NSABP FB-10: a phase Ib/II trial evaluating ado-trastuzumab emtansine (T-DM1) with neratinib in women with metastatic HER2-positive breast cancer.

BACKGROUND: We previously reported our phase Ib trial, testing the safety, tolerability, and efficacy of T-DM1 + neratinib in HER2-positive metastatic breast cancer patients. Patients with ERBB2 amplification in ctDNA had deeper and more durable responses. This study extends these observations with in-depth analysis of molecular markers and mechanisms of resistance in additional patients. METHODS: Forty-nine HER2-positive patients (determined locally) who progressed on-treatment with trastuzumab + pertuzumab were enrolled in this phase Ib/II study. Mutations and HER2 amplifications were assessed in ctDNA before (C1D1) and on-treatment (C2D1) with the Guardant360 assay. Archived tissue (TP0) and study entry biopsies (TP1) were assayed for whole transcriptome, HER2 copy number, and mutations, with Ampli-Seq, and centrally for HER2 with CLIA assays. Patient responses were assessed with RECIST v1.1, and Molecular Response with the Guardant360 Response algorithm. RESULTS: The ORR in phase II was 7/22 (32%), which included all patients who had at least one dose of study therapy. In phase I, the ORR was 12/19 (63%), which included only patients who were considered evaluable, having received their first scan at 6 weeks. Central confirmation of HER2-positivity was found in 83% (30/36) of the TP0 samples. HER2-amplified ctDNA was found at C1D1 in 48% (20/42) of samples. Patients with ctHER2-amp versus non-amplified HER2 ctDNA determined in C1D1 ctDNA had a longer median progression-free survival (PFS): 480 days versus 60 days (P = 0.015). Molecular Response scores were significantly associated with both PFS (HR 0.28, 0.09-0.90, P = 0.033) and best response (P = 0.037). All five of the patients with ctHER2-amp at C1D1 who had undetectable ctDNA after study therapy had an objective response. Patients whose ctHER2-amp decreased on-treatment had better outcomes than patients whose ctHER2-amp remained unchanged. HER2 RNA levels show a correlation to HER2 CLIA IHC status and were significantly higher in patients with clinically documented responses compared to patients with progressive disease (P = 0.03). CONCLUSIONS: The following biomarkers were associated with better outcomes for patients treated with T-DM1 + neratinib: (1) ctHER2-amp (C1D1) or in TP1; (2) Molecular Response scores; (3) loss of detectable ctDNA; (4) RNA levels of HER2; and (5) on-treatment loss of detectable ctHER2-amp. HER2 transcriptional and IHC/FISH status identify HER2-low cases (IHC 1+ or IHC 2+ and FISH negative) in these heavily anti-HER2 treated patients. Due to the small number of patients and samples in this study, the associations we have shown are for hypothesis generation only and remain to be validated in future studies. Clinical Trials registration NCT02236000.

Tumor Intrinsic Subtypes and Gene Expression Signatures in Early-Stage ERBB2/HER2-Positive Breast Cancer: A Pooled Analysis of CALGB 40601, NeoALTTO, and NSABP B-41 Trials.

