Predictors of Response to CDK4/6i Retrial After Prior CDK4/6i Failure in ER+ Metastatic Breast Cancer.

After disease progression on endocrine therapy (ET) plus a CDK4/6 inhibitor, there is no standardized sequence for subsequent treatment lines for estrogen receptor positive (ER+) metastatic breast cancer (MBC). CDK4/6i retrial as a treatment strategy is commonplace in modern clinical practice; however, the available prospective data investigating this strategy have had inconclusive results. To frame this data in a real-world context, we performed a retrospective analysis assessing the efficacy of CDK4/6is in 195 patients who had previous exposure to CDK4/6i in a prior treatment line at our institution. Among patients who had stopped a CDK4/6i due to toxicity, CDK4/6i retrial either immediately after with a different CDK4/6i or in a further treatment line with the same initial CDK4/6i was both safe and effective, with a median time to treatment failure (TTF) of 10.1 months (95%CI, 4.8-16.9). For patients whose disease progressed on a prior CDK4/6i, we demonstrated comparable median TTFs for patients rechallenged with the same CDK4/6i (4.3 months, 95%CI 3.2-5.5) and with a different CDK4/6i (4.7 months, 95%CI 3.7-6.0) when compared to the recent PACE, PALMIRA, and MAINTAIN trials. Exploratory genomic analysis suggested that the presence of mutations known to confer CDK4/6i resistance, such as TP53 mutations, CDK4 amplifications, and RB1 or FAT1 loss of function mutations may be molecular biomarkers predictive of CDK4/6i retrial failure.

Preoperative immune checkpoint inhibition and cryoablation in early-stage breast cancer.

Local cryoablation can engender systemic immune activation/anticancer responses in tumors otherwise resistant to immune checkpoint blockade (ICB). We evaluated the safety/tolerability of preoperative cryoablation plus ipilimumab and nivolumab in 5 early-stage/resectable breast cancers. The primary endpoint was met when all 5 patients underwent standard-of-care primary breast surgery undelayedly. Three patients developed transient hyperthyroidism; one developed grade 4 liver toxicity (resolved with supportive management). We compared this strategy with cryoablation and/or ipilimumab. Dual ICB plus cryoablation induced higher expression of T cell activation markers and serum Th1 cytokines and reduced immunosuppressive serum CD4+PD-1hi T cells, improving effector-to-suppressor T cell ratio. After dual ICB and before cryoablation, T cell receptor sequencing of 4 patients showed increased T cell clonality. In this small subset of patients, we provide preliminary evidence that preoperative cryoablation plus ipilimumab and nivolumab is feasible, inducing systemic adaptive immune activation potentially more robust than cryoablation with/without ipilimumab.

Redox signalling regulates breast cancer metastasis via phenotypic and metabolic reprogramming due to p63 activation by HIF1α.

BACKGROUND: Redox signaling caused by knockdown (KD) of Glutathione Peroxidase 2 (GPx2) in the PyMT mammary tumour model promotes metastasis via phenotypic and metabolic reprogramming. However, the tumour cell subpopulations and transcriptional regulators governing these processes remained unknown. METHODS: We used single-cell transcriptomics to decipher the tumour cell subpopulations stimulated by GPx2 KD in the PyMT mammary tumour and paired pulmonary metastases. We analyzed the EMT spectrum across the various tumour cell clusters using pseudotime trajectory analysis and elucidated the transcriptional and metabolic regulation of the hybrid EMT state. RESULTS: Integration of single-cell transcriptomics between the PyMT/GPx2 KD primary tumour and paired lung metastases unraveled a basal/mesenchymal-like cluster and several luminal-like clusters spanning an EMT spectrum. Interestingly, the luminal clusters at the primary tumour gained mesenchymal gene expression, resulting in epithelial/mesenchymal subpopulations fueled by oxidative phosphorylation (OXPHOS) and glycolysis. By contrast, at distant metastasis, the basal/mesenchymal-like cluster gained luminal and mesenchymal gene expression, resulting in a hybrid subpopulation using OXPHOS, supporting adaptive plasticity. Furthermore, p63 was dramatically upregulated in all hybrid clusters, implying a role in regulating partial EMT and MET at primary and distant sites, respectively. Importantly, these effects were reversed by HIF1α loss or GPx2 gain of function, resulting in metastasis suppression. CONCLUSIONS: Collectively, these results underscored a dramatic effect of redox signaling on p63 activation by HIF1α, underlying phenotypic and metabolic plasticity leading to mammary tumour metastasis.

