Spatial molecular profiling of mixed invasive ductal and lobular breast cancers reveals heterogeneity in intrinsic molecular subtypes, oncogenic signatures, and mutations.

Mixed invasive ductal and lobular carcinoma (MDLC) is a rare histologic subtype of breast cancer displaying both E-cadherin positive ductal and E-cadherin negative lobular morphologies within the same tumor, posing challenges with regard to anticipated clinical management. It remains unclear whether these distinct morphologies also have distinct biology and risk of recurrence. Our spatially resolved transcriptomic, genomic, and single-cell profiling revealed clinically significant differences between ductal and lobular tumor regions including distinct intrinsic subtype heterogeneity - e.g., MDLC with triple-negative breast cancer (TNBC) or basal ductal and estrogen receptor positive (ER+) luminal lobular regions, distinct enrichment of cell cycle arrest/senescence and oncogenic (ER and MYC) signatures, genetic and epigenetic CDH1 inactivation in lobular but not ductal regions, and single-cell ductal and lobular subpopulations with unique oncogenic signatures further highlighting intraregional heterogeneity. Altogether, we demonstrated that the intratumoral morphological/histological heterogeneity within MDLC is underpinned by intrinsic subtype and oncogenic heterogeneity which may result in prognostic uncertainty and therapeutic dilemma.

Systems approach for congruence and selection of cancer models towards precision medicine.

Cancer models are instrumental as a substitute for human studies and to expedite basic, translational, and clinical cancer research. For a given cancer type, a wide selection of models, such as cell lines, patient-derived xenografts, organoids and genetically modified murine models, are often available to researchers. However, how to quantify their congruence to human tumors and to select the most appropriate cancer model is a largely unsolved issue. Here, we present Congruence Analysis and Selection of CAncer Models (CASCAM), a statistical and machine learning framework for authenticating and selecting the most representative cancer models in a pathway-specific manner using transcriptomic data. CASCAM provides harmonization between human tumor and cancer model omics data, systematic congruence quantification, and pathway-based topological visualization to determine the most appropriate cancer model selection. The systems approach is presented using invasive lobular breast carcinoma (ILC) subtype and suggesting CAMA1 followed by UACC3133 as the most representative cell lines for ILC research. Two additional case studies for triple negative breast cancer (TNBC) and patient-derived xenograft/organoid (PDX/PDO) are further investigated. CASCAM is generalizable to any cancer subtype and will authenticate cancer models for faithful non-human preclinical research towards precision medicine.

Estrogen regulation and functional role of FGFR4 in estrogen receptor positive breast cancer.

Background: Resistance to endocrine therapy is a major challenge of managing estrogen receptor positive (ER+) breast cancer. We previously reported frequent overexpression of FGFR4 in endocrine resistant cell lines and breast cancers that recurred and metastasized following endocrine therapy, suggesting FGFR4 as a potential driver of endocrine resistance. In this study, we investigated the role of FGFR4 in mediating endocrine resistance and explored the therapeutic potential of targeting FGFR4 in advanced breast cancer. Methods: A gene expression signature of FGFR4 activity was examined in ER+ breast cancer pre- and post-neoadjuvant endocrine therapy and the association between FGFR4 expression and patient survival was examined. A correlation analysis was used to uncover potential regulators of FGFR4 overexpression. To investigate if FGFR4 is necessary to drive endocrine resistance, we tested response to FGFR4 inhibition in long term estrogen deprived (LTED) cells and their paired parental cells. Doxycycline inducible FGFR4 overexpression and knockdown cell models were generated to examine if FGFR4 was sufficient to confer endocrine resistance. Finally, we examined response to FGFR4 monotherapy or combination therapy with fulvestrant in breast cancer cell lines to explore the potential of FGFR4 targeted therapy for advanced breast cancer and assessed the importance of PAM50 subtype in response to FGFR4 inhibition. Results: A FGFR4 activity gene signature was significantly upregulated post neoadjuvant aromatase inhibitor treatment, and high FGFR4 expression predicted poorer survival in patients with ER+ breast cancer. Gene expression association analysis using TCGA, METABRIC and SCAN-B datasets uncovered ER as the most significant gene negatively correlated with FGFR4 expression. ER negatively regulates FGFR4 expression at both the mRNA and protein level across multiple ER+ breast cancer cell lines. Despite robust overexpression of FGFR4, LTED cells did not show enhanced responses to FGFR4 inhibition compared to parental cells. Similarly, FGFR4 overexpression, knockdown or hotspot mutations did not significantly alter response to endocrine treatment in ER+ cell lines, nor did FGFR4 and fulvestrant combination treatment show synergistic effects. The HER2-like subtype of breast cancer showed elevated expression of FGFR4 and an increased response to FGFR4 inhibition relative to other breast cancer subtypes. Conclusions: Despite ER-mediated upregulation of FGFR4 post endocrine therapy, our study does not support a general role of FGFR4 in mediating endocrine resistance in ER+ breast cancer. Our data suggests that specific genomic backgrounds such as HER2 expression may be required for FGFR4 function in breast cancer and should be further explored.