Importance: Biologic features may affect pathologic complete response (pCR) and event-free survival (EFS) after neoadjuvant chemotherapy plus ERBB2/HER2 blockade in ERBB2/HER2-positive early breast cancer (EBC). Objective: To define the quantitative association between pCR and EFS by intrinsic subtype and by other gene expression signatures in a pooled analysis of 3 phase 3 trials: CALGB 40601, NeoALTTO, and NSABP B-41. Design, Setting, and Participants: In this retrospective pooled analysis, 1289 patients with EBC received chemotherapy plus either trastuzumab, lapatinib, or the combination, with a combined median follow-up of 5.5 years. Gene expression profiling by RNA sequencing was obtained from 758 samples, and intrinsic subtypes and 618 gene expression signatures were calculated. Data analyses were performed from June 1, 2020, to January 1, 2023. Main Outcomes and Measures: The association of clinical variables and gene expression biomarkers with pCR and EFS were studied by logistic regression and Cox analyses. Results: In the pooled analysis, of 758 women, median age was 49 years, 12% were Asian, 6% Black, and 75% were White. Overall, pCR results were associated with EFS in the ERBB2-enriched (hazard ratio [HR], 0.45; 95% CI, 0.29-0.70; P < .001) and basal-like (HR, 0.19; 95% CI, 0.04-0.86; P = .03) subtypes but not in luminal A or B tumors. Dual trastuzumab plus lapatinib blockade over trastuzumab alone had a trend toward EFS benefit in the intention-to-treat population; however, in the ERBB2-enriched subtype there was a significant and independent EFS benefit of trastuzumab plus lapatinib vs trastuzumab alone (HR, 0.47; 95% CI, 0.27-0.83; P = .009). Overall, 275 of 618 gene expression signatures (44.5%) were significantly associated with pCR and 9 of 618 (1.5%) with EFS. The ERBB2/HER2 amplicon and multiple immune signatures were significantly associated with pCR. Luminal-related signatures were associated with lower pCR rates but better EFS, especially among patients with residual disease and independent of hormone receptor status. There was significant adjusted HR for pCR ranging from 0.45 to 0.81 (higher pCR) and 1.21-1.94 (lower pCR rate); significant adjusted HR for EFS ranged from 0.71 to 0.94. Conclusions and relevance: In patients with ERBB2/HER2-positive EBC, the association between pCR and EFS differed by tumor intrinsic subtype, and the benefit of dual ERBB2/HER2 blockade was limited to ERBB2-enriched tumors. Immune-activated signatures were concordantly associated with higher pCR rates and better EFS, whereas luminal signatures were associated with lower pCR rates.

Breast Cancer Index and Prediction of Extended Aromatase Inhibitor Therapy Benefit in Hormone Receptor-Positive Breast Cancer from the NRG Oncology/NSABP B-42 Trial.

PURPOSE: BCI (H/I) has been shown to predict extended endocrine therapy (EET) benefit. We examined BCI (H/I) for EET benefit prediction in NSABP B-42, which evaluated extended letrozole therapy (ELT) in patients with hormone receptor-positive breast cancer after 5 years of ET. EXPERIMENTAL DESIGN: A stratified Cox model was used to analyze RFI as the primary endpoint, with DR, BCFI, and DFS as secondary endpoints. Because of a nonproportional effect of ELT on DR, time-dependent analyses were performed. RESULTS: The translational cohort included 2,178 patients (45% BCI (H/I)-High, 55% BCI (H/I)-Low). ELT showed an absolute 10-year RFI benefit of 1.6% (P = 0.10), resulting in an underpowered primary analysis (50% power). ELT benefit and BCI (H/I) did not show a significant interaction for RFI (BCI (H/I)-Low: 10 years absolute benefit 1.1% [HR, 0.70; 95% confidence interval (CI), 0.43-1.12; P = 0.13]; BCI (H/I)-High: 2.4% [HR, 0.83; 95% CI, 0.55-1.26; P = 0.38]; Pinteraction = 0.56). Time-dependent DR analysis showed that after 4 years, BCI (H/I)-High patients had significant ELT benefit (HR = 0.29; 95% CI, 0.12-0.69; P < 0.01), whereas BCI (H/I)-Low patients were less likely to benefit (HR, 0.68; 95% CI, 0.33-1.39; P = 0.29; Pinteraction = 0.14). Prediction of ELT benefit by BCI (H/I) was more apparent in the HER2- subset after 4 years (ELT-by-BCI (H/I) Pinteraction = 0.04). CONCLUSIONS: BCI (H/I)-High versus BCI (H/I)-Low did not show a statistically significant difference in ELT benefit for the primary endpoint (RFI). However, in time-dependent DR analysis, BCI (H/I)-High patients experienced statistically significant benefit from ELT after 4 years, whereas (H/I)-Low patients did not. Because BCI (H/I) has been validated as a predictive marker of EET benefit in other trials, additional follow-up may enable further characterization of BCI's predictive ability.

Machine Learning Predicts Oxaliplatin Benefit in Early Colon Cancer.