Dynamic network curvature analysis of gene expression reveals novel potential therapeutic targets in sarcoma.

Network properties account for the complex relationship between genes, making it easier to identify complex patterns in their interactions. In this work, we leveraged these network properties for dual purposes. First, we clustered pediatric sarcoma tumors using network information flow as a similarity metric, computed by the Wasserstein distance. We demonstrate that this approach yields the best concordance with histological subtypes, validated against three state-of-the-art methods. Second, to identify molecular targets that would be missed by more conventional methods of analysis, we applied a novel unsupervised method to cluster gene interactomes represented as networks in pediatric sarcoma. RNA-Seq data were mapped to protein-level interactomes to construct weighted networks that were then subjected to a non-Euclidean, multi-scale geometric approach centered on a discrete notion of curvature. This provides a measure of the functional association among genes in the context of their connectivity. In confirmation of the validity of this method, hierarchical clustering revealed the characteristic EWSR1-FLI1 fusion in Ewing sarcoma. Furthermore, assessing the effects of in silico edge perturbations and simulated gene knockouts as quantified by changes in curvature, we found non-trivial gene associations not previously identified.

Functional transcriptional signatures for tumor-type-agnostic phenotype prediction.

Cancer transcriptional patterns exhibit both shared and unique features across diverse cancer types, but whether these patterns are sufficient to characterize the full breadth of tumor phenotype heterogeneity remains an open question. We hypothesized that cancer transcriptional diversity mirrors patterns in normal tissues optimized for distinct functional tasks. Starting with normal tissue transcriptomic profiles, we use non-negative matrix factorization to derive six distinct transcriptomic phenotypes, called archetypes, which combine to describe both normal tissue patterns and variations across a broad spectrum of malignancies. We show that differential enrichment of these signatures correlates with key tumor characteristics, including overall patient survival and drug sensitivity, independent of clinically actionable DNA alterations. Additionally, we show that in HR+/HER2-breast cancers, metastatic tumors adopt transcriptomic signatures consistent with the invaded tissue. Broadly, our findings suggest that cancer often arrogates normal tissue transcriptomic characteristics as a component of both malignant progression and drug response. This quantitative framework provides a strategy for connecting the diversity of cancer phenotypes and could potentially help manage individual patients.

Impact of reactive changes on multigene testing: histopathologic analysis of low-grade breast cancers with high-risk 21-gene recurrence scores.

PURPOSE: The 21-gene recurrence score (RS) assay predicts the recurrence risk and magnitude of chemotherapy benefit in patients with invasive breast cancer (BC). This study examined low-grade tumors yielding a high-risk RS and their outcomes.Kindly check the edit made in the article titleOk  METHODS: We compared patients with grade 1 BC and a high-risk RS to those with low-risk RS. Histologic sections were reviewed and features reported to elevate the RS were noted, mainly biopsy cavity and reactive stromal changes (BXC). RESULTS: A total of 54 patients had high-risk RS (median RS of 28, range 26-36). On review, BXC were seen in all cases. Thirty BCs in this group also had low to negative PR. Treatment regimens included: chemoendocrine therapy (63%), endocrine therapy alone (31%) and no adjuvant therapy (6%). There were no additional breast cancer events over a median follow-up of 54.0 months (range 6.2 to 145.3). A total of 108 patients had low-risk RS (median RS of 7, range 0-9). BXC were seen in 47% of cases and none were PR negative. One patient had a recurrence at 64.8 months while the rest had no additional events over a median of 68.1 months (2.4 to 100). CONCLUSION: We provide further evidence that reactive stromal changes and/or low-PR scores enhance the elevation of the RS. A high-RS result in low grade, PR-positive BC may not reflect actual risk and any suspected discrepancies should be discussed with the management teams. Multigene testing results should be interpreted after correlation with pathologic findings to optimize patient care.