Spatial molecular profiling of mixed invasive ductal-lobular breast cancers reveals heterogeneity in intrinsic molecular subtypes, oncogenic signatures, and mutations.

Mixed invasive ductal and lobular carcinoma (MDLC) is a rare histologic subtype of breast cancer displaying both E-cadherin positive ductal and E-cadherin negative lobular morphologies within the same tumor, posing challenges with regard to anticipated clinical management. It remains unclear whether these distinct morphologies also have distinct biology and risk of recurrence. Our spatially-resolved transcriptomic, genomic, and single-cell profiling revealed clinically significant differences between ductal and lobular tumor regions including distinct intrinsic subtype heterogeneity (e.g., MDLC with TNBC/basal ductal and ER+/luminal lobular regions), distinct enrichment of senescence/dormancy and oncogenic (ER and MYC) signatures, genetic and epigenetic CDH1 inactivation in lobular, but not ductal regions, and single-cell ductal and lobular sub-populations with unique oncogenic signatures further highlighting intra-regional heterogeneity. Altogether, we demonstrated that the intra-tumoral morphological/histological heterogeneity within MDLC is underpinned by intrinsic subtype and oncogenic heterogeneity which may result in prognostic uncertainty and therapeutic dilemma. Significance: MDLC displays both ductal and lobular tumor regions. Our multi-omic profiling approach revealed that these morphologically distinct tumor regions harbor distinct intrinsic subtypes and oncogenic features that may cause prognostic uncertainty and therapeutic dilemma. Thus histopathological/molecular profiling of individual tumor regions may guide clinical decision making and benefit patients with MDLC, particularly in the advanced setting where there is increased reliance on next generation sequencing.

International survey on invasive lobular breast cancer identifies priority research questions.

There is growing awareness of the unique etiology, biology, and clinical presentation of invasive lobular breast cancer (ILC), but additional research is needed to ensure translation of findings into management and treatment guidelines. We conducted a survey with input from breast cancer physicians, laboratory-based researchers, and patients to analyze the current understanding of ILC, and identify consensus research questions. 1774 participants from 66 countries respondents self-identified as clinicians (N = 413), researchers (N = 376), and breast cancer patients and advocates (N = 1120), with some belonging to more than one category. The majority of physicians reported being very/extremely (41%) to moderately (42%) confident in describing the differences between ILC and invasive breast cancer of no special type (NST). Knowledge of histology was seen as important (73%) and as affecting treatment decisions (51%), and most agreed that refining treatment guidelines would be valuable (76%). 85% of clinicians have never powered a clinical trial to allow subset analysis for histological subtypes, but the majority would consider it, and would participate in an ILC clinical trials consortium. The majority of laboratory researchers, reported being and very/extremely (48%) to moderately (29%) confident in describing differences between ILC and NST. They reported that ILCs are inadequately presented in large genomic data sets, and that ILC models are insufficient. The majority have adequate access to tissue or blood from patients with ILC. The majority of patients and advocates (52%) thought that their health care providers did not sufficiently explain the unique features of ILC. They identified improvement of ILC screening/early detection, and identification of better imaging tools as top research priorities. In contrast, both researchers and clinicians identified understanding of endocrine resistance and identifying novel drugs that can be tested in clinical trials as top research priority. In summary, we have gathered information from an international community of physicians, researchers, and patients/advocates that we expect will lay the foundation for a community-informed collaborative research agenda, with the goal of improving management and personalizing treatment for patients with ILC.