PURPOSE: A combination of fluorouracil, leucovorin, and oxaliplatin (FOLFOX) is the standard for adjuvant therapy of resected early-stage colon cancer (CC). Oxaliplatin leads to lasting and disabling neurotoxicity. Reserving the regimen for patients who benefit from oxaliplatin would maximize efficacy and minimize unnecessary adverse side effects. METHODS: We trained a new machine learning model, referred to as the colon oxaliplatin signature (COLOXIS) model, for predicting response to oxaliplatin-containing regimens. We examined whether COLOXIS was predictive of oxaliplatin benefits in the CC adjuvant setting among 1,065 patients treated with 5-fluorouracil plus leucovorin (FULV; n = 421) or FULV + oxaliplatin (FOLFOX; n = 644) from NSABP C-07 and C-08 phase III trials. The COLOXIS model dichotomizes patients into COLOXIS+ (oxaliplatin responder) and COLOXIS- (nonresponder) groups. Eight-year recurrence-free survival was used to evaluate oxaliplatin benefits within each of the groups, and the predictive value of the COLOXIS model was assessed using the P value associated with the interaction term (int P) between the model prediction and the treatment effect. RESULTS: Among 1,065 patients, 526 were predicted as COLOXIS+ and 539 as COLOXIS-. The COLOXIS+ prediction was associated with prognosis for FULV-treated patients (hazard ratio [HR], 1.52 [95% CI, 1.07 to 2.15]; P = .017). The model was predictive of oxaliplatin benefits: COLOXIS+ patients benefited from oxaliplatin (HR, 0.65 [95% CI, 0.48 to 0.89]; P = .0065; int P = .03), but COLOXIS- patients did not (COLOXIS- HR, 1.08 [95% CI, 0.77 to 1.52]; P = .65). CONCLUSION: The COLOXIS model is predictive of oxaliplatin benefits in the CC adjuvant setting. The results provide evidence supporting a change in CC adjuvant therapy: reserve oxaliplatin only for COLOXIS+ patients, but further investigation is warranted.

iGenSig-Rx: an integral genomic signature based white-box tool for modeling cancer therapeutic responses using multi-omics data.

Multi-omics sequencing is expected to become clinically routine within the next decade and transform clinical care. However, there is a paucity of viable and interpretable genome-wide modeling methods that can facilitate rational selection of patients for tailored intervention. Here we develop an integral genomic signature-based method called iGenSig-Rx as a white-box tool for modeling therapeutic response based on clinical trial datasets with improved cross-dataset applicability and tolerance to sequencing bias. This method leverages high-dimensional redundant genomic features to address the challenges of cross-dataset modeling, a concept similar to the use of redundant steel rods to reinforce the pillars of a building. Using genomic datasets for HER2 targeted therapies, the iGenSig-Rx model demonstrates stable predictive power across four independent clinical trials. More importantly, the iGenSig-Rx model offers the level of transparency much needed for clinical application, allowing for clear explanations as to how the predictions are produced, how the features contribute to the prediction, and what are the key underlying pathways. We expect that iGenSig-Rx as a class of biologically interpretable multi-omics modeling methods will have broad applications in big-data based precision oncology. The R package is available: https://github.com/wangxlab/iGenSig-Rx. NOTE: the Github website will be released upon publication and the R package is available for review through google drive: https://drive.google.com/drive/folders/1KgecmUoon9-h2Dg1rPCyEGFPOp28Ols3?usp=sharing.

Identification of tumor-intrinsic drivers of immune exclusion in acral melanoma.

Acral melanoma (AM) has distinct characteristics as compared with cutaneous melanoma and exhibits poor response to immune checkpoint inhibitors (ICIs). Tumor-intrinsic mechanisms of immune exclusion have been identified in many cancers but less studied in AM. We characterized clinically annotated tumors from patients diagnosed with AM at our institution in correlation with ICI response using whole transcriptome RNAseq, whole exome sequencing, CD8 immunohistochemistry, and multispectral immunofluorescence imaging. A defined interferon-γ-associated T cell-inflamed gene signature was used to categorize tumors into non-T cell-inflamed and T cell-inflamed phenotypes. In combination with AM tumors from two published studies, we systematically assessed the immune landscape of AM and detected differential gene expression and pathway activation in a non-T cell-inflamed tumor microenvironment (TME). Two single-cell(sc) RNAseq AM cohorts and 11 bulk RNAseq cohorts of various tumor types were used for independent validation on pathways associated with lack of ICI response. In total, 892 specimens were included in this study. 72.5% of AM tumors showed low expression of the T cell-inflamed gene signature, with 23.9% of total tumors categorized as the non-T cell-inflamed phenotype. Patients of low CD3+CD8+PD1+ intratumoral T cell density showed poor prognosis. We identified 11 oncogenic pathways significantly upregulated in non-T cell-inflamed relative to T cell-inflamed TME shared across all three acral cohorts (MYC, HGF, MITF, VEGF, EGFR, SP1, ERBB2, TFEB, SREBF1, SOX2, and CCND1). scRNAseq analysis revealed that tumor cell-expressing pathway scores were significantly higher in low versus high T cell-infiltrated AM tumors. We further demonstrated that the 11 pathways were enriched in ICI non-responders compared with responders across cancers, including AM, cutaneous melanoma, triple-negative breast cancer, and non-small cell lung cancer. Pathway activation was associated with low expression of interferon stimulated genes, suggesting suppression of antigen presentation. Across the 11 pathways, fatty acid synthase and CXCL8 were unifying downstream target molecules suggesting potential nodes for therapeutic intervention. A unique set of pathways is associated with immune exclusion and ICI resistance in AM. These data may inform immunotherapy combinations for immediate clinical translation.