Wasserstein HOG: Local Directionality Extraction via Optimal Transport.

Directionally sensitive radiomic features including the histogram of oriented gradient (HOG) have been shown to provide objective and quantitative measures for predicting disease outcomes in multiple cancers. However, radiomic features are sensitive to imaging variabilities including acquisition differences, imaging artifacts and noise, making them impractical for using in the clinic to inform patient care. We treat the problem of extracting robust local directionality features by mapping via optimal transport a given local image patch to an iso-intense patch of its mean. We decompose the transport map into sub-work costs each transporting in different directions. To test our approach, we evaluated the ability of the proposed approach to quantify tumor heterogeneity from magnetic resonance imaging (MRI) scans of brain glioblastoma multiforme, computed tomography (CT) scans of head and neck squamous cell carcinoma as well as longitudinal CT scans in lung cancer patients treated with immunotherapy. By considering the entropy difference of the extracted local directionality within tumor regions, we found that patients with higher entropy in their images, had significantly worse overall survival for all three datasets, which indicates that tumors that have images exhibiting flows in many directions may be more malignant. This may seem to reflect high tumor histologic grade or disorganization. Furthermore, by comparing the changes in entropy longitudinally using two imaging time points, we found patients with reduction in entropy from baseline CT are associated with longer overall survival (hazard ratio = 1.95, 95% confidence interval of 1.4-2.8, p = 1.65e-5). The proposed method provides a robust, training free approach to quantify the local directionality contained in images.

Gene interaction network analysis in multiple myeloma detects complex immune dysregulation associated with shorter survival.

The plasma cell cancer multiple myeloma (MM) varies significantly in genomic characteristics, response to therapy, and long-term prognosis. To investigate global interactions in MM, we combined a known protein interaction network with a large clinically annotated MM dataset. We hypothesized that an unbiased network analysis method based on large-scale similarities in gene expression, copy number aberration, and protein interactions may provide novel biological insights. Applying a novel measure of network robustness, Ollivier-Ricci Curvature, we examined patterns in the RNA-Seq gene expression and CNA data and how they relate to clinical outcomes. Hierarchical clustering using ORC differentiated high-risk subtypes with low progression free survival. Differential gene expression analysis defined 118 genes with significantly aberrant expression. These genes, while not previously associated with MM, were associated with DNA repair, apoptosis, and the immune system. Univariate analysis identified 8/118 to be prognostic genes; all associated with the immune system. A network topology analysis identified both hub and bridge genes which connect known genes of biological significance of MM. Taken together, gene interaction network analysis in MM uses a novel method of global assessment to demonstrate complex immune dysregulation associated with shorter survival.

Associations Between Cancer Predisposition Mutations and Clonal Hematopoiesis in Patients With Solid Tumors.

PURPOSE: Clonal hematopoiesis (CH), the expansion of clones in the hematopoietic system, has been linked to different internal and external features such as aging, genetic ancestry, smoking, and oncologic treatment. However, the interplay between mutations in known cancer predisposition genes and CH has not been thoroughly examined in patients with solid tumors. METHODS: We used prospective tumor-blood paired sequencing data from 46,906 patients who underwent Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) testing to interrogate the associations between CH and rare pathogenic or likely pathogenic (P/LP) germline variants. RESULTS: We observed an enrichment of CH-positive patients among those carrying P/LP germline mutations and identified a significant association between P/LP germline variants in ATM and CH. Germline and CH comutation patterns in ATM, TP53, and CHEK2 suggested biallelic inactivation as a potential mediator of clonal expansion. Moreover, we observed that CH-PPM1D mutations, similar to somatic tumor-associated PPM1D mutations, were depleted in patients with P/LP germline mutations in the DNA damage response (DDR) genes ATM, CHEK2, and TP53. Patients with solid tumors and harboring P/LP germline mutations, CH mutations, and mosaicism chromosomal alterations might be at an increased risk of developing secondary leukemia while germline variants in TP53 were identified as an independent risk factor (hazard ratio, 36; P < .001) for secondary leukemias. CONCLUSION: Our results suggest a close relationship between inherited variants and CH mutations within the DDR genes in patients with solid tumors. Associations identified in this study might translate into enhanced clinical surveillance for CH and associated comorbidities in patients with cancer harboring these germline mutations.

