within the tumor invasive network to facilitate tumor escape from the primary organ, invasion and traversing of muscle, and navigation to metastatic sites. Cooperation between specific epithelial cells within the tumor and stromal (mesenchymal) cells interacting with the tumor is illustrated using the examples of laminin-binding adhesion molecules—especially integrins—and their response to growth and inflammatory factors in the tumor microenvironment. The cooperation between cell-cell (E-cadherin, CDH1) and cell-ECM (α6 integrin, CD49f) expression and growth factor receptors is highlighted within poorly differentiated human tumors associated with aggressive disease. Cancer-associated fibroblasts are examined for their role in the tumor microenvironment in generating and organizing various growth factors. Cellular structural proteins are potential utility markers for future spatial profiling studies. We also examine the special characteristics of the smooth muscle microenvironment and how invasion by a primary tumor can alter this environment and contribute to tumor escape via cooperation between epithelial and stromal cells. This cooperative state allows the heterogenous tumor clusters to be shaped by various growth factors, co-opt or evade immune system response, adapt from hypoxic to normoxic conditions, adjust to varying energy sources, and survive radiation and chemotherapeutic interventions. Understanding the epithelial-mesenchymal cooperation in early tumor invasive networks holds potential for both identifying early biomarkers of the aggressive transition and identification of novel agents to prevent the epithelial-mesenchymal cooperation phenotype. Epithelial-mesenchymal cooperation is likely to unveil new tumor subtypes to aid in selection of appropriate therapeutic strategies.