Identification of tumor-intrinsic drivers of immune exclusion in acral melanoma.

Background: Acral melanoma (AM) has distinct characteristics as compared to cutaneous melanoma and exhibits poor response to immune checkpoint inhibitors (ICI). Tumor-intrinsic mechanisms of immune exclusion have been identified in many cancers but less studied in AM. Methods: We characterized clinically annotated tumors from patients diagnosed with AM at our institution in correlation with ICI response using whole transcriptome RNAseq, whole exome sequencing, CD8 immunohistochemistry, and multispectral immunofluorescence imaging. A defined interferon-γ-associated T cell-inflamed gene signature was used to categorize tumors into non-T cell-inflamed and T cell-inflamed phenotypes. In combination with AM tumors from two published studies, we systematically assessed the immune landscape of AM and detected differential gene expression and pathway activation in a non-T cell-inflamed tumor microenvironment (TME). Two single-cell(sc) RNAseq AM cohorts and 11 bulk RNAseq cohorts of various tumor types were used for independent validation on pathways associated with lack of ICI response. In total, 892 specimens were included in this study. Results: 72.5% of AM tumors showed low expression of the T cell-inflamed gene signature, with 23.9% of total tumors categorized as the non-T cell-inflamed phenotype. Patients of low CD3 + CD8 + PD1 + intratumoral T cell density showed poor prognosis. We identified 11 oncogenic pathways significantly upregulated in non-T cell-inflamed relative to T cell-inflamed TME shared across all three acral cohorts (MYC, HGF, MITF, VEGF, EGFR, SP1, ERBB2, TFEB, SREBF1, SOX2, and CCND1). scRNAseq analysis revealed that tumor cell-expressing pathway scores were significantly higher in low vs high T cell-infiltrated AM tumors. We further demonstrated that the 11 pathways were enriched in ICI non-responders compared to responders across cancers, including acral melanoma, cutaneous melanoma, triple-negative breast cancer, and non-small cell lung cancer. Pathway activation was associated with low expression of interferon stimulated genes, suggesting suppression of antigen presentation. Across the 11 pathways, fatty acid synthase and CXCL8 were unifying downstream target molecules suggesting potential nodes for therapeutic intervention. Conclusions: A unique set of pathways is associated with immune exclusion and ICI resistance in AM. These data may inform immunotherapy combinations for immediate clinical translation.

WCRC-25: A novel luminal Invasive Lobular Carcinoma cell line model.