New Frontiers in the Role of Locoregional Therapies in Breast Cancer: Proceedings from the Society of Interventional Radiology Foundation Research Consensus Panel.

Emerging evidence regarding the effectiveness of locoregional therapies (LRTs) for breast cancer has prompted investigation of the potential role of interventional radiology (IR) in the care continuum of patients with breast cancer. The Society of Interventional Radiology Foundation invited 7 key opinion leaders to develop research priorities to delineate the role of LRTs in both primary and metastatic breast cancer. The objectives of the research consensus panel were to identify knowledge gaps and opportunities pertaining to the treatment of primary and metastatic breast cancer, establish priorities for future breast cancer LRT clinical trials, and highlight lead technologies that will improve breast cancer outcomes either alone or in combination with other therapies. Potential research focus areas were proposed by individual panel members and ranked by all participants according to each focus area's overall impact. The results of this research consensus panel present the current priorities for the IR research community related to the treatment of breast cancer to investigate the clinical impact of minimally invasive therapies in the current breast cancer treatment paradigm.

Geometric graph neural networks on multi-omics data to predict cancer survival outcomes.

The advance of sequencing technologies has enabled a thorough molecular characterization of the genome in human cancers. To improve patient prognosis predictions and subsequent treatment strategies, it is imperative to develop advanced computational methods to analyze large-scale, high-dimensional genomic data. However, traditional machine learning methods face a challenge in handling the high-dimensional, low-sample size problem that is shown in most genomic data sets. To address this, our group has developed geometric network analysis techniques on multi-omics data in connection with prior biological knowledge derived from protein-protein interactions (PPIs) or pathways. Geometric features obtained from the genomic network, such as Ollivier-Ricci curvature and the invariant measure of the associated Markov chain, have been shown to be predictive of survival outcomes in various cancers. In this study, we propose a novel supervised deep learning method called geometric graph neural network (GGNN) that incorporates such geometric features into deep learning for enhanced predictive power and interpretability. More specifically, we utilize a state-of-the-art graph neural network with sparse connections between the hidden layers based on known biology of the PPI network and pathway information. Geometric features along with multi-omics data are then incorporated into the corresponding layers. The proposed approach utilizes a local-global principle in such a manner that highly predictive features are selected at the front layers and fed directly to the last layer for multivariable Cox proportional-hazards regression modeling. The method was applied to multi-omics data from the CoMMpass study of multiple myeloma and ten major cancers in The Cancer Genome Atlas (TCGA). In most experiments, our method showed superior predictive performance compared to other alternative methods.

Global Oncology Medical Diplomacy Working Group Inaugural Meeting: Defining Worldwide Barriers to Germline Genomics in Cancer Prevention and Management.

We convened an international working group to examine the issues that challenge equity and inclusion in genetic medicine. Specifically, 72 internationally known experts in oncology and cancer genetics from 34 countries (the Global Oncology Medical Diplomacy Working Group), gathered virtually on January 4-5, 2022, for the "Humanity Cancer Germline Convergence and Divergence Cancer Predispositions" conference hosted by Memorial Sloan Kettering Cancer Center, in collaboration with the United Arab Emirates Ministry of Health and the Al Jalila Foundation. The goal of the conference was to broaden transnational understanding of the current state of genetics in preventive and therapeutic cancer medicine, and to define barriers to increased uptake of germline genomics to decrease the international burden of cancer. Here, we highlight the overarching barriers that were defined through this effort. These global barriers to incorporating germline genomics into optimal cancer care can inform ongoing research, collaboration, and advocacy for equitable, cost-effective genomic medicine for populations worldwide.