Breast cancer is categorized by the molecular and histologic presentation of the tumor, with the major histologic subtypes being No Special Type (NST) and Invasive Lobular Carcinoma (ILC). ILC are characterized by growth in a single file discohesive manner with stromal infiltration attributed to their hallmark pathognomonic loss of E-cadherin ( CDH1 ). Few ILC cell line models are available to researchers. Here we report the successful establishment and characterization of a novel ILC cell line, WCRC-25, from a metastatic pleural effusion from a postmenopausal Caucasian woman with metastatic ILC. WCRC-25 is an ER-negative luminal epithelial ILC cell line with both luminal and Her2-like features. It exhibits anchorage independent growth and haptotactic migration towards Collagen I. Sequencing revealed a CDH1 Q706* truncating mutation, together with mutations in FOXA1, CTCF, BRCA2 and TP53 , which were also seen in a series of metastatic lesions from the patient. Copy number analyses revealed amplification and deletion of genes frequently altered in ILC while optical genome mapping revealed novel structural rearrangements. RNA-seq analysis comparing the primary tumor, metastases and the cell line revealed signatures for cell cycle progression and receptor tyrosine kinase signaling. To assess targetability, we treated WCRC-25 with AZD5363 and Alpelisib confirming WCRC-25 as susceptible to PI3K/AKT signaling inhibition as predicted by our RNA sequencing analysis. In conclusion, we report WCRC-25 as a novel ILC cell line with promise as a valuable research tool to advance our understanding of ILC and its therapeutic vulnerabilities. Financial support: The work was in part supported by a Susan G Komen Leadership Grant to SO (SAC160073) and NCI R01 CA252378 (SO/AVL). AVL and SO are Komen Scholars, Hillman Foundation Fellows and supported by BCRF. This project used the UPMC Hillman Cancer Center and Tissue and Research Pathology/Pitt Biospecimen Core shared resource which is supported in part by award P30CA047904. This research was also supported in part by the University of Pittsburgh Center for Research Computing, RRID:SCR_022735, through the resources provided. Specifically, this work used the HTC cluster, which is supported by NIH award number S10OD028483. Finally, partial support was provided by the Magee-Womens Research Institute and Foundation, The Shear Family Foundation, and The Metastatic Breast Cancer Network.

Vascular endothelial profilin-1 drives a protumorigenic tumor microenvironment and tumor progression in renal cancer.

Overexpression of actin-binding protein profilin-1 (Pfn1) correlates with advanced disease features and adverse clinical outcome of patients with clear cell renal carcinoma, the most prevalent form of renal cancer. We previously reported that Pfn1 is predominantly overexpressed in tumor-associated vascular endothelial cells in human clear cell renal carcinoma. In this study, we combined in vivo strategies involving endothelial cell-specific depletion and overexpression of Pfn1 to demonstrate a role of vascular endothelial Pfn1 in promoting tumorigenicity and enabling progressive growth and metastasis of renal carcinoma cells in a syngeneic orthotopic mouse model of kidney cancer. We established an important role of endothelial Pfn1 in tumor angiogenesis and further identified endothelial Pfn1-dependent regulation of several pro- (VEGF, SERPINE1, CCL2) and anti-angiogenic factors (platelet factor 4) in vivo. Endothelial Pfn1 overexpression increases tumor infiltration by macrophages and concomitantly diminishes tumor infiltration by T cells including CD8+ T cells in vivo, correlating with the pattern of endothelial Pfn1-dependent changes in tumor abundance of several prominent immunomodulatory cytokines. These data were also corroborated by multiplexed quantitative immunohistochemistry and immune deconvolution analyses of RNA-seq data of clinical samples. Guided by Upstream Regulator Analysis of tumor transcriptome data, we further established endothelial Pfn1-induced Hif1α elevation and suppression of STAT1 activation. In conclusion, this study demonstrates for the first time a direct causal relationship between vascular endothelial Pfn1 dysregulation, immunosuppressive tumor microenvironment, and disease progression with mechanistic insights in kidney cancer. Our study also provides a conceptual basis for targeting Pfn1 for therapeutic benefit in kidney cancer.

Immune landscape in invasive ductal and lobular breast cancer reveals a divergent macrophage-driven microenvironment.

T cell-centric immunotherapies have shown modest clinical benefit thus far for estrogen receptor-positive (ER+) breast cancer. Despite accounting for 70% of all breast cancers, relatively little is known about the immunobiology of ER+ breast cancer in women with invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC). To investigate this, we performed phenotypic, transcriptional and functional analyses for a cohort of treatment-naive IDC (n = 94) and ILC (n = 87) tumors. We show that macrophages, and not T cells, are the predominant immune cells infiltrating the tumor bed and the most transcriptionally diverse cell subset between IDC and ILC. Analysis of cellular neighborhoods revealed an interplay between macrophages and T cells associated with longer disease-free survival in IDC but not ILC. Our datasets provide a rich resource for further interrogation into immune cell dynamics in ER+ IDC and ILC and highlight macrophages as a potential target for ER+ breast cancer.

CRISPRa-induced upregulation of human LAMA1 compensates for LAMA2-deficiency in Merosin-deficient congenital muscular dystrophy.

Merosin-deficient congenital muscular dystrophy (MDC1A) is an autosomal recessive disorder caused by mutations in the LAMA2 gene, resulting in a defective form of the extracellular matrix protein laminin-α2 (LAMA2). Individuals diagnosed with MDC1A exhibit progressive muscle wasting and declining neuromuscular functions. No treatments for this disorder are currently available. We previously showed that postnatal Lama1 upregulation, achieved through CRISPR activation (CRISPRa), compensates for Lama2 deficiency and prevents neuromuscular pathophysiology in a mouse model of MDC1A. In this study, we assessed the feasibility of upregulating human LAMA1 as a potential therapeutic strategy for individuals with MDC1A, regardless of their mutations. We hypothesized that CRISPRa-mediated upregulation of human LAMA1 would compensate for the lack of LAMA2 and rescue cellular abnormalities in MDC1A fibroblasts. Global transcriptomic and pathway enrichment analyses of fibroblasts collected from individuals carrying pathogenic LAMA2 mutations, compared with healthy controls, indicated higher expression of transcripts encoding proteins that contribute to wound healing, including Transforming Growth Factor-ß (TGF-ß) and Fibroblast Growth Factor (FGF). These findings were supported by wound-healing assays indicating that MDC1A fibroblasts migrated significantly more rapidly than the controls. Subsequently, we treated the MDC1A fibroblasts with SadCas9-2XVP64 and sgRNAs targeting the LAMA1 promoter. We observed robust LAMA1 expression, which was accompanied by significant decreases in cell migration and expression of FGFR2, TGF-ß2, and ACTA2, which are involved in the wound-healing mechanism in MDC1A fibroblasts. Collectively, our data suggest that CRISPRa-mediated LAMA1 upregulation may be a feasible mutation-independent therapeutic approach for MDC1A. This strategy might be adapted to address other neuromuscular diseases and inherited conditions in which strong compensatory mechanisms have been identified.

Biomarker Data from the Phase III KATHERINE Study of Adjuvant T-DM1 versus Trastuzumab for Residual Invasive Disease after Neoadjuvant Therapy for HER2-Positive Breast Cancer.

PURPOSE: In KATHERINE, adjuvant T-DM1 reduced risk of disease recurrence or death by 50% compared with trastuzumab in patients with residual invasive breast cancer after neoadjuvant therapy (NAT) comprised of HER2-targeted therapy and chemotherapy. This analysis aimed to identify biomarkers of response and differences in biomarker expression before and after NAT. EXPERIMENTAL DESIGN: Exploratory analyses investigated the relationship between invasive disease-free survival (IDFS) and HER2 protein expression/gene amplification, PIK3CA hotspot mutations, and gene expression of HER2, PD-L1, CD8, predefined immune signatures, and Prediction Analysis of Microarray 50 intrinsic molecular subtypes, classified by Absolute Intrinsic Molecular Subtyping. HER2 expression on paired pre- and post-NAT samples was examined. RESULTS: T-DM1 appeared to improve IDFS versus trastuzumab across most biomarker subgroups, except the HER2 focal expression subgroup. High versus low HER2 gene expression in residual disease was associated with worse outcomes with trastuzumab [HR, 2.02; 95% confidence interval (CI), 1.32-3.11], but IDFS with T-DM1 was independent of HER2 expression level (HR, 1.01; 95% CI, 0.56-1.83). Low PD-L1 gene expression in residual disease was associated with worse outcomes with trastuzumab (HR, 0.66; 95% CI, 0.44-1.00), but not T-DM1 (HR, 1.05; 95% CI, 0.59-1.87). PIK3CA mutations were not prognostic. Increased variability in HER2 expression was observed in post-NAT versus paired pre-NAT samples. CONCLUSIONS: T-DM1 appears to overcome HER2 resistance. T-DM1 benefit does not appear dependent on immune activation, but these results do not rule out an influence of the tumor immune microenvironment on the degree of response.

The Great Immune Escape: Understanding the Divergent Immune Response in Breast Cancer Subtypes.

Breast cancer, the most common type of cancer affecting women, encompasses a collection of histologic (mainly ductal and lobular) and molecular subtypes exhibiting diverse clinical presentation, disease trajectories, treatment options, and outcomes. Immunotherapy has revolutionized treatment for some solid tumors but has shown limited promise for breast cancers. In this review, we summarize recent advances in our understanding of the complex interactions between tumor and immune cells in subtypes of breast cancer at the cellular and microenvironmental levels. We aim to provide a perspective on opportunities for future immunotherapy agents tailored to specific features of each subtype of breast cancer. SIGNIFICANCE: Although there are currently over 200 ongoing clinical trials testing immunotherapeutics, such as immune-checkpoint blockade agents, these are largely restricted to the triple-negative and HER2+ subtypes and primarily focus on T cells. With the rapid expansion of new in vitro, in vivo, and clinical data, it is critical to identify and highlight the challenges and opportunities unique for each breast cancer subtype to drive the next generation of treatments that harness the immune system.

Mixed invasive ductal lobular carcinoma is clinically and pathologically more similar to invasive lobular than ductal carcinoma.

BACKGROUND: Mixed invasive ductal lobular carcinoma (mDLC) remains a poorly understood subtype of breast cancer composed of coexisting ductal and lobular components. METHODS: We sought to describe clinicopathologic characteristics and determine whether mDLC is clinically more similar to invasive ductal carcinoma (IDC) or invasive lobular carcinoma (ILC), using data from patients seen at the University of Pittsburgh Medical Center. RESULTS: We observed a higher concordance in clinicopathologic characteristics between mDLC and ILC, compared to IDC. There is a trend for higher rates of successful breast-conserving surgery after neoadjuvant chemotherapy in patients with mDLC compared to patients with ILC, in which it is known to be lower than in those with IDC. Metastatic patterns of mDLC demonstrate a propensity to develop in sites characteristic of both IDC and ILC. A meta-analysis evaluating mDLC showed shared features with both ILC and IDC with significantly more ER-positive and fewer high grades in mDLC compared to IDC, although mDLCs were significantly smaller and included fewer late-stage tumours compared to ILC. CONCLUSIONS: These findings support clinicopathologic characteristics of mDLC driven by individual ductal vs lobular components and given the dominance of lobular pathology, mDLC features are often more similar to ILC than IDC. This study exemplifies the complexity of mixed disease.

Improved preoperative risk stratification in endometrial carcinoma patients: external validation of the ENDORISK Bayesian network model in a large population-based case series.

PURPOSE: Preoperative risk stratification of newly diagnosed endometrial carcinoma (EC) patients has been hindered by only moderate prediction performance for many years. Recently ENDORISK, a Bayesian network model, showed high predictive performance. It was the aim of this study to validate ENDORISK by applying the model to a population-based case series of EC patients. METHODS: ENDORISK was applied to a retrospective cohort of women surgically treated for EC from 2003 to 2013. Prediction accuracy for LNM as well as 5-year DSS was investigated. The model's overall performance was quantified by the Brier score, discriminative performance by area under the curve (AUC). RESULTS: A complete dataset was evaluable from 247 patients. 78.1% cases were endometrioid histotype. The majority of patients (n = 156;63.2%) had stage IA disease. Overall, positive lymph nodes were found in 20 (8.1%) patients. Using ENDORISK predicted probabilities, most (n = 156;63.2%) patients have been assigned to low or very low risk group with a false-negative rate of 0.6%. AUC for LNM prediction was 0.851 [95% confidence interval (CI) 0.761-0.941] with a Brier score of 0.06. For 5-year DSS the AUC was 0.698 (95% CI 0.595-0.800) as Brier score has been calculated 0.09. CONCLUSIONS: We were able to successfully validate ENDORISK for prediction of LNM and 5-year DSS. Next steps will now have to focus on ENDORISK performance in daily clinical practice. In addition, incorporating TCGA-derived molecular subtypes will be of key importance for future extended use. This study may support further promoting of data-based decision-making tools for personalized treatment of EC.

Visual Assistance in Development and Validation of Bayesian Networks for Clinical Decision Support.

The development and validation of Clinical Decision Support Models (CDSM) based on Bayesian networks (BN) is commonly done in a collaborative work between medical researchers providing the domain expertise and computer scientists developing the decision support model. Although modern tools provide facilities for data-driven model generation, domain experts are required to validate the accuracy of the learned model and to provide expert knowledge for fine-tuning it while computer scientists are needed to integrate this knowledge in the learned model (hybrid modeling approach). This generally time-expensive procedure hampers CDSM generation and updating. To address this problem, we developed a novel interactive visual approach allowing medical researchers with less knowledge in CDSM to develop and validate BNs based on domain specific data mainly independently and thus, diminishing the need for an additional computer scientist. In this context, we abstracted and simplified the common workflow in BN development as well as adjusted the workflow to medical experts' needs. We demonstrate our visual approach with data of endometrial cancer patients and evaluated it with six medical researchers who are domain experts in the gynecological field.

MRTF promotes breast cancer cell motility through SRF-dependent upregulation of DIAPH3 expression.

Dysregulated actin cytoskeleton gives rise to aberrant cell motility and metastatic spread of tumor cells. The MRTF-SRF transcriptional complex plays a key role in regulating the expressions of actin cytoskeleton-modulatory genes. In this study, we demonstrate that MRTF's interaction with SRF is critical for migration and invasion of breast cancer cells. Disruption of the MRTF-SRF interaction suppresses membrane dynamics affecting the frequency and the effectiveness of membrane protrusion during cell motility. Consistent with these phenotypic changes, we further show that MRTF promotes actin polymerization at the leading edge, a key aspect of membrane protrusion, and migration of breast cancer cells through upregulating the expression of formin-family actin nucleating/elongating protein encoding gene DIAPH3 in an SRF-dependent manner. In support of these findings, multiplexed quantitative immunohistochemistry and transcriptome analyses of clinical specimens of breast cancer further demonstrate a positive correlation between nuclear localization of MRTF with malignant traits of cancer cells as well as enrichment of MRTF/SRF gene signature in distant metastases relative to primary tumors. In conclusion, this study for the first time links the MRTF/SRF signaling axis to cell migration through the regulation of a specific actin-binding protein, and provides evidence for an association between MRTF/SRF activity and malignancy in human breast cancer.

Minimal Residual Disease-Directed Adjuvant Therapy for Patients With Early-Stage Colon Cancer: CIRCULATE-US.

BACKGROUND: The ability to detect circulating tumor DNA (ctDNA), a novel surrogate for minimal residual disease (MRD) for patients with solid tumors, has significantly evolved over the past decade. Several studies have shown that ctDNA may provide clinical insight into the biological dynamics of MRD. The CIRCULATE-US (NRG-GI008; NCT05174169) trial will aim to address the role of ctDNA for risk stratification to intensify and deintensify adjuvant chemotherapy for patients with early-stage colon cancer. METHODS: CIRCULATE-US, a prospective phase 2/3 randomized trial, is investigating the molecular dynamics and prognostic role of ctDNA (evaluated by Natera's Signatera assay) for patients with resected colon cancer. Patients with negative postoperative ctDNA will be enrolled in cohort A and randomized to receive either immediate treatment with 5-fluorouracil and folinic acid or capecitabine plus oxaliplatin (FOLFOX6 or CAPEOX; Arm 1) or serial ctDNA surveillance with delayed adjuvant therapy (Arm 2). Patients randomized to Arm 2 with subsequent positive ctDNA results will be enrolled in cohort B for a second randomization to receive either FOLFOX6/CAPEOX (Arm 3) or 5-fluorouracil, folinic acid, oxaliplatin, and irinotecan (FOLFIRINOX; Arm 4) for 6 months. Patients with positive postoperative ctDNA results will be directly enrolled in cohort B and randomized to receive either FOLFOX6/CAPEOX (Arm 3) or FOLFIRINOX (Arm 4). Patients with stage II or stage IIIC colon cancer with positive ctDNA results (tested as standard of care with commercial testing) will be eligible for enrollment in cohort B. The primary end point for cohort A is time to positive ctDNA status for phase 2 and disease-free survival for phase 3 with a noninferiority design. The primary end point for cohort B is disease-free survival for both phase 2 and phase 3 with a superiority design. DISCUSSION: CIRCULATE-US will aim to understand postoperative ctDNA dynamics in early-stage colon cancer and will investigate escalation and de-escalation approaches by using ctDNA status as a surrogate for MRD status.