Targeting stressor-induced dysfunctions in protein-protein interaction networks via epichaperomes.

Diseases are manifestations of complex changes in protein-protein interaction (PPI) networks whereby stressors, genetic, environmental, and combinations thereof, alter molecular interactions and perturb the individual from the level of cells and tissues to the entire organism. Targeting stressor-induced dysfunctions in PPI networks has therefore become a promising but technically challenging frontier in therapeutics discovery. This opinion provides a new framework based upon disrupting epichaperomes - pathological entities that enable dysfunctional rewiring of PPI networks - as a mechanism to revert context-specific PPI network dysfunction to a normative state. We speculate on the implications of recent research in this area for a precision medicine approach to detecting and treating complex diseases, including cancer and neurodegenerative disorders.

Multiomics in primary and metastatic breast tumors from the AURORA US network finds microenvironment and epigenetic drivers of metastasis.

The AURORA US Metastasis Project was established with the goal to identify molecular features associated with metastasis. We assayed 55 females with metastatic breast cancer (51 primary cancers and 102 metastases) by RNA sequencing, tumor/germline DNA exome and low-pass whole-genome sequencing and global DNA methylation microarrays. Expression subtype changes were observed in ~30% of samples and were coincident with DNA clonality shifts, especially involving HER2. Downregulation of estrogen receptor (ER)-mediated cell-cell adhesion genes through DNA methylation mechanisms was observed in metastases. Microenvironment differences varied according to tumor subtype; the ER+/luminal subtype had lower fibroblast and endothelial content, while triple-negative breast cancer/basal metastases showed a decrease in B and T cells. In 17% of metastases, DNA hypermethylation and/or focal deletions were identified near HLA-A and were associated with reduced expression and lower immune cell infiltrates, especially in brain and liver metastases. These findings could have implications for treating individuals with metastatic breast cancer with immune- and HER2-targeting therapies.

Solid-basaloid variant of adenoid cystic carcinoma of the breast with near complete response to neoadjuvant chemotherapy.

Breast adenoid cystic carcinoma (AdCC) is a rare subtype of triple negative breast cancer. Two morphologic variants are described, namely classic AdCC (C-AdCC) and solid basaloid (SB-AdCC). Recent studies have shown that the SB-AdCC variant has significantly worse prognosis than C-AdCC. Due to the rarity of SB-AdCC, no standard recommendations are available for its management. Data on the use and benefit of chemotherapy in patients with SB-AdCC are sparse and the response to neoadjuvant chemotherapy has not been reported. We present the clinical and pathologic findings of a patient with SB-AdCC treated with neoadjuvant chemotherapy who achieved a remarkable pathologic response.

Escalating de-escalation in breast cancer treatment.

Efforts have continually been made to de-escalate treatment for breast cancer, with the goal of balancing oncologic outcomes with complications and patient quality of life. In the early 2000s, two landmark studies firmly established that conservative treatment approaches for breast cancer can be safe and effective. More recently, neoadjuvant chemotherapy has gained momentum as a potential standard of care for breast cancer. An important question has thus arisen: Can neoadjuvant approaches themselves be de-escalated to further minimize adverse treatment effects while maintaining oncological outcomes? In this editorial, we look at the available evidence and assess current trends in treatment de-escalation for women with breast cancer.

Brain radiotherapy, tremelimumab-mediated CTLA-4-directed blockade +/- trastuzumab in patients with breast cancer brain metastases.

Breast cancer brain metastases (BCBM) are a common and devastating complication of metastatic breast cancer with conventional systemic therapies demonstrating limited effectiveness. Consequently, radiotherapy (RT) ± surgery remains the cornerstone of BCBM management. Because preclinical and clinical evidence indicate that immune checkpoint blockade (ICB) may synergize with RT to promote systemic tumor regression, we explored the safety and efficacy of RT and concurrent tremelimumab-mediated cytotoxic T-lymphocyte associated protein 4 (CTLA-4) ICB with tremelimumab ± HER2-directed therapy with trastuzumab for BCBM. Eligible patients had BCBM indicated for brain RT. A Simon two-stage design was adopted to evaluate the efficacy of tremelimumab and RT in 20 patients with human epidermal growth factor receptor normal (HER2-) BCBM. The safety of concurrent RT, tremelimumab, and trastuzumab was evaluated in a cohort of 6 HER2+ patients. The primary endpoint was 12-week non-central nervous system (CNS) disease control rate (DCR). Secondary endpoints included safety, survival, and CNS response. Exploratory correlatives included characterization of peripheral blood immune responses among exceptional responders. Tremelimumab plus RT ± trastuzumab was tolerated with no treatment-related grade 4 adverse events reported. The 12-week non-CNS DCR was 10% (2/20) in the HER2- cohort and 33% (2/6) in the HER2+ cohort. One patient with HER2+ disease experienced a durable partial response with evidence of peripheral T-cell activation. Thus, tremelimumab and RT ± trastuzumab was tolerated. Although modest clinical activity was observed in the HER2- efficacy cohort, encouraging responses were observed in the HER2+ safety cohort. Consequently, a trial to determine efficacy in HER2+ BCBM is planned.Clinical Trial Registration Number: NCT02563925.

Incidence of brain metastases in patients with early HER2-positive breast cancer receiving neoadjuvant chemotherapy with trastuzumab and pertuzumab.

The addition of pertuzumab (P) to trastuzumab (H) and neoadjuvant chemotherapy (NAC) has decreased the risk of distant recurrence in early stage HER2-positive breast cancer. The incidence of brain metastases (BM) in patients who achieved pathological complete response (pCR) versus those who do not is unknown. In this study, we sought the incidence of BM in patients receiving HP-containing NAC as well as survival outcome. We reviewed the medical records of 526 early stage HER2-positive patients treated with an HP-based regimen at Memorial Sloan Kettering Cancer Center (MSKCC), between September 1, 2013 to November 1, 2019. The primary endpoint was to estimate the cumulative incidence of BM in pCR versus non-pCR patients; secondary endpoints included disease free-survival (DFS) and overall survival (OS). After a median follow-up of 3.2 years, 7 out of 286 patients with pCR had a BM while 5 out of 240 non-pCR patients had a BM. The 3-year DFS was significantly higher in the pCR group compared to non-pCR group (95% vs 91 %, p = 0.03) and the same trend was observed for overall survival. In our cohort, despite the better survival outcomes of patients who achieved pCR, we did not observe appreciable differences in the incidence of BM by pCR/non-pCR status. This finding suggests that the BM incidence could not be associated with pCR. Future trials with new small molecules able to cross the blood brain barrier should use more specific biomarkers rather than pCR for patients' selection.

Redox signaling by glutathione peroxidase 2 links vascular modulation to metabolic plasticity of breast cancer.

In search of redox mechanisms in breast cancer, we uncovered a striking role for glutathione peroxidase 2 (GPx2) in oncogenic signaling and patient survival. GPx2 loss stimulates malignant progression due to reactive oxygen species/hypoxia inducible factor-α (HIF1α)/VEGFA (vascular endothelial growth factor A) signaling, causing poor perfusion and hypoxia, which were reversed by GPx2 reexpression or HIF1α inhibition. Ingenuity Pathway Analysis revealed a link between GPx2 loss, tumor angiogenesis, metabolic modulation, and HIF1α signaling. Single-cell RNA analysis and bioenergetic profiling revealed that GPx2 loss stimulated the Warburg effect in most tumor cell subpopulations, except for one cluster, which was capable of oxidative phosphorylation and glycolysis, as confirmed by coexpression of phosphorylated-AMPK and GLUT1. These findings underscore a unique role for redox signaling by GPx2 dysregulation in breast cancer, underlying tumor heterogeneity, leading to metabolic plasticity and malignant